Guide to Cost-benefit Analysis of
Investment Projects
Economic appraisal tool for Cohesion Policy 2014-2020
December 2014
ACKNOWLEDGEMENTS AND DISCLAIMER
Authors: Davide Sartori (Centre for Industrial Studies [CSIL]), Lead author; Gelsomina Catalano, Mario Genco,
Chiara Pancotti, Emanuela Sirtori, Silvia Vignetti (CSIL); Chiara Del Bo (Universitá degli Studi di Milano).
Academic Panel Review: Massimo Florio (Universitá degli Studi di Milano), Panel Coordinator; Per-Olov
Johansson (Stockholm School of Economics), Susana Mourato (London School of Economics & Political Science),
Arnold Picot (Ludwig-Maximilians-Universität, Munich), Mateu Turró (Universitat Politècnica de Catalunya).
Technical advisory: JASPERS acted as technical advisor to DG REGIO for the preparation of this Guide, with a
focus on the practical issues related to the CBA of major infrastructure projects. In particular, besides peer
reviewing the early drafts of the Guide, JASPERS contributed by highlighting best practice and common mistakes
in carrying out CBA as well as with the design and development of the seven case studies included in the Guide.
The JASPERS team was composed of experts in all sectors covered by the Guide. It was led by Christian Schempp
and Francesco Angelini and included Patrizia Fagiani, Joanna Knast-Braczkowska, Marko Kristl, Massimo Marra,
Tudor Radu, Paul Riley, Robert Swerdlow, Dorothee Teichmann, Ken Valentine and Elisabet Vila Jorda.
The authors gratefully acknowledges very helpful comments by Witold Willak, Head of Sector, G.1 Major Project
Team, the European Commission Directorate-General for Regional and Urban Policy, who has been in charge of
the management of the service, by Mateusz Kujawa, European Commission Directorate-General for Regional and
Urban Policy, by the members of the Academic Panel Review, by experts from JASPERS and the European
Investment Bank (EIB), as well as participants in the Steering Committee meetings including desk officers from
the European Commission Directorates-General for Communications Networks, Content and Technology, for
Climate Action, for the Environment, for Energy, for Mobility and Transport, for Regional and Urban Policy and
for Research and Innovation.
In some cases, constraints of space, of time, or scope of the Guide have limited the possibility by the authors to
fully include all the suggested changes to earlier drafts. The usual disclaimer applies and the authors are
responsible for any remaining omissions or errors.
The European Commission and the authors accept no responsibility or liability whatsoever with regard to this
text. This material is:
- information of general nature which is not intended to address the specific circumstances of any particular
individual or entity;
- not necessarily comprehensive, accurate or up to date. It is not meant to offer professional or legal advice.
Reproduction or translation is permitted, provided that the source is duly acknowledged and no modifications to
the text are made.
Quotation is authorised as long as the source is acknowledged along with the fact that the results are provisional.
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List of abbreviations
BAU Business As Usual
CBA Cost-Benefit Analysis
CF Conversion Factor
DCF Discounted Cash Flow
EC European Commission
EIA Environmental Impact Assessment
EIB European Investment Bank
ENPV Economic Net Present Value
ERDF European Regional Development Fund
ERR Economic Rate of Return
ESI European and Structural Investment
EU European Union
FDR Financial Discount Rate
FNPV Financial Net Present Value
FRR(C) Financial Rate of Return of the Investment
FRR(K) Financial Rate of Return on National Capital
GDP Gross Domestic Product
GHG Green House Gas
IWS Integrated Water Supply
LRMC Long Run Marginal Cost
MCA Multi-Criteria Analysis
NACE Statistical classification of economic activities
MS Member State
OP Operational Programme
O&M Operation & Maintenance
PPP Public-Private Partnership
QALY Quality-Adjusted Life Year
SCF Standard Conversion Factor
SDR Social Discount Rate
STPR Social Time Preference Rate
VAT Value Added Tax
VOSL Value of Statistical Life
VOT Value of Time
WTP Willingness-to-pay
WTA Willingness-to-accept
WWTP Waste Water Treatment Plant
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Table of Contents
Introduction ...................................................................................................................................................................................... 5
1. CBA in the framework of the EU funds ........................................................................................................................ 6
1.1 Introduction ................................................................................................................................................................................................ 6
1.2 Definition and scope of ‘Major projects’ ......................................................................................................................................... 6
1.3 Information required, roles and responsibility for the appraisal ....................................................................................... 8
1.4 Consistency with recent policy developments ......................................................................................................................... 11
2. General principles for carrying out cost benefit analysis................................................................................. 15
2.1 Introduction ............................................................................................................................................................................................. 15
2.2 Project appraisal steps ........................................................................................................................................................................ 17
2.3 Description of the context .................................................................................................................................................................. 19
2.4 Definition of objectives........................................................................................................................................................................ 20
2.5 Identification of the project ............................................................................................................................................................... 21
2.6 Technical feasibility and environmental sustainability ........................................................................................................ 24
2.7 Financial analysis ................................................................................................................................................................................... 31
2.8 Economic analysis ................................................................................................................................................................................. 43
2.9 Risk assessment ...................................................................................................................................................................................... 56
2.10 Checklist ..................................................................................................................................................................................................... 64
3. Transport ............................................................................................................................................................................ 66
3.1 Introduction ............................................................................................................................................................................................. 66
3.2 Description of the context .................................................................................................................................................................. 68
3.3 Definition of objectives........................................................................................................................................................................ 68
3.4 Project identification ............................................................................................................................................................................ 69
3.5 Forecasting traffic volume ................................................................................................................................................................. 70
3.6 Option analysis ........................................................................................................................................................................................ 73
3.7 Financial analysis ................................................................................................................................................................................... 73
3.8 Economic analysis ................................................................................................................................................................................. 76
3.9 Risk assessment ...................................................................................................................................................................................... 89
Case study - Road Project ...........................................................................................................................................................90
Case study - Railway .................................................................................................................................................................. 101
Case study – Urban Transport ............................................................................................................................................... 115
4. Environment .................................................................................................................................................................... 134
4.1 Water supply and sanitation .......................................................................................................................................................... 134
4.2 Waste management ........................................................................................................................................................................... 147
4.3 Environment remediation, protection and risk prevention ............................................................................................ 159
Case Study – Waste Water Infrastructure ......................................................................................................................... 167
Case Study – Waste Incinerator with Energy Recovery ............................................................................................... 167
5. Energy ................................................................................................................................................................................ 201
5.1 Introduction .......................................................................................................................................................................................... 201
5.2 Description of the context ............................................................................................................................................................... 203
5.3 Definition of objectives..................................................................................................................................................................... 204
5.4 Project identification ......................................................................................................................................................................... 204
5.5 Forecasting energy demand and supply ................................................................................................................................... 205
5.6 Option analysis ..................................................................................................................................................................................... 207
5.7 Financial analysis ................................................................................................................................................................................ 207
5.8 Economic analysis .............................................................................................................................................................................. 209
5.9 Risk assessment ................................................................................................................................................................................... 219
Case Study – Natural gas transmission pipeline ............................................................................................................. 221
6. Broadband ........................................................................................................................................................................ 230
6.1 Introduction .......................................................................................................................................................................................... 230
6.2 Description of the context ............................................................................................................................................................... 231
6.3 Definition of objectives..................................................................................................................................................................... 232
6.4 Project identification ......................................................................................................................................................................... 232
6.5 Demand analysis ................................................................................................................................................................................. 234
6.6 Option analysis ..................................................................................................................................................................................... 236
6.7 Financial analysis ................................................................................................................................................................................ 236
6.8 Economic analysis .............................................................................................................................................................................. 237
6.9 Risk assessment ................................................................................................................................................................................... 241
Case Study – Broadband infrastructure ............................................................................................................................. 242
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7. Research, development and innovation ................................................................................................................ 255
7.1 Introduction .......................................................................................................................................................................................... 255
7.2 Description of the context ............................................................................................................................................................... 258
7.3 Definition of objectives..................................................................................................................................................................... 259
7.4 Project identification ......................................................................................................................................................................... 260
7.5 Demand analysis ................................................................................................................................................................................. 261
7.6 Option analysis ..................................................................................................................................................................................... 263
7.7 Financial analysis ................................................................................................................................................................................ 264
7.8 Economic analysis .............................................................................................................................................................................. 266
7.9 Risk assessment ................................................................................................................................................................................... 282
Annex I. The financial discount rate ................................................................................................................................... 287
Annex II. The social discount rate ........................................................................................................................................ 289
Annex III. Approaches for empirical estimation of conversion factors ................................................................. 292
Annex IV. The shadow wage ................................................................................................................................................... 299
Annex V. Tariff setting, polluter-pays principle and affordability analysis ......................................................... 303
Annex VI. Willingness-to-pay approach to evaluate direct and external impacts ............................................. 307
Annex VII. Project performance indicators ...................................................................................................................... 319
Annex VIII. Probabilistic risk analysis ............................................................................................................................... 322
Annex IX. Other appraisal tools ............................................................................................................................................ 329
Bibliography ................................................................................................................................................................................ 332
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Introduction
The present guide to Cost-Benefit Analysis (CBA) of investment projects updates and expands the
previous edition of 2008. The guide has been revised with consideration for the recent developments
in EU polices and methodology for cost benefit analysis and international best practice, and builds on
the considerable experience gained in project preparation and appraisal during the previous
programming periods of the cohesion policy.
The objective of the guide reflects a specific requirement for the European Commission to offer
practical guidance on major project appraisals, as embodied in the cohesion policy legislation for
2014-2020. As with previous versions, however, the guide should be seen primarily as a contribution
to a shared European-wide evaluation culture in the field of project appraisal. Its main objective is to
illustrate common principles and rules for application of the CBA approach into the practice of
different sectors.
The guide targets a wide range of users, including desk officers in the European Commission, civil
servants in the Member States (MS) and in candidate countries, staff of financial institutions and
consultants involved in the preparation or evaluation of investment projects. The text is relatively self-
contained and does not require a specific background in financial and economic analysis of capital
investments. The main change with respect to the previous edition concerns a reinforced operational
approach and a stronger focus on the investment priorities of the cohesion policy.
The structure of the guide is as follows.
Chapter one presents the regulatory requirements for the project appraisal process and the related
decision on a major project. The project appraisal activity is discussed within the more comprehensive
framework of the multi-level governance planning exercise of the cohesion policy and its recent policy
developments.
Chapter two discusses the CBA guiding principles, working rules and analytical steps that shall be
considered for investment appraisal under EU funds. The proposed methodological framework is
structured as a suggested agenda and check-list, both from the standpoint of the investment proposer,
who is involved in assessing or preparing a project dossier, and the project examiner involved in
project appraisals.
Chapters three to seven include outlines of project analysis by sector, focusing on transport,
environment, energy, broadband and research & innovation sectors. The aim is to make explicit those
aspects of the CBA that are sector-specific, such as typical economic costs and benefits, evaluation
methods, reference periods, etc.
To facilitate the understanding and practical application of CBA in the different sectors covered by the
Guide, a number of cases studies are provided. The case studies are solely intended as worked
examples of the general methodology described in Chapter 2 and the sector specific methodologies.
Although the project examples used in the case studies may be partially based on real projects, these
have been simplified and modified in many ways to fit the intended purpose, which is why they are not
necessarily representative of the complexity of any real project. Also, the projects selected are only
illustrative examples of a vast variety of possible project types within each infrastructure sector and
should not be seen as a standard project for the given sector. Similarly, none of the specific
assumptions featured in any of the case studies are meant to be seen as representative or standard for
any other project, in any sector or country, but rather as illustrative examples. Finally, it should also be
noted that for reasons of space limitations in this Guide, the case studies have been generally kept as
short as possible and thus many details had to be left out in many ways.
A set of annexes cover the following topics: financial discount rate; social discount rate; approaches for
empirical estimation of conversion factors; shadow wage; tariff setting, polluter pays principle and
affordability; willingness to pay approach; project performance indicators; probabilistic risk analysis;
other appraisal tools. The text is completed by a bibliography.
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1. CBA in the framework of the EU funds
1.1 Introduction
The EU cohesion policy aims to deliver growth and jobs together with the targets and objectives
contained within the Europe 2020 strategy. Choosing the best quality projects which offer best value
for money and which impact significantly on jobs and growth is a key ingredient of the overall
strategy. In this framework, Cost Benefit Analysis (CBA) is explicitly required, among other elements,
as a basis for decision making on the co-financing of major projects included in operational
programmes (OPs) of the European Regional Development Fund (ERDF) and the Cohesion Fund.
CBA is an analytical tool to be used to appraise an investment decision in order to assess the welfare
change attributable to it and, in so doing, the contribution to EU cohesion policy objectives. The
purpose of CBA is to facilitate a more efficient allocation of resources, demonstrating the convenience
for society of a particular intervention rather than possible alternatives.
This chapter describes the legal requirements and scope of the CBA in the appraisal of investment
projects within the EU cohesion policy, according to the EU regulations and other European
Commission documents (see box below). In addition, the role of CBA in the broader framework of EU
policy is discussed in light of the EU 2020 Strategy, the targets and objectives of the flagship initiatives
and the main sectorial policies and cross cutting issues, including climate change and resource
efficiency, in addition to synergies with other EU funding instruments such as the Connecting Europe
Facility. The key contents of the chapter are:
definition and scope of ‘major projects’;
information required, roles and responsibility for the appraisal; and
consistency with recent policy development and cross cutting issues.
1.2 Definition and scope of ‘Major projects’
According to Article 100 (Major projects) of Regulation (EU) No 1303/2013, a major project is an
investment operation comprising ‘a series of works, activities or services intended to accomplish an
indivisible task of a precise economic and technical nature which has clearly identified goals and for
which the total eligible cost exceeds EUR 50 million.ʼ The total eligible cost is the part of the
investment cost that is eligible for EU co-financing.1 In the case of operations falling under Article 9(7)
(Thematic objectives) of Regulation (EU) No 1303/2013, the financial threshold for the identification
of major project is set at EUR 75 million.
THE LEGAL BASIS FOR MAJOR PROJECTS APPRAISAL
- Regulation (EU) No 1303/2013 of the European Parliament and of the Council of 17 December 2013 laying
down common provisions on the European Regional Development Fund, the European Social Fund, the Cohesion
Fund, the European Agricultural Fund for Rural Development and the European Maritime and Fisheries Fund
and laying down general provisions on the European Regional Development Fund, the European Social Fund, the
Cohesion Fund and the European Maritime and Fisheries Fund and repealing Council Regulation (EC) No
1083/2006.
- Commission Delegated Regulation (EU) No 480/2014 of 3 March 2014 supplementing Regulation (EU) No
1303/2013.
- Commission Implementing Regulation (EU) No 1011/2014 of 22 September 2014 laying down detailed rules
for implementing Regulation (EU) No 1303/2013 of the European Parliament and of the Council as regards the
models for submission of certain information to the Commission and the detailed rules concerning the exchanges
of information between beneficiaries and managing authorities, certifying authorities, audit authorities and
1 See Preamble 92 to Regulation (EU) No 1303/2013.
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intermediate bodies (hereinafter called IR on notification procedure and IQR)
- Commission Implementing Regulation (EU) laying down detailed rules implementing Regulation (EU) No
1303/2013 of the European Parliament and of the Council as regards the models for the progress report,
submission of the information on a major project, the joint action plan, the implementation reports for the
Investment for growth and jobs goal, the management declaration, the audit strategy, the audit opinion and the
annual control report and the methodology for carrying out the cost-benefit analysis and pursuant to Regulation
(EU) No 1299/2013 of the European Parliament and of the Council as regards the model for the implementation
reports for the European territorial cooperation goal (hereinafter called IR on application form and CBA
methodology)
The definition of a major project does not apply to the operation of setting up a financial instrument, as
defined by Article 37 (Financial instrument) of Regulation (EU) No 1303/20132, which should undergo
a specific procedure3. In the same vein, a Joint Action Plan, as defined by Article 104 (Joint action plan)
of Regulation (EU) No 1303/20134 is not a major project. Major projects may be financially supported
by the ERDF and Cohesion Fund (hereafter the Funds) as part of an OP or more than one OP (see box
below). While the ERDF focuses on investments linked to the context in which firms operate
(infrastructure, business services, support for business, innovation, information and communication
technologies [ICT] and research applications) and the provision of services to citizens (energy, online
services, education, health, social and research infrastructures, accessibility, quality of the
environment)5, the Cohesion Fund supports interventions within the area of transport and
environment. In the environment field, the Cohesion Fund specifically supports investment in climate
change adaptation and risk prevention, investment in the water and waste sectors and the urban
environment. Investments in energy efficiency and renewable energy are also eligible for support,
provided it has positive environmental benefits. In the field of transport the Cohesion Fund
contributes to investments in the Trans-European Transport Network, as well as low-carbon transport
systems and sustainable urban transport6.
THE INCLUSION OF MAJOR PROJECTS IN AN OPERATIONAL PROGRAMME
According to Article 96 (Content, adoption and amendment of operational programmes under the Investment for
growth and jobs goal) of Regulation (EU) No 1303/2013, an operational programme shall set out (…) ʻa
description of the type and examples of actions to be supported under each investment priority and their
expected contribution to the specific objectives referred to in point (i), including the guiding principles for the
selection of operations and, where appropriate, the identification of main target groups, specific territories
targeted, types of beneficiaries, the planned use of financial instruments and major projects.ʼ
As part of the operational programme(s), the implementation of major projects should be examined by the
Monitoring Committee appointed for the specific programme(s) (Article 110). Progress on their preparation and
implementation shall be reported in the Annual Implementation Report (Article 111), which Member States are
asked to submit annually, from 2016 to 2023.
Financial instruments can be set up to finance major projects, even in combination with ERDF or
Cohesion Fund grants. In the latter case separate records must be maintained for each form of
financing. In addition, the applicant is asked to specify the type of financial instruments used for
financing the project.
2ʻThe ESI Funds may be used to support financial instruments under a programme, including when organised through funds of funds, in
order to contribute to the achievement of specific objectives set out under a priority’ (Reg.1083/2013, Art. 32(1)).
3‘Based on an ex ante assessment which has identified market failures or suboptimal investment situations, and investment needs.’ Source:
(Reg. 1083/2013, Art. 32(2)).
4‘It comprises a project or a group of projects, not consisting of the provision of infrastructure, carried out under the responsibility of the
beneficiary, as part of an OP or OPs. ((Reg. 1083/2013, Art. 104(1)).
5Regulation (EU) No 1301/2013 of the European Parliament and of the Council of 17 December 2013 on the ERDF and on specific provisions
concerning the investment for growth and jobs goals and repealing Regulation (EC) No 1080/2006.
6Regulation (EU) No 1300/2013 of the European Parliament and of the Council of 17 December 2013 on the Cohesion Fund and repealing
Council Regulation (EC) No 1084/2006.
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1.3 Information required, roles and responsibility for the appraisal
In order to get the approval for the co-financing of the major project, the managing authority (MA) of
the programme(s) which submits the project is asked to make available the information referred to in
Article 101 (Information necessary for the approval of a major project) of Regulation
(EU) No 1303/2013 (see box).
INFORMATION REQUIRED
(a) Details concerning the body responsible for implementation of the major project, and its capacity.
(b) A description of the investment and its location.
(c) The total cost and total eligible cost, taking account of the requirements set out in Article 61.
(d) Feasibility studies carried out, including options analysis, and the results.
(e) A CBA, including an economic and a financial analysis, and a risk assessment.
(f) An analysis of the environmental impact, taking into account climate change mitigation and adaptation needs,
and disaster resilience.
(g) An explanation as to how the major project is consistent with the relevant priority axes of the OP or OPs
concerned, and its expected contribution to achieving the specific objectives of those priority axes and the
expected contribution to socio-economic development.
(h) The financing plan showing the total planned financial resources and the planned support from the Funds,
the EIB, and all other sources of financing, together with physical and financial indicators for monitoring
progress, taking account of the identified risks.
(i) The timetable for implementing the major project and, where the implementation period is expected to be
longer than the programming period, the phases for which support from the Funds is requested during the
programming period.
The information in Article 101(a to i) represents the basis for appraising the major project and
determining whether support from the Funds is justified.
The principles, methods and criteria presented in this guide (especially in chapter 2) will help
beneficiaries, public decision-makers and independent reviewers to better understand what
information is required in order to appraise the socio-economic benefits and costs of an investment
project. Although the CBA is just one of the information elements requested, it is strongly interlinked
with all other elements and forms part of a more comprehensive exercise of project design and
preparation.
According to Article 102 (Decision on a major project) of Regulation (EU) No 1303/2013, the
appraisal procedure can take two different forms. It is up to the Member State to decide which of the
two forms to apply for specific major projects under its OPs:
the first option is an assessment of the major project by independent experts followed by a
notification to the Commission by the MA of the major project selected. According to this
procedure, the independent experts will assess the information provided on the major project
according to Article 101;
the second option is to send the major project documentation directly to the Commission, in
line with the procedure of the 2007-2013 programming period. In this case, the MS shall
submit to the Commission the information set out in Article 101, which will be assessed by the
Commission.
Regardless of the procedure adopted, the aim is to check that:
the project dossier is complete, i.e. all the necessary information required by Article 101 is
made available and is of sufficient quality;
the CBA analysis is of good quality, i.e. it is coherent with the Commission methodology; and
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the results of the CBA analysis justify the contribution of the Funds.
Figure 1.1 Role and responsibilities in the Major Project’s appraisal
Member State Selection of the appraisal procedure
Art. 102 (1) Art. 102 (2)
procedure procedure
Managing Makes available Makes available
authority information referred to in information referred to in
Art.101 to the Art. 101 and submits an
independent experts Application Form to the
Commission services
Assess the project on the
Independent basis of the information
experts referred to in Art. 101
and produce an
Independent Quality
Review report
Managing Submits a notification of
authority the selected project to
the Commission services
Assesses the project on Assesses the project on
European the basis of the the basis of the
Commission Independent Quality information referred to in
Review report Art. 101 with the support
of the EIB
(if necessary)
The project is approved/rejected
Source: Authors
The results of the analysis should, in particular, demonstrate that the project is the following:
consistent with the OP. This is demonstrated by checking that the result(s) produced by the
project (e.g. in terms of employment generation, carbon dioxide reduction, etc.) contribute to
the specific objective(s) of the priority axis of the programme and policy goals;
in need of co-financing. This is assessed by the financial analysis and, particularly, with the
calculation of the Financial Net Present Value and the Financial Rate of Return of the
Investment (FNPV(C) and FRR(C) respectively). To gain a contribution from the Funds, the
FNPV(C) should be negative and the FRR(C) should be lower than the discount rate used for
the analysis (except for some projects falling under State Aid rules for which this may not be
relevant7);
desirable from a socio-economic perspective. This is demonstrated by the economic
7 As well as in case of projects which risks are too high to carry out the investment without a public grant, e.g. highly innovative projects. See
Annex III to the Implementing Regulation on application form and CBA methodology.
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analysis result and particularly by a positive Economic Net Present Value (ENPV)8.
In order to assess if the results of the CBA actually support a case for the major project approval, the
CBA dossier should demonstrate that the methodology is sound and consistent. To this end, it is of
paramount importance that all the information related to the CBA is made easily available and is
discussed convincingly by the project beneficiary in the form of a quality CBA report, that refers to
methods and tools used (including the model(s) used for calculations) as well as all the working
hypotheses underpinning the analysis and especially the forecasts of future values, in addition to their
sources. A quality CBA report should therefore be: self-contained (results of previous studies should
be briefly recalled and illustrated); transparent (a complete set of data and sources of evidence should
be made easily available); verifiable (assumptions and methods used to calculate forecast values
should be made available so that the analysis can be replicated by the reviewer); and credible (based
on well-documented and internationally accepted theoretical approaches and practices).
Figure 1.2 The role of CBA in the appraisal of the major project
CBA RESULTS
Consistency and
completeness
check
The methodology is The methodology is not Need to check assumptions
sound consistent in some points and consistency of the
CBA Results are reliable CBA Results are unreliable analysis
Assessment of
performance
indicators
The project is
not in need
FNPV(C) > 0 FNPV(C) <0
of co-
financing*
The project is in-
need of co-financing
EU
contribution
is not ENPV <0 ENPV > 0
justified
EU
EU grant
contribution is
calculation
justified
*With exceptions, as set out in Annex III to the Implementing Regulation on application form and CBA methodology.
Source: Authors
Where the major project has received a positive appraisal in a quality review by independent experts,
8 A positive economic return shows the society is better off with the project, i.e. the expected benefits on society justify the opportunity cost
of the investment.
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according to Article 102(1) (Decision on a major project) of Regulation (EU) No 1303/2013, the
Member State may proceed with the selection of the major project and shall notify the Commission.
The Commission has 3 months to agree with the independent experts, or adopt the Commission
decision refusing the financial contribution to the major project.
If the Commission appraises the major project in accordance with Article 102(2), the Commission shall
adopt its decision on the approval (or rejection) of the financial contribution to the selected major
project, by means of an implementing act, no later than three months from the date of submission of
the information referred to in Article 101.
The co-financing rate for the priority axis, under which the major project is included, shall be fixed by
the Commission when adopting the OP [Article 120 (Determination of co-financing rates) of
Regulation (EU) No 1303/2013]. For each priority axis, the Commission shall set out whether the co-
financing rate for the priority axis is to be applied to the total eligible expenditure (including public
and private expenditure) or to the public eligible expenditure. As stated in Article 65 (Eligibility) of
Regulation (EU) No 1303/2013, the eligible expenditure of an operation, including major projects, is
determined on the basis of national rules ‘except where specific rules are laid down in, or on the basis
of, this Regulation or the Fund-specific rules’. Also, specific provisions apply in the case of revenue-
generating projects (see box).
The financing method and appraisal procedure of major projects has therefore changed with respect
to the 2007-2013 programming period. Table 1.3, displayed at the end of the chapter, highlights the
main differences introduced by the new regulations as compared to the Council Regulation
1083/2006.
REVENUE-GENERATING PROJECTS
Revenue-generating projects are investment operations in which discounted revenues are higher than
discounted operating costs. According to Article 61 (Operations generating net revenue after completion) of
Regulation (EU) No 1303/2013, the eligible expenditure to be co-financed from the Funds shall be reduced,
taking into account the potential of the operation to generate net revenue over a specific reference period that
covers both implementation of the operation and the period after completion. The potential net revenue of the
operation shall be determined in advance by one of the following methods:
1) Application of a flat rate for the net revenue percentage. It is a simplified approach as compared to the
previous programming period.
2) Calculation of discounted net revenue of the operation. This is the method used in the 2007-2013
programming period, in accordance with Article 55 of the Council Regulation 1083/2006.
3) Application of reduced co-financing rates for particular priority axes.
Where it is not objectively possible to determine the revenue in advance according to these methods, Article 61
states that ‘the net revenue generated within three years of the completion of an operation […] shall be deducted
from the expenditure declared to the Commission.’
It should be noted that Article 61 does not apply to operations for which support under the programme
constitutes: (a) de minimis aid; (b) compatible State aid to small and medium-sized businesses (SMEs), where an
aid intensity or an aid amount limit is applied in relation to State aid; or (c) compatible State aid, where an
individual verification of financing needs in accordance with the applicable State aid rules has been carried out.
1.4 Consistency with recent policy developments
For the 2014-2020 programming period, cohesion policy and its Funds are deemed to be a key
delivery mechanism to achieve the objectives of Europe 2020 strategy9. As stated in Article 18
(Thematic concentration) of Regulation (EU) No 1303/2013, Member States shall concentrate the EU
support (in accordance with the Fund’s-specific rules) on actions that bring the greatest added value in
9European Commission (2010), Communication from the Commission -Europe 202: A European strategy for smart, sustainable and inclusive
growth, COM(2010) 2020, Brussels, 3.3.2010.
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relation to the Europe 2020 priorities of smart growth, sustainable growth and inclusive growth.
The EU has set five ambitious targets – in the fields of employment, innovation, education, social
inclusion and climate/energy – which are to be achieved at EU level by 2020. To meet these targets,
the Commission proposed a Europe 2020 agenda consisting of seven flagship initiatives representing
the investment areas supporting the Europe 2020 priorities. These include: innovation; digital
economy; employment; youth; industrial policy; and poverty and resource efficiency.
Actions under the smart growth priority will require investments aimed at strengthening
research performance, promoting innovation and knowledge transfer throughout the Union,
making full use of ICTs, ensuring that innovative ideas can be turned into products and services
that create growth, improving education quality. Investments in specific sectors, such as R&D, ICT
and education are considered to be of major strategic importance in the promotion of this
objective;
To achieve sustainable growth, it is necessary to invest in operations aimed at limiting emissions
and improving resource efficiency. All sectors of the economy, not just emission-intensive ones,
are concerned. Environmental measures in water and waste management, investments related to
transport and energy infrastructures, as well as instruments based on the use of ICT, are expected
to contribute to the shift towards a resource efficient and low-carbon economy. A further step
towards sustainable growth will be achieved by supporting manufacturing and service industries
(such as tourism) in seizing the opportunities presented by globalisation and the green economy;
Inclusive growth priority requires actions aimed at modernising and strengthening the
employment and social protection systems. In particular, this priority specifically addresses the
challenge of demographic change by increasing labour participation and reducing structural
unemployment (especially for women, young people and older workers). In addition, it will
address the challenges of a low skilled workforce and marginalisation (e.g. children and elderly
who are particularly exposed to the risk of poverty). In this regard, investments in social
infrastructure, including childcare, healthcare, culture and education facilities, will help improve
skills. This will enable citizens to balance work with their private lives, and will reduce social
exclusion and health inequalities, thus ensuring that the benefits gained from growth can be
enjoyed by everyone;
Table 1.1. shows how specific investment sectors are related to the Europe 2020 priorities, flagship
initiatives and targets. Within this context, major projects play a key role and their appraisal should be
seen as part of a larger planning exercise aimed at identifying the contribution of the project to the
achievement of the Europe 2020 strategy. In addition, the projects must comply with EU legislation
(e.g. public procurement, competition and State-aid) and sectorial policies.
Finally, all sectors and investments are required to comply with EU climate policy. Climate change
issues, both mitigation and adaptation aspects, must be taken into account during the preparation,
design and implementation of major projects. That is, major projects shall contribute to the
progressive achievement of emissions reduction targets by 2050. Accordingly, in the context of the co-
financing request, MAs are required to explain how mitigation and adaptation needs have been taken
into account when preparing and designing the project. Second, major projects should be climate-
resilient: the possible impacts of the changing climate have to be assessed and addressed at all stages
of their development. In the context of the co-funding request, MAs are required to explain which
measures have been adopted in order to ensure resilience to current climate variability and future
climate change.
Overall, the CBA provides key support in assessing the contribution of the projects to the achievement
of Europe 2020 targets. Table 1.2 below shows how certain effects may be identified and quantified
through the CBA.
Table 1.1 Matching Investment sectors and Europe 2020 priorities/flagships/targets
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Europe 2020 targets
Employment
Innovation
Europe
Education
Poverty
Climate
change
2020 Europe 2020 flagship initiatives Sector/investments
priorities
- Research, Technological
Innovation Union
Development and Innovation √ √ √
Smart
Growth Youth on the move - Education √ √
Digital Agenda for Europe - ICT √ √
- Environment
Sustainable
Resource efficient Europe - Energy √ √ √
- Transport
Growth
An industrial policy for the - Entrepreneurship
globalisation era - Industry √ √ √
- Culture
Inclusive
An agenda for new skills and jobs
- Childcare √ √
Growth European Platform against - Health
poverty - Housing √
Source: Authors
Table 1.2 The role of the CBA in contributing towards the achievement of the EU objectives
Europe 2020 Effects quantifiable through the CBA Guide Section
Targets
The effect, in terms of employment used by the project, is captured by Par.2.8.5
applying the Shadow Wage Conversion Factor to labour cost. The effect,
Employment Annex IV
in terms of employment spilling over from the project, is captured by the
additional profit created, e.g. by new spin-off companies. Par 7.8.3
The contribution to the innovation objective is assessed by:
Innovation - the economic returns generated by license deals; and Par 7.8.3
- the technological progress generated by the project.
The responses to climate change are assessed by estimating costs and
benefits of integrating:
- climate change mitigation measures, by measuring the economic value
Par 2.6.3
Climate change of greenhouse gas (GHG) emissions emitted in the atmosphere and the
opportunity cost of the energy supply savings; Par. 2.8.8
- climate change adaptation measures, resulting from the assessment of
the project’s risk-exposure and vulnerability to climate change impacts.
The contribution to a higher level of education is assessed by estimating
the expected increased income of students and researchers due to better
Education Par. 7.8.4
positioning on the job market, as well as the economic value of
knowledge outputs (e.g. scientific articles).
Effects on poverty reduction may be assessed by evaluating the equity
dimension of the project through the consideration of the households
Poverty Annex V
affordability (ability-to-pay), in particular the less wealthy, to access a
given public service and the computation of a set of welfare weights.
Source: Authors
/13
Table 1.3 Main changes compared to the 2007-2013 programming period
2007 – 2013 2014 – 2020
(Regulation 1083/2006) (Regulation 1303/2013)
Major project Operations where the eligible cost exceeds EUR 50 million and, in the case of operations
Operations where the total cost exceeds EUR 50 million (Art. 39).
threshold contributing to the thematic objective under Article 9(7), EUR 75 million (Art. 100).
The major project is financed as part of an OP or OPs. In addition it can be supported by
Inclusion of The major project is financed as part of an OP or OPs (Art. 39). The more than 1 priority axis within the OP. Major projects notified to the Commission under
major projects in list of major projects contained in the OP is indicative. paragraph 1, or submitted for approval under paragraph 2, shall be contained in the list of
the OP major projects in an OP (Art. 102).
- Article 102 (1) procedure: at the level of the MS, if the MS decides, the major project is
assessed by independent experts supported by technical assistance or, in agreement
with the Commission, by other independent experts. The MS notifies the Commission
about the results by presenting the information required in Article 101. The
- Submission: MS submits a major project application to the EC.
Commission approves or refuses the MS’s selection of the major project within three
The COM appraises the major project application on the basis of
months. In the absence of a decision, the project is deemed approved after three
the information referred in Art. 40 and, if necessary, consulting
months from its notification (Art. 101).
outside experts including the EIB.
- Article 102 (2) procedure:
o The MS sends major project application to the Commission. The Commission
Project appraisal - Decision: The Commission adopts a decision within three months.
appraises and adopts a decision approving or refusing the MS selection of
and decision If the Commission appraises the major project and it does not
the major project within three months (Art.102).
process comply with the Regulations, the MS is requested to withdraw the
o For an operation which consists of the second or subsequent phase of a
application. Alternatively, the Commission may adopt a negative
major project for which the preceding phase was approved by the
decision.
Commission and there are no substantial changes compared to the
(Art. 41)
information provided for the major project application submitted in the
previous period, in particular as regards the total eligible cost, the MS may
proceed with the selection of the major project in accordance with Art. 125(3)
and submit the notification containing all the elements, together with
confirmation that there are no substantial changes in the major project. No
assessment of the information by independent experts is required (Art.103)
Expenditure relating to major projects can be included in payment Expenditure relating to major projects may be included in payment applications only after
Payment applications before the project has been approved by a the MA notifies to the Commission of the major project decision or following the submission
applications Commission decision. for major project application approval.
Validity of Approval by the Commission shall be conditional on the first works/PPP contract being
A Commission decision on a major project is valid for the entire
Commission concluded within three years of the date of the approval of the project by the Commission.
programming period.
approval The deadline could be extended in duly motivated cases by not more than two years.
Three possibilities:
Calculation of One possibility: - Calculation of discounted net revenues
net revenue - Calculation of discounted net revenues (Art. 55). - Flat rate net revenue percentage
- Decreasing co-financing rate for a chosen priority axis (Art. 61).
Source: Authors
/14
2. General principles for carrying out cost
benefit analysis
2.1 Introduction
Cost-Benefit Analysis (CBA) is an analytical tool for judging the economic advantages or disadvantages
of an investment decision by assessing its costs and benefits in order to assess the welfare change
attributable to it.
The analytical framework of CBA refers to a list of underlying concepts which is as follows:
Opportunity cost. The opportunity cost of a good or service is defined as the potential gain
from the best alternative forgone, when a choice needs to be made between several mutually
exclusive alternatives. The rationale of CBA lies in the observation that investment decisions
taken on the basis of profit motivations and price mechanisms lead, in some circumstances
(e.g. market failures such as asymmetry of information, externalities, public goods, etc.), to
socially undesirable outcomes. On the contrary, if input, output (including intangible ones) and
external effects of an investment project are valued at their social opportunity costs, the return
calculated is a proper measure of the project’s contribution to social welfare.
Long-term perspective. A long-term outlook is adopted, ranging from a minimum of 10 to a
maximum of 30 years or more, depending on the sector of intervention. Hence the need to:
o set a proper time horizon;
o forecast future costs and benefits (looking forward);
o adopt appropriate discount rates to calculate the present value of future costs and benefits;
o take into account uncertainty by assessing the project’s risks.
Although, traditionally, the main application is for project appraisal in the ex-ante phase, CBA
can also be used for in medias res and ex post evaluation10.
Calculation of economic performance indicators expressed in monetary terms. CBA is
based on a set of predetermined project objectives, giving a monetary value to all the positive
(benefits) and negative (costs) welfare effects of the intervention. These values are discounted
and then totalled in order to calculate a net total benefit. The project overall performance is
measured by indicators, namely the Economic Net Present Value (ENPV), expressed in
monetary values, and the Economic Rate of Return (ERR), allowing comparability and ranking
for competing projects or alternatives.
Microeconomic approach. CBA is typically a microeconomic approach enabling the
assessment of the project’s impact on society as a whole via the calculation of economic
performance indicators, thereby providing an assessment of expected welfare changes. While
direct employment or external environmental effects realised by the project are reflected in
the ENPV, indirect (i.e. on secondary markets) and wider effects (i.e. on public funds,
employment, regional growth, etc.) should be excluded. This is for two main reasons:
o most indirect and/or wider effects are usually transformed, redistributed and capitalised
forms of direct effects; thus, the need to limit the potential for benefits double-counting;
10 In this case: i) for all the years for which information is available actual values, instead of forecasted, for costs and benefits are used; ii)
instead of discounting, past values are capitalised with a proper backward discount rate. For some practical CBA examples refer to EC (2012),
Ex post evaluation of investment projects, co-financed by the European Fund for Regional Development (ERDF) and Cohesion Fund during
the period 1994-1999.
\15
o there remains little practice on how to translate them into robust techniques for project
appraisal, thus the need to avoid the analysis relies on assumptions whose reliability is
difficult to check.
It is recommended, however, to provide a qualitative description of these impacts to better
explain the contribution of the project to the EU regional policy goals.11
Incremental approach. CBA compares a scenario with-the-project with a counterfactual
baseline scenario without-the-project. The incremental approach requires that:
o a counterfactual scenario is defined as what would happen in the absence of the project.
For this scenario, projections are made of all cash flows related to the operations in the
project area for each year during the project lifetime. In cases where a project consists of a
completely new asset, e.g. there is no pre-existing service or infrastructure, the without-
the-project scenario is one with no operations. In cases of investments aimed at improving
an already existing facility, it should include the costs and the revenues/benefits to operate
and maintain the service at a level that it is still operable (Business As Usual12 (BAU)) or
even small adaptation investments that were programmed to take place anyway (do-
minimum13). In particular, it is recommended to carry out an analysis of the promoter’s
historical cash-flows (at least previous three years) as a basis for projections, where
relevant. The choice between BAU or do-minimum as counterfactual should be made case
by case, on the basis of the evidence about the most feasible, and likely, situation. If
uncertainty exists, the BAU scenario shall be adopted as a rule of thumb. If do-minimum is
used as counterfactual, this scenario should be both feasible and credible, and not cause
undue and unrealistic additional benefits or costs. As illustrated in the box below the
choice made may have important implications on the results of the analysis;
o secondly, projections of cash-flows are made for the situation with the proposed project.
This takes into account all the investment, financial and economic costs and benefits
resulting from the project. In cases of pre-existing infrastructure, it is recommended to
carry out an analysis of historical costs and revenues of the beneficiary (at least three
previous years) as a basis for the financial projections of the with-project scenario and as a
reference for the without-project scenario, otherwise the incremental analysis is very
vulnerable to manipulation;
o finally, the CBA only considers the difference between the cash flows in the with-the-
project and the counterfactual scenarios. The financial and economic performance
indicators are calculated on the incremental cash flows only14.
The rest of the chapter presents the conceptual framework of a standard CBA15, i.e. the ʻstepsʼ for
project appraisal, enriched with focuses, didactical examples or shortcuts, presented in boxes, to
support the comprehension and practical application of the steps proposed. At the end of each section,
a review of good practices and common mistakes drawn from empirical literature, ex post evaluations
and experience gained from major projects funded during the 2007-13 programming period, is also
11 In some cases, where there is a methodologically sound study forecasting indirect and wider impacts in quantity terms and when these are
deemed to be substantial or a major factor in the decision to implement the project, their inclusion in the quantitative analysis could be done
as a sensitivity test.
12 For example, a scenario that ensures: (i) basic functionality of the assets, (ii) service provision under similar quality levels, (iii) limited
asset replacements and (iv) minimum cost recovery to ensure financial sustainability of operations.
13 For example, when limited amount of capital investments are necessary to avoid interruption of service or any other catastrophic scenario.
14 The analysis of financial sustainability, however, may also need to look at the situation of the operator in the with-project scenario, in
particular where the project is embedded in a pre-existing infrastructure/service. See section 2.8.
15 For a description of other project appraisal tools, such as Cost-Effectiveness Analysis (CEA) and Multi-Criteria Analysis (MCA) Annexes, see
Annex IX.
\16
illustrated. A checklist that can be used as useful tool for checking the quality of a CBA closes the
chapter.
THE CHOICE OF THE COUNTERFACTUAL SCENARIO
The following example, adapted from EIB (2013) 16, illustrates the issue of the project performance in relation to
what scenario is selected as counterfactual.
The proposed project, which consists of rehabilitating and expanding existing infrastructure capacity, involves
investing EUR 450 million and will result in benefits growing by 5 % per year. The ʻdo-minimumʼ scenario, which
consists of only rehabilitating existing capacity, involves investing EUR 30 million, followed by constant benefits.
The BAU involves no investment at all, which, in turn, will affect the amount of output the facility can produce,
causing a fall in net benefits of 5 % per year.
As shown below, the results of the CBA change significantly if different scenarios are adopted as counterfactual.
By comparing the proposed project with the ʻdo-minimumʼ scenario, the ERR equals 3 %. If the BAU is taken as a
reference, the ERR increases to 6 %. Thus, any choice should be duly justified by the project promoter on the
basis of clear evidence about the most feasible situation that would occur in the absence of the project.
Scenarios EUR m NPV 1 2 10 21
1 Proposed project Net benefit 1058 45 47 70 119
Investment 435 450
2 Do-minimum Net benefit 661 45 45 45 45
Investment 29 30
3 Business As Usual Net benefit 442 45 43 28 16
Investment 0
Results
1-2 Proposed project net of Do-minimum Net flows -9 -420 2 25 74
ERR 3%
1-3 Proposed project net of Business As Usual Net flows 182 -450 4 42 103
ERR 6%
Source: EIB (2013)
2.2 Project appraisal steps
Standard CBA is structured in seven steps:
1. Description of the context
2. Definition of objectives
3. Identification of the project
4. Technical feasibility & Environmental sustainability
5. Financial analysis
6. Economic analysis
7. Risk assessment.
The following sections illustrate, in detail, the scope of each step.
16 European Investment Bank, (2013) The Economic Appraisal of Investment Projects at the EIB.
\17
Figure 2.1 The steps of the appraisal
1. Presentation of the socio-economic,
institutional and political context
2. Definition of objectives
Needs assessment
Projects relevance
3. Project identification
Project activities
Body responsible for project implementation
Who has standing?
4. Technical feasibility & Environmental sustainability
Demand analysis
Option analysis
Environmental considerations, including EIA and climate change
Technical design, cost estimates and implementation schedule
5. Financial analysis
Cash-flows for project costs and revenues, including residual value
Tariff and affordability analysis (where relevant)
Sources of financing
Financial profitability & Sustainability
FNPV>0 FNPV<0
The project does not require The project does require
financial support financial support
(with exceptions, as set out in
Annex III to the Implementing
Regulation on application
form and CBA methodology 6. Economic analysis
Fiscal corrections
From market to shadow prices
Evaluation of non-market impacts
Economic profitability
ENPV<0 ENPV>0
The society is better off The society is better off
without the project with the project
7. Risk assessment
Sensitivity analysis
Qualitative risk analysis
Probabilistic risk analysis
Source: Authors
\18
2.3 Description of the context
The first step of the project appraisal aims to describe the social, economic, political and
institutional context in which the project will be implemented. The key features to be described
relate to:
the socio-economic conditions of the country/region that are relevant for the project, including
e.g. demographic dynamics, expected GDP growth, labour market conditions, unemployment
trend, etc.;
the policy and institutional aspects, including existing economic policies and development
plans, organisation and management of services to be provided/developed by the project, as
well as capacity and quality of the institutions involved;
the current infrastructure endowment and service provision, including indicators/data on
coverage and quality of services provided, current operating costs and tariffs/fees/charges
paid by users, if any17;
other information and statistics that are relevant to better qualify the context, for instance,
existence of environmental issues, environmental authorities likely to be involved, etc.;
the perception and expectations of the population with relation to the service to be provided,
including, when relevant, the positions adopted by civil society organisations.
The presentation of the context is instrumental to forecast future trends, especially for demand
analysis. In fact, the possibility of achieving credible forecasts about users, benefits and costs often
relies on the assessment’s accuracy of the macro-economic and social conditions of the region. In this
regard, an obvious recommendation is to check that the assumptions made, for instance on GDP or
demographic growth, are consistent with data provided in the corresponding OP or other sectorial
and/or regional plans of the Member State.
Also, this exercise aims to verify that the project is appropriate to the context in which it takes
place. Any project is integrated in pre-existing systems with its own rules and features, and this is an
imminent complexity that cannot be disregarded. Investments to provide services to citizens can
achieve their goals through the integration of either new or renewed facilities into already existing
infrastructures. Partnership with the various stakeholders intervening in the system is thus a
necessity. Also, sound economic policy, quality institutions and strong political commitment can help
the implementation and management of the projects, and the achievement of larger benefits. In short,
investments are easier to carry out where the context is more favourable. For this reason, the specific
context characteristics need to be taken into due consideration starting from the project design and
appraisal phase. In some cases, improvements in the institutional set up might be needed to ensure an
adequate project performance.
GOOD PRACTICES
- The context is presented including all sectors that are relevant to the project and avoiding unnecessary
discussions on sectors that are unrelated to the project.
- The existing infrastructure endowment and service provision is presented with relevant statistics.
- The sectorial and regional characteristics of the service to be provided are presented in light of the existing
development plans.
17 As an example, a project dealing with a waste incinerator with energy recovery would necessarily need to describe the current situation of:
(i) the waste management system in the region (i.e. based on indicators such as total waste produced from households and commercial,
industrial and construction activities; number and capacity of operating landfills and/or other waste treatment plants), (ii) the local district
heating system (i.e. including heat generation facilities and distribution system), to which the project would supply the heat it produces, (iii)
the road system (including type, length and condition of roads), which it would rely on to transport the waste to the plant, but would not
need to provide information on the regional railway system, unless the project considers transporting the waste to the plant by rail.
\19
COMMON MISTAKES
- Socio-economic context and statistics are presented without explaining their relevance for the project.
- Socio-economic statistics and forecasts are not based on readily available official data and forecasts.
- The political and institutional aspects are considered irrelevant and not adequately analysed and discussed.
2.4 Definition of objectives
The second step of the project appraisal aims to define the objectives of the project.
From the analysis of all the contextual elements listed in the previous section, the regional and/or
sectorial needs that can be addressed by the project must be assessed, in compliance with the sectorial
strategy prepared by the MS and accepted by the European Commission. The project objectives should
then be defined in explicit relation to needs18. In other words, the needs assessment builds upon the
description of the context and provides the basis for the objective’s definition.
As far as possible, objectives should be quantified through indicators and targeted 19, in line with the
result orientation principle of the Cohesion Policy. They may relate, for example, to improvement of
the output quality, to better accessibility to the service, to the increase of existing capacity, etc. For a
detailed illustration of the typical objectives per sector see chapters three to seven.
A clear definition of the project objectives is necessary to:
identify the effects of the project to be further evaluated in the CBA. The identification of
effects should be linked to the project’s objectives in order to measure the impact on welfare.
The clearer the definition of the objectives, the easier the identification of the project and its
effects. Objectives are highly relevant for the CBA, which should reveal to what extent they are
met;
verify the project’s relevance. Evidence should be provided that the project’s rationale
responds to a priority for the territory. This is achieved by checking that the project
contributes to reaching the EU policy goals and national/regional long-term development
plans in the specific sector of assistance. Reference to these strategic plans should demonstrate
that the problems are recognised and that there is a plan in place to resolve them.
Whenever possible, the relationship or, better, the relative contribution of the project objectives to
achieve the specific targets of the OPs should be clearly quantified. Such identification will also enable
the linking of the project objectives with the monitoring and evaluation system. This is particularly
important for reporting the progress of major projects in the annual implementation reports, as
requested by Article 111 (Implementation reports for the Investment for growth and jobs goal) of
Regulation (EU) No 1303/2013. In addition, according to the most recent policy development of the
European and Structural Investment (ESI) Funds, the promoter should also show how and to what
extent the project will contribute to achieving the targets of any national or regional sectorial
programme.
18 When specifying the needs, the promoter should focus on specific and not generic issues such as economic development. Also, these should
be quantified and explained: e.g. volume and growth rate of traffic congestion due to urbanisation dynamics, indices of water quality
deterioration as a consequence of industrialisation, risk of energy supply shortage due to increased demand, etc.
19 A target is a quantified aspect of the objectives, for example: reduction of travel time from A to B of X minutes; increasing the catchment
area of a service of N thousands of people, improvement of capacity from X to Y MW, reduction of GHG emissions from X to Y tonnes of CO2
per year, etc.
\20
GOOD PRACTICES
- Project effects are identified in clear relation to the project objectives.
- The general objectives of the project are quantified with a system of indicators and targets.
- Target values are established and compared to the situations with- and without-the-project.
- Project indicators are linked to those defined in the respective OP and priority axis. Where the indicators set at
the level of the OP are inappropriate to measure the impact of specific projects, additional project-specific
indicators, are set up.
- If a region or country-wide target exists (e.g. 100 % coverage of water supply in a given service area, diversion
of minimum 50 % of biodegradable waste from landfill, etc.), the contribution of the project to achieving this
wider target (in % of total target) is explained.
- Source and values of indicators are explained.
COMMON MISTAKES
- The economic effects considered in the CBA are not well aligned with the specific objectives of the project.
- Project objectives are confused with its outputs. For instance, if the main objective of the project is to improve
the accessibility of a peripheral area, the construction of a new road or the modernisation of the existing network
are not objectives, but the means through which the objective of improving the area’s accessibility will be
accomplished.
- Where the investment is compliance driven (e.g. UWWTD20), the extent to which the project contributes to
achieve such compliance is not shown. If the required standards are not attained by the project, evidence of what
other measures are planned and how they will be financed must be provided.
2.5 Identification of the project
Section 1.2 has presented the legal basis for the definition of a project. Here, some analytical issues
involved in project identification are developed. In particular, a project is clearly identified when:
the physical elements and the activities that will be implemented to provide a given good or
service, and to achieve a well-defined set of objectives, consist of a self-sufficient unit of
analysis;
the body responsible for implementation (often referred to as ʻproject promoterʼ or
ʻbeneficiaryʼ) is identified and its technical, financial and institutional capacities analysed; and
the impact area, the final beneficiaries and all relevant stakeholders are duly identified (ʻwho
has standing?ʼ).
2.5.1 Physical elements and activities
A project is defined as ʻas a series of works, activities or services intended in itself to accomplish an
indivisible task of a precise economic or technical nature which has clearly identified goalsʼ (Article
100 (Content) of Regulation (EU) No 1303/2013). These works, activities or services should be
instrumental in the achievement of the previously defined objectives. A description of the type of
infrastructure (railway line, power plant, broadband, waste water treatment plant, etc.), type of
intervention (new construction, rehabilitation, upgrade, etc.), service provided (cargo traffic, urban
solid waste management, access to broadband for businesses, cultural activities, etc.) and location
should be provided in order to define the project activities.
In this regard, the key aspect is that appraisal needs to focus on the whole project as a self-sufficient
20 Urban Waste Water Treatment Directive.
\21
unit of analysis, which is to say that no essential feature or component is left outside the scope of the
appraisal (under-scaling). For example, if there are no connecting roads for waste delivery, a new
landfill will not be operational. In that case, both the landfill and the connecting roads are to be
considered as a unique project. In general, a project can be defined as technically self-sufficient if it is
possible to produce a functionally complete infrastructure and put a service into operation without
dependence on other new investments. At the same time, including components in the project that are
not essential to provide the service under consideration should be avoided (over-scaling).
The application of this principle requires that:
partitions of project for financing, administrative or engineering reasons are not
appropriate objects of appraisal (ʻhalf a bridge is not a bridgeʼ). A typical case might be that
of a request for EU financial support for the first phase of an investment, whose success hinges
on the completion of the project as a whole. Or, a request for EU financial support for only a
part of a project because the remaining will be financed by other sponsors. In these cases, the
whole investment should be considered in CBA. The appraisal should focus on all the parts that
are logically connected to the attainment of the objectives, regardless of what the aim of the EU
assistance is.
inter-related but relatively self-standing components, whose costs and benefits are
largely independent, should be appraised independently. Sometimes a project consists of
several inter-related elements. For example, the construction of a green park area including
solid waste management and recreational facilities. Appraising such a project involves, firstly,
the consideration of each component independently and, secondly, the assessment of possible
combinations of components. The measurement of the economic benefits of individual project
components is particularly relevant in the context of large multifaceted projects (see box
below). As a whole these projects may present a net positive economic benefit (i.e. a positive
ENPV). However, this positive ENPV may include one or more project components that have a
negative ENPV. If this component(s) is not integral to the overall project, then excluding it will
increase the ENPV for the rest of the project.
future planned investments should be considered in the CBA if they are critical for ensuring the
operations of the original investment. For example, in the case of wastewater treatment, a
capacity upgrade of the original plant shall be factored in at a certain point of the project’s life
cycle, if it is needed to comply with an expected population increase, in order to continue to
meet the original project’s objectives.
PROJECT IDENTIFICATION: EXAMPLES
The main driver of the improvement of a railway line is its electrification in order to improve its performance
and its integration into the electrified network. Given that the construction works will generate some service
disruptions, the project incorporates other actions on the line such as alignment improvements, track
reconstruction and the adoption of the ERMTS signalling system. The CBA should consider all these investments
and their effects.
EU assistance can be designed to co-finance the reorganisation of some water subnets as part of a broader
intervention financed with several sponsors and concerning the entire municipality’s water supply network. The
larger intervention should be considered as the unit of the analysis.
A system of integrated environmental regeneration which envisages the construction of several waste water
treatment plants and the installation of sewage pipelines and pumping stations in different municipalities can be
considered as one integrated project if the single components are integral to the achievement of the
environmental regeneration of the impact area.
In the context of urban development, the rehabilitation of city walls and streets in the historical centre of a
town should be appraised independently from the rehabilitation and adaptation of buildings for commercial
activities in the same area.
\22
2.5.2 The body responsible for project implementation
The project owner, i.e. the body responsible for project implementation, should be identified and
described in terms of its technical, financial and institutional capacity. The technical capacity refers
to the relevant staff resources and staff expertise available within the organisation of the project
promoter and allocated to the project to manage its implementation and subsequent operation. In the
case of the need to recruit additional staff, evidence should be provided that no constraints exist to
find the necessary skills on the local labour market. The financial capacity refers to the financial
standing of the body, which should demonstrate that it is able to guarantee adequate funding both
during implementation and operations. This is particularly important when the project is expected to
require substantial cash inflow for working capital or other financial imbalances (e.g. medium-long
term loan, clearing cycle of VAT, etc.). The institutional capacity refers to all the institutional
arrangements needed to implement and operate the project [e.g. set up of a Project Implementation
Unit (PIU)] including the legal and contractual issues for project licensing. Where necessary, special
external technical assistance may need to be foreseen and included in the project.
When the infrastructure owner and its operator are different, a description of the operating company
or agency who will manage the infrastructure (if already known) and its legal status, the criteria used
for its selection, and the contractual arrangements foreseen between the partners, including the
funding mechanisms (e.g. collection of tariffs/service fees, presence of government subsides), should
be provided.
2.5.3 Who has standing
After having described the project activities and the body responsible for project implementation, the
boundaries of the analysis should be defined. The territorial area affected by the project effects is
defined as the impact area. This can be of local, regional or national (or even EU) interest, depending
on the size and scope of the investment, and the capacity of the effects to unfold. Although
generalisations should be avoided, projects typically belonging to some sectors have a common scope
of effects. For example, transport investments such as a new motorway (the same does not usually
apply to urban transport), even if implemented within a regional framework, should be analysed from
a broader perspective since they usually form part of an integrated network that may extend beyond
the geographical scope of the analysis. The same can be said for an energy plant serving a delimited
territory but belonging to a wider system. In contrast, water supply and waste management projects
are more frequently of local interest. However, all projects must incorporate a wider perspective when
dealing with environmental issues related to CO2 and other greenhouse gas (GHG) emissions with
effects on climate change, which are intrinsically non-local.
A good description of the impact area requires the identification of the project’s final beneficiaries,
i.e. the population that benefits directly from the project. These may include, for example, motorway
users, households exposed to a natural risk, companies using a science park, etc. It is recommended to
explain what type of benefits will be enjoyed and to quantify them as much as possible. The
identification of the final beneficiaries should be consistent with the assumptions of the demand
analysis (see section 2.7.1).
In addition, all bodies, public and private, that are affected by the project need to be described. Large
infrastructure investment does not usually only affect the producer and the direct consumers of the
service, but can generate larger effects (or ʻreactionsʼ) e.g. on partners, suppliers, competitors, public
administrations, local communities, etc. For instance, in the case of a high speed train linking two
major cities, local communities along the train layout may be affected by negative environmental
impacts, while the benefits of the project are accrued by the inhabitants of the larger areas. The
identification of ʻwho has standingʼ should account for all the stakeholders who are significantly
affected by the costs and benefits of the project. For a more detailed discussion about how to integrate
distributional effects in the CBA see section 2.9.11.
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GOOD PRACTICES
- Where a project has several stages or phases, these are properly presented together with their respective costs
and benefits.
- Individual investment measures are bundled into one single project when these are: i) integral to the
achievement of the intended objectives and complementary from a functional point of view; ii) implemented in
the same impact area; iii) share the same project owner; and iv) have similar implementation periods.
COMMON MISTAKES
- An artificial splitting of the project is adopted to reduce the project investment cost in order to fit under the
major projects threshold.
- Project over-scaling: investments which are functionally independent of each other are packaged together
without a preliminary verification of the economic viability of each investment and of possible combinations and
without a clear functional and strategic link among them.
- Project under-scaling: a request for assistance is presented for financing a portion of a project which cannot be
justified in isolation from other functional elements.
- Project over-sizing due to over-optimistic assessment of the impact area, e.g. on the basis of unrealistic
assumptions of demographic growth.
- The institutional set-up for project operations is presented unclearly . This will make it difficult to verify that
financial cash flows are properly accounted for in the financial analysis.
- Benefits of a second phase of a project are included in the economic analysis of the first phase without also
including the additional costs, thus making the first phase look economically and/or financially more attractive.
2.6 Technical feasibility and environmental sustainability
Technical feasibility and environmental sustainability are among the elements of information to be
provided in the funding request for major projects (Article 101 (Information necessary for the
approval of a major project) of Regulation (EU) No 1303/2013). Although both analyses are not
formally part of the CBA, their results must be concisely reported and used as a main data source
within the CBA (see box). Detailed information should be provided on:
demand analysis;
options analysis;
environment and climate change considerations;
technical design, cost estimates and implementation schedule.
In the following, a review of the key information that needs to be summarised in the CBA, in order to
understand the overall justification of the project solution sought, is provided. Although they are
presented consecutively, they should be viewed as parts of an integrated process of project
preparation, where each piece of information and analysis feed each other into a mutual-learning
exercise (see box).
\24
TIMING OF CBA: AN ONGOING PROCESS
The CBA principles should be adopted in the project design process as soon as possible. The CBA should be
understood as an ongoing, multi-disciplinary, exercise performed throughout the project preparation in parallel
with other technical and environmental considerations. Prerequisites for the CBA of the proposed project
solution are, however, the finalisation of a detailed demand analysis and the availability of investment and
operational and management (O&M) cost estimates, including costs for environmental mitigation and adaptation
measures. These are based on the preliminary project design, which are centrepieces of the ʻtechnicalʼ feasibility
study and the EIA.
This does not necessarily mean that the analysts responsible for preparing the CBA should start working after
the engineers complete the preliminary technical design and deliver the cost estimates, but rather in parallel. In
fact, analysts preparing the CBA should adopt an interdisciplinary approach to project preparation from an early
stage and are usually involved in preliminary, simplified CBAs for comparisons of different technical and
environmental options. Their involvement in the preparation of the demand analysis and options analysis is
useful (and often decisive) in achieving the best results for the project.
Once the optimal project solution is identified, a full-scale CBA is usually performed at the end of the preliminary
design stage. The aim is to provide confirmation to the project planner(s) of the adequacy and economic
convenience of the proposed solution to meet the pre-established project objectives. The results of the full-scale
CBA, based on the most recent cost estimates, shall be presented in the EU request for co-financing.
2.6.1 Demand analysis
Demand analysis identifies the need for an investment by assessing:
current demand (based on statistics provided by service suppliers/ regulators/ ministries/
national and regional statistical offices for the various types of users);
future demand (based on reliable demand forecasting models that take into consideration
macro- and socio-economic forecasts, alternative sources of supply, elasticity of demand to
relevant prices and income, etc.) in both the scenarios with- and without-the-project.
Both quantifications are essential to formulate demand projections, including generated/induced
demand where relevant21, and to design a project with the appropriate productive capacity. For
example, it is necessary to investigate which share of the demand for public services, rail transport, or
disposal of waste material can be expected to be satisfied by the project. Demand hypotheses should
be tested by analysing the conditions of both the present and future supply, which may be affected by
actions that are independent from the project.
For a detailed discussion about the main factors affecting demand, methods and outputs of demand
analysis in the different fields of intervention see chapters three to seven.
PROJECTS BELONGING TO LARGER, TRANSBOUNDARY NETWORKS
Particular attention should be paid to identifying whether the project under consideration belongs to networks.
This is particularly the case for transport and energy infrastructures, which always form part of networks, but
also for ICT and telecommunication projects.
When projects belong to networks, their demand (and consequently their financial and economic performance)
is highly influenced by issues of mutual dependency (projects might compete with each other or be
complementary) and accessibility (ease of reaching the facility).
Several techniques (e.g. multiple regression models, trend extrapolations, interviewing experts, etc.)
can be used for demand forecasting, depending on the data available, the resources that can be
21 Future demand comes from: existing users, users diverted from other service providers, users generated/induced by the new activities
that are allowed by the project. The capacity of a project to generate induced demand for example depends, among other things, on the size of
the project compared to existing supply, the elasticity of demand and the related capacity to reduce the prevailing market price.
\25
dedicated to the estimates and the sector involved. The selection of the most appropriate technique
will depend, amongst other factors, on the nature of the good or service, the characteristics of the
market and the reliability of the available data. In some case, e.g. transport, sophisticated forecast
models are required.
Transparency in the main assumptions, as well in the main parameters, values, trends and coefficients
used in the forecasting exercise, are matters of considerable importance for assessing the accuracy of
the estimates. Assumptions concerning the policy and regulatory framework evolutions, including
norms and standards, should also be clearly expressed. Furthermore, any uncertainty in the prediction
of future demand must be clearly stated and appropriately treated in risk analysis (see section 2.10).
The method used for forecasting, the data source and the working hypotheses must be clearly
explained and documented in order to facilitate the understanding of the consistency and realism of
the forecasts. Even the information about the mathematical models used, the tools that support them
and their qualification, are fundamental elements of transparency.
GOOD PRACTICES
- Use is made of appropriate modelling tools to forecast future demand.
-Where macro-economic/socio-economic data/forecasts are available from official national sources, consistent
use of them is made across all projects/sectors within the country.
- Demand is appraised separately for all distinct groups of users/consumers relevant to the project.
- Effects of current or planned policy measures and economic instruments that could influence the project are
taken into account for demand analysis. Also, all parallel investments potentially affecting the demand for
services delivered by the project are identified, described and assessed.
COMMON MISTAKES
- The methodology and parameters used for estimation of current and future demand are not explicitly
presented nor justified, or they deviate from national standards and/or official forecasts for the region/country.
- Users’ growth rates ʻautomaticallyʼ assumed throughout the entire reference period of the project are
overoptimistic. Where uncertainty exists, it is wise to assume a stabilisation of demand after the first e.g. 3-to-X
years of operation.
- Insufficient or incomplete market analysis often leads to an overestimation of revenues. In particular, a full
assessment of the competition in the market (projects providing similar products and/or surrogates) and quality
requirements for project outputs are often neglected.
- The link between demand analysis and design capacity of the project (supply) is missing or unclear. The design
capacity of the project should always refer to the year in which demand is highest.
2.6.2 Option analysis
Undertaking a project entails the simultaneous decision of not undertaking any of the other feasible
options. Therefore, in order to assess the technical, economic and environmental convenience of a
project, an adequate range of options should be considered for comparison.
Thus, it is recommended to undertake, as a first step, a strategic options analysis, typically carried
out at pre-feasibility stage and which may require multiple criteria analysis (see box). The approach
for option selection should be as follows:
establish a list of alternative strategies to achieve the intended objectives;
screen the identified list against some qualitative criteria, e.g. multi-criteria analysis based on a
\26
set of scores22, and identify the most suitable strategy.
STRATEGIC OPTIONS: EXAMPLES
- Different routes or construction timing in transport projects (roads/rails).
- Centralised vs. decentralised systems for water supply or wastewater treatment projects.
- A new gravity sewer main and a new wastewater treatment plant vs. a pumping station and pressure pipes that
pump the wastewater towards an existing treatment plant, but with a capacity which has to be increased;
- Different locations for a centralised landfill in a regional waste management project.
- Retrofitting an old power plant or building a new one.
- Different peak-load arrangements for energy supply.
- Construction of underground gas storage facilities vs. new LNG terminal.
- Large hospital structures rather than a more widespread offer of health services through local clinics.
- Possible re-use of existing infrastructure (e.g. ducts, poles, sewerage networks) or possible co-deployment with
other sectors (energy, transport) to reduce the cost of broadband deployment projects 23.
- Different procurement (classic public procurement vs. PPP) and user charging methods for large
infrastructures.
Once the strategic option is identified, a comparison of the specific technological solutions is
typically carried out at feasibility stage. In some circumstances, it is useful to consider, as a first
technological option, a ʻdo-minimumʼ solution. As mentioned, this assumes incurring certain
investment outlays, for example for partial modernisation of an existing infrastructure, beyond the
current operational and maintenance costs. Hence, this option includes a certain amount of costs for
necessary improvements, in order to avoid deterioration of infrastructure or sanctions24. Synergies in
infrastructure deployment (e.g. transport/energy and high-speed broadband infrastructure) should
also be considered, in view of better use of public funds, higher socio-economic impact, and lower
environmental impact.
Once all potential technological solutions are identified, also in the context of the Environmental
Impact Assessment (EIA)/the Strategic Environmental assessment (SEA) procedures and their results
(see next paragraph), they need to be assessed and the optimal solution selected as the subject of the
financial and economic appraisal. The following criteria shall be applied:
if different alternatives have the same, unique, objective (e.g. in the case of compliance-driven
projects with predetermined policy objectives or targets) and similar externalities, the
selection can be based on the least cost solution25 per unit of output produced;
if outputs and/or externalities, especially environmental impacts, are different in different
options (assuming all share the same objective), it is recommended to undertake a simplified
CBA for all main options in order to select the best alternative. A simplified CBA usually
implies focusing on first qualified estimates of demand and rough estimates of the key financial
and economic parameters, including investment and operating costs, the main direct benefit(s)
and externalities26. The calculation of the financial and economic performance indicators in the
22 The criteria used to assign scores and the weights given to them should be made clear to avoid any risk of manipulation of the screening
exercise. For an overview of the elements featuring the MCA see Annex IX.
23 In line with Directive 2014/61/EU on measures to reduce the cost of deploying high-speed electronic communications networks.
24 For instance , when projects are motivated by the need to comply with EU regulations.
25 According to the Life-cycle cost (LCC) approach, this shall include the (discounted) sum of all relevant costs over the lifetime of the project:
investment, operation and maintenance costs, replacement costs and, when applicable, decommissioning costs.
26 Rough cost estimates are generally understood as being based on unit prices obtained from limited (regional) market surveys (i.e.
quotations from different suppliers) or from similar projects in the same regional context. It should be made sure, however, that cost
estimates are all-inclusive, i.e. that no important cost component is missing (e.g. asset replacement costs). Overhead costs for planning and
supervision as well as contingencies may be excluded, but then this should be the same for all options. If included, overheads should be
calculated similarly, i.e. as a percentage of net investment cost, which should be the same for all options. Another simplification is the use of
\27
simplified CBA must be made, as usual, with the incremental technique.
The criteria considered in selecting the best solution, with ranking of their importance and the method
used in the evaluation, shall always be presented by the project promoter as a justification for the
option chosen.
GOOD PRACTICES
- The options analysis is based on a common baseline (i.e. a common counterfactual scenario and consistent
demand analysis are adopted across the options).
- The options analysis starts from a more strategic point of view (i.e. general type of infrastructure and/or
location/alignment for the project) and continues with an assessment of specific technological variants for the
type of infrastructure/site selected. New alternative technologies are accompanied by a thorough assessment of
their technological, financial, managerial risks, climate risk and environmental impacts.
- For comparisons based on costs, all assumptions on unit costs of investment, O&M and replacement should be
disclosed and explained separately for each option to facilitate their appraisal. Unit costs of common
consumables (e.g. labour, energy, etc.) are the same for all options.
- Options are compared using the same reference period.
COMMON MISTAKES
- The various project options are discussed and analysed in detail, but they are not assessed against a
counterfactual scenario which forms the basis of the incremental approach.
- The identification of possible alternatives is done rather ʻartificiallyʼ, e.g. alternatives are not genuine solutions
but simply constructed to show they are worse than the preferred (pre-decided) alternative.
- There is lack of ʻstrategic thinkingʼ: project options are considered only in terms of alternative routes (for
transport projects) or alternative technologies of a pre-selected solution, but not in terms of possible alternative
means to achieve the intended objectives.
- Too many or irrelevant criteria, or inappropriate scoring, are used in multi-criteria analysis for shortlisting the
project options.
2.6.3 Environment and climate change considerations
Some requirements on the project’s environmental sustainability should be fulfilled in parallel with
the technical considerations and contribute to the selection of the best project option.
In particular, the project promoter shall demonstrate to which extent the project: a) contributes to
achieve the resource efficiency and climate change targets for 2020; b) complies with the Directive on
the prevention and remedying of environmental damage (2004/35/EC); c) respects the ‘polluter pays’
principle, the principle of preventive action and the principle that environmental damage should be
rectified at source; d) complies with protection of the Natura 2000 sites and protection of species
covered by the Habitats Directive (92/43/EEC) and the Birds Directive (2009/147/EC); e) is
implemented as a result of a plan or programme falling within the scope of the Strategic
Environmental Assessment (SEA) (2001/42/EC); f) is compliant with the Council Directive
2014/52/EU on the Environment Impact Assessment (EIA)27, as well as any other legislation requiring
financial costs (based on market prices) instead of the economic costs (based on shadow prices). Conversion is not necessary in simplified
economic analysis, unless it is likely to change the order of the options in terms of their ENPV (i.e. where two options differ notably with
regards to investment and O&M components, especially labour intensiveness in construction and operations, and/or their ENPVs before
conversion are very close).
27 In line with this Directive MS shall bring into force the laws, regulations and administrative provisions necessary to comply with this
Directive by 16 May 2017 (as stated in Article 2(1) of the Directive) and that “projects in respect of which the determination referred to in
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an environmental assessment to be carried out. In addition, environmental investments, e.g. water
supply, wastewater and solid waste management, have to comply with other sector-specific Directives,
as further illustrated in chapter 4.
When appropriate, an EIA must be carried out to identify, describe and assess the direct and indirect
effects of the project on human beings and the environment. While the EIA is a formally distinct and
self-standing procedure, its outcomes need to be integrated in the CBA and be in the balance
when choosing the final project option. The costs of any environmental integration measures
resulting from the EIA procedure (including measures for protection of biodiversity) are treated as
input in the assessment of the financial and economic viability of the project. On the other hand, the
benefits resulting from such measures are estimated, as far as possible, when valuing the non-market
impacts generated by the project (see section 2.9.8).
Impacts of the project on climate, in terms of reduction of GHG emissions, are referred to as climate
change mitigation and must be included in the EIA. The following emission sources must be taken
into account when assessing the impact of the project on climate:
direct GHG emissions caused by the construction, operation, and possible decommissioning of
the proposed project, including from land use, land-use change and forestry;
indirect GHG emissions due to increased demand for energy;
indirect GHG emissions caused by any additional supporting activity or infrastructure which is
directly linked to the implementation of the proposed project (e.g. transport, waste
management).
On the other hand, the impacts of climate change on the project, referred to as climate change
adaptation or resilience to climate change, must also to be addressed during the project design
process, when necessary.28 Climate change adaptation is a process aimed to reduce the vulnerability of
natural and human systems against actual or expected climate change effects. The main threats to
infrastructure assets include damage or destruction caused by extreme weather events, which climate
change may exacerbate; coastal flooding and inundation from sea level rise; changes in patterns of
water availability; and effects of higher temperature on operating costs, including effects in temperate
and/or permafrost29. The following phenomena need to be screened:
heat waves (including impact on human health, damage to crops, forest fires, etc.);
droughts (including decreased water availability and quality and increased water demand);
extreme rainfall, riverine flooding and flash floods;
storms and high winds (including damage to infrastructure, buildings, crops and forests);
landslides;
rising sea levels, storm surges, coastal erosion and saline intrusion;
cold spells;
freeze-thaw damage.
To support resilience to climate change in infrastructure investments, the Commission encourages
project promoters to assess the project’s risk-exposure and vulnerability to climate change impacts.
The ʻGuidelines for project managers: Making vulnerable investment climate resilient'30 include a
Article 4(2) of Directive 2011/92/EU was initiated before 16 May 2017 shall be subject to the obligations referred to in Article 4 of Directive
2011/92/EU prior to its amendment by this Directive” (as stated in Article 3(1) of the new Directive)
28 See European Union, 2013, Guidance on Integrating Climate Change and Biodiversity into Environmental Impact Assessment.
29 Commission Staff Working Document, Adapting infrastructure to climate change. Accompanying the document: Communication from the
Commission to the European Parliament, The Council, The European Economic and Social Committee and The Committee of The Regions.
Brussels, 2013. Page 5.
30 Available at: http://ec.europa.eu/clima/policies/adaptation/what/docs/non_paper_guidelines_project_managers_en.pdf
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methodology to systematically assess the sustainability and viability of infrastructure projects in
changing climate conditions. These guidelines are not intended as a substitute for EIA or CBA, but as a
complement to the existing project appraisal tools and development procedures.
Costs and benefits resulting from the integration of both mitigation and adaptation measures in the
project design are used in the appraisal of the project’s financial and economic performance.
GOOD PRACTICES
- Environment and climate change considerations, including impact assessment on Natura 2000, are
incorporated into the project design and preparation at an early stage, i.e. during project screening and scoping.
Climate change adaptation and/or mitigation measures are integrated into the EIA procedure together with
other environmental impacts.
- Cost of measures taken for correcting negative environmental impacts are included in the investment cost
considered in the CBA.
- Early dialogue between the developer and the authorities/nature experts is carried out to run procedures
smoothly and to enable better and faster decisions, which in turn could reduce costs and avoid delays.
COMMON MISTAKES
- There is no consistency between options analysed in the CBA and options analysed in the EIA. In particular, the
option selected in the CBA must have been fully analysed in the EIA.
- Project cost does not incorporate cost of measures related to climate change mitigation, adaptation and other
environmental impacts.
- The benefits of mitigation measures are not properly taken into account.
2.6.4 Technical design, cost estimates and implementation schedule
A summary of the proposed project solution shall be presented with the following headings.
Location: description of the location of the project including a graphical illustration (map).
Availability of land is a key aspect: evidence should be provided that the land is owned (or can
be accessed) by the beneficiary, who has the full title to use it, or has to be purchased (or
rented) through an acquisition process. In the latter case, the conditions of acquisition should
be described. The administrative process and the availability of the relevant permits to carry
out the works should also be explained.
Technical design: description of the main works components, technology adopted, design
standards and specifications. Key output indicators, defined as the main physical quantities
produced (e.g. kilometres of pipeline, number of overpasses, number of trees planted, etc.),
should be provided.
Production plan: description of the infrastructure capacity and the expected utilisation rate.
These elements describe the service provision from the supply side. Project scope and size
should be justified in the context of the forecasted demand.
Costs estimates: estimation of the financial needs for project realisation and operations are
imported in the CBA as a key input for the financial analysis (see section 2.8). Evidence should
be provided as to whether cost estimations are investor estimates, tender prices or out-turn
costs.
Implementation timing: a realistic project timetable together with the implementation
schedule should be provided including, for example, a Gantt chart (or equivalent) with the
works planned. A reasonable degree of detail is needed in order to enable an assessment of the
proposed schedule.
GOOD PRACTICES
- A concise summary of the results of the feasibility study(ies) is included in the CBA report to explain the
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justification of the selected solution. Input data from the technical studies are duly used in the CBA. Should the FS
include a section on CBA, consistency with the main CBA report is ensured or major differences explained.
- The technical description of investment and operating cost components provides sufficient detail to allow for
cost benchmarking.
2.7 Financial analysis
2.7.1 Introduction
As set out in Article 101 (Information necessary for the approval of a major project) of Regulation (EU)
No 1303/2013, a financial analysis must be included in the CBA to compute the project’s financial
performance indicators. Financial analysis is carried out in order to:
assess the consolidated project profitability;
assess the project profitability for the project owner and some key stakeholders;
verify the project financial sustainability, a key feasibility condition for any typology of project;
outline the cash flows which underpin the calculation of the socio-economic costs and benefits
(see section 2.9).
The cash inflows and outflows to be considered are described in detail below. The methods to reduce
the eligible expenditure of the operation and calculate the Union assistance (taking into account the
potential to generate net revenue) are not discussed in this Guide. Please refer to Art. 61 (operations
generating net revenue after completion) of (EU) Regulation 1303/2013 and Article 15 (Method for
calculating discounted net revenue) of Commission Delegated Regulation (EU) No 480/2014.
2.7.2 Methodology
The financial analysis methodology used in this guide is the Discounted Cash Flow (DCF) method, in
compliance with section III (Method for calculating the discounted net revenue of operations
generating net revenue) of Commission Delegated Regulation (EU) No 480/2014. The following rules
should be adopted:
Only cash inflows and outflows are considered in the analysis, i.e. depreciation, reserves,
price and technical contingencies and other accounting items which do not correspond to
actual flows are disregarded.
Financial analysis should, as a general rule, be carried out from the point of view of the
infrastructure owner. If, in the provision of a general interest service, owner and operator are
not the same entity, a consolidated financial analysis, which excludes the cash flows
between the owner and the operator, should be carried out to assess the actual profitability of
the investment, independent of the internal payments. This is particularly feasible when there
is only one operator, which provides the service on behalf of the owner usually by means of a
concession contract.31
An appropriate Financial Discount Rate (FDR) is adopted in order to calculate the present
value of the future cash flows. The financial discount rate reflects the opportunity cost of
capital. The practical ways of estimating the reference rate to use for discounting are discussed
in Annex I, while the box below reminds the European Commission’s reference parameter
suggested for the programming period 2014-2020.
Project cash-flow forecasts should cover a period appropriate to the project’s economically
useful life and its likely long term impacts. The number of years for which forecasts are
31 On the other hand, when there are many operators, the consolidation of the analysis might not be feasible. In this case, the analysis
perspective should be that of the project promoter, either owner or operator, depending on the investment typology (see for example
section 3.7.3 in the Transport chapter).
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provided should correspond to the project’s time horizon (or reference period). The choice
of time horizon affects the appraisal results. In practice, it is therefore helpful to refer to a
standard benchmark, differentiated by sector and based on internationally accepted practice.
The Commission-proposed reference periods are shown in table 2.1. These values should be
considered as including the implementation period. In the case of unusually long construction
periods, longer values can be adopted.
The financial analysis should usually be carried out in constant (real) prices, i.e. with prices
fixed at a base-year. The use of current (nominal) prices [i.e. prices adjusted by the Consumer
Price Index (CPI)] would involve a forecast of CPI that does not seem always necessary. When a
different rate of change of relative prices is envisaged for specific key items, this differential
should be taken into account in the corresponding cash flow forecasts.
When the analysis is carried out at constant prices, the FDR will be expressed in real terms.
When the analysis is carried out at current prices, a nominal FDR will be used32.
The analysis should be carried out net of VAT, both on purchase (cost) and sales (revenues), if
this is recoverable by the project promoter. On the contrary, when VAT is not recoverable, it
must be included.33
Direct taxes (on capital, income or other) are considered only for the financial sustainability
verification and not for the calculation of the financial profitability, which is calculated before
such tax deductions. The rationale is to avoid capital income tax rules complexity and
variability across time and countries.
FINANCIAL DISCOUNT RATE: THE EC BENCHMARK
According to Article 19 (Discounting of cash flows) of Commission Delegated Regulation (EU) No 480/2014, for
the programming period 2014-2020, the European Commission recommends that a 4 % discount rate in real
terms is considered as the reference parameter for the real opportunity cost of capital in the long term. Values
differing from the 4 % benchmark may, however, be justified on the grounds of international macroeconomic
trends and conjunctures, the Member State’s specific macroeconomic conditions and the nature of the investor
and/or the sector concerned. To ensure consistency amongst the discount rates used for similar projects in the
same country, the Commission encourages the Member States to provide their own benchmark for the financial
discount rate in their guidance documents and then to apply it consistently in project appraisal at national level.
Table 2.1 European Commission’s reference periods by sector
Reference period
Sector
(years)
Railways 30
Roads 25-30
Ports and airports 25
Urban transport 25-30
Water supply/sanitation 30
Waste management 25-30
Energy 15-25
Broadband 15-20
Research and Innovation 15-25
Business infrastructure 10-15
Other sectors 10-15
Source: ANNEX I to Commission Delegated Regulation (EU) No 480/2014.
32 The formula for the calculation of the nominal discount rate is: (1+n)=(1+r)*(1+i), where: n – nominal rate, r – real rate, i – inflation rate.
33 VAT, even where recoverable, is part of the total investment outlay that has to be paid for and needs to be funded. To this extent, it is worth
stressing that treatment of VAT can generate a financing cost. This is the case when there is the need to access the credit market in order to
anticipate the VAT payments on construction costs during implementation. The interest paid is real cost borne by the project promoter.
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The financial analysis is carried out by a set of accounting tables, as illustrated in Figure 2.2. and in
table 2.2, and, in more detail, in the following sections.
Figure 2.2 Structure of financial analysis
Total investment cost Financial return on
investment – FNPV(C)
Operating costs and Financial sustainability
revenues
Sources of financing Financial return on
capital – FNPV(K)
Source: EC CBA Guide 2008
Table 2.2 Financial analysis at a glance
FNPV(C) SUSTAINABILITY FNPV(K)
Investment costs
Start-up and technical costs - -
Land - -
Buildings - -
Equipment - -
Machinery - -
Replacement costs - - -*
Residual value + +
Operating costs
Personnel - - -
Energy - - -
General expenditure - - -
Intermediate services - - -
Raw materials - - -
Other outflows
Loan repayments - -
Interests - -
Taxes -
Inflows
Revenues + + +
Operating subsidies +
Sources of financing
Union assistance +
Public contribution + -**
Private equity + -
Private loan +
* Only if they are self-financed by the project revenues. Otherwise, if new sources of financing (either equity or debt) are
needed to sustain them, these sources must be displayed within the outflows at the time they are disbursed.
** Operating subsidies shall not be accounted in order to avoid double counting with the operating costs outflow.
Source: Adapted from EC CBA Guide 2008.
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2.7.3 Investment cost, replacement costs and residual value
The first step in the financial analysis is the analysis of the amount and breakdown over the years of
the total investment costs. Investment costs are classified by:
Initial investment: it includes the capital costs of all the fixed assets (e.g. land, constructions
buildings, plant and machinery, equipment, etc.) and non-fixed assets (e.g. start up and
technical costs such as design/planning, project management and technical assistance,
construction supervision, publicity, etc.). Where appropriate, changes in net working capital
should also be included. Information must be taken from the technical feasibility study(ies)34
and the data to consider are the incremental cash disbursements encountered in the single
accounting periods (usually years) to acquire the various types of assets (see box). Cost
breakdown over the years should be consistent with the physical realisations envisaged and
the time-plan for implementation (see section 2.7.4)35. Where relevant, the initial investment
shall also include environmental and/or climate change mitigating costs during the
construction, as usually defined in the EIA or in other appraisal procedures.
Replacement costs: includes costs occurring during the reference period to replace short-life
machinery and/or equipment, e.g. engineering plants, filters and instruments, vehicles,
furniture, office and IT equipment, etc.36
It is preferable not to compute cash-flows for large replacements close to the end of the reference
period. When a specific project asset needs to be replaced shortly before the end of the reference
period, the following alternatives should be considered:
shorten the reference period to match the end of the design lifetime of the large asset that
needs replacing;
postpone the replacement until after the end of the reference period and assume an increase of
the annual maintenance and repair cost for the specific asset until the end of the reference
period.
AVOIDED CAPITAL INVESTMENT COST IN THE COUNTERFACTUAL SCENARIO
According to the incremental approach, investment costs should be considered net of possible avoided capital
costs in the counterfactual scenario. The latter costs are based on the assumption that, without the investment,
there is no longer a feasible situation so that it is in any case necessary to implement other interventions, at least
in a way to guarantee a minimum level of service provision. This is the assumption of taking the do-minimum as
the reference scenario (see section 2.2). For example, in the electrical sector, a new substation could be needed
to satisfy the load increase in the absence of a new line. This cost must be included in the counterfactual scenario.
A residual value of the fixed investments must be included within the investment costs account for
the end-year. The residual value reflects the capacity of the remaining service potential of fixed assets
whose economic life is not yet completely exhausted.37 The latter will be zero or negligible if a time
horizon equal to the economic lifetime of the asset has been selected.
According to Article 18 (Residual value of the investment) of Commission Delegated Regulation (EU)
No 480/2014, for project assets with economic lifetimes in excess of reference period, their residual
value shall be determined by ʻcomputing the net present value of cash flows in the remaining life years of
34 If more advanced technical projects have already been drawn up, the investment costs data may be taken from these documents.
35 It should be noted that the costs breakdown suggested in the application for EU co-financing may differ from that of the feasibility
study(ies). Project promoters should therefore additionally present the project costs in the format required by the request for financing,
taking into consideration the eligibility of expenditures incurred.
36 Please note that replacement costs shall be treated together with operating costs for the purpose of calculating the pro-rata application of
discounted net revenue, as set out in Section E.1.2 of Annex II to the Implementing Regulation on application form and CBA methodology.
37 Where relevant, this potential should also account for the value of increased resilience to climate change, for example in the case of
development of a harbour and industrial area in a coastal area that may be at risk from sea-level rise in the longer term.
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the operationʼ.38 Other residual value calculation methods may be used in duly justified circumstances.
For instance, in the case of non-revenue generating projects39, by computing the value of all assets and
liabilities based on a standard accounting depreciation formula40 or considering the residual market
value of the fixed asset as if it were to be sold at the end of the time horizon. Also, the depreciation
formula should be used in the special case of projects with very long design lifetimes, (usually in the
transport sector), whose residual value will be so large as to distort the analysis if calculated with the
net present value method.
The residual value can be singled out either within the project inflows or within the investment costs
but with negative sign (see table 2.3 for an example).
Table 2.3 Total investment costs. EUR thousands
Years
Total 1 2 3 4-9 10 11-29 30
Start-up and technical
costs 6 980 1 816
Land 1 485 757
Buildings 37 342 17 801
Equipment 11 355 23 273
Machinery 25,722
Initial Investment 126,531 8 465 75 176 42 890
Replacement costs 11 890 9 760
Residual value -4 265
Total Investment
152,655 8 465 75 176 42 890 11 890 9 760 -4 265
costs
These can include also costs, e.g. for In the example, expenditures of EUR 11.9 and The residual value is
feasibility studies, borne before the 9.8 million are expected in year 10 and 20, considered with negative sign
start of the evaluation period, respectively, to replace short life equipment because it is an inflow.
although not eligible for EU funding. and machinery.
2.7.4 Operating costs and revenues
The second step in financial analysis is the calculation of the total operating costs and revenues (if
any).
Operating costs41 include all the costs to operate and maintain (O&M) the new or upgraded service.
Cost forecasts can be based on historic unit costs, when patterns of expenditures on operations and
maintenance ensured adequate quality standards.42 Although the actual composition is project-
specific, typical O&M costs include: labour costs for the employer; materials needed for maintenance
and repair of assets; consumption of raw materials, fuel, energy, and other process consumables;
services purchased from third parties, rent of buildings or sheds, rental of machinery; general
management and administration; insurance cost; quality control; waste disposal costs; and emission
charges (including. environmental taxes, if applicable).
These costs are usually distinguished between fixed (for a given capacity, they do not vary with the
volume of good/service provided) and variable (they depend on the volume).
Cost of financing (i.e. interest payments) follow a different course and must not be included within the
O&M costs.
38 In this regard, it is suggested that revenues and costs are assumed constant after the end of the time horizon, unless demand analysis is
carried out over a longer period and provides differently.
39 These are defined as projects that: (i) generate no revenues at all, (ii) generate revenues which are consistently lower than operating costs
during the whole reference period or (iii) generate revenues which may exceed operating costs in the last years of the reference period but
whose discounted net revenues are negative over the reference period.
40 In this case, any asset replacement costs computed during the reference period must be included in the calculation, even if these are
regarded as O&M costs for the purpose of the calculation of the discounted net revenue to determine the Union assistance.
41 See Article 17 (determination of costs) of Commission Delegated Regulation (EU) No 480/2014.
42In case of severe under-spending leading to severely degraded infrastructure, on the contrary, costs forecast should be set at a level which
represents adequate patterns of expenditures.
\35
CHANGE OF RELATIVE PRICES
The change of relative prices is defined as the total nominal increase (decrease) rate net of the inflation
(deflation) factor, as defined by the CPI.
When the prices of some input and output items are expected to change significantly, above or below the average
inflation rate, this differential should be taken into account in the corresponding cash flow forecasts.
Since there is high uncertainty over price evolution in the long term, the application of changes of relative prices
should, however, be the result of proper analysis and supporting evidence should be provided in the CBA. For
example, increase rates applied across all O&M costs and of the same magnitude must be avoided. In particular,
high real increases of unit costs of both energy (e.g. fuel and electricity) and labour are not plausible as these
together determine an large amount of average inflation. Also, with regards to labour costs, any assumed
increase in real salaries and wages can be partially offset by increases in labour productivity throughout the time
horizon.
The project revenues are defined as the ʻcash in-flows directly paid by users for the goods or services
provided by the operation, such as charges borne directly by users for the use of infrastructure, sale or
rent of land or buildings, or payments for servicesʼ (Article 61 (Operations generating net revenue after
completion) of (EU) Regulation 1303/2013).
These revenues will be determined by the quantities forecasts of goods/services provided and by their
prices. Incremental revenues may come from increases in quantities sold, in the level of prices, or both.
Transfers or subsidies (e.g. transfers from state or regional budgets or national health insurance), as
well as other financial income (e.g. interests from bank deposits) shall not be included within the
operating revenues for the calculations of financial profitability because they are not directly
attributable to the project operations43. On the contrary, they shall be computed for the financial
sustainability verification.
When the contribution of the state or other public authority (PA) is, however, in exchange for a good
or service directly provided to it by the project (i.e. the state is the user), this shall be generally
considered a project revenue and included in the financial profitability analysis. In other words, it is
not relevant how the state or PA pays for the goods or services (i.e. through tariffs, shadow tolls,
availability payments, etc.) because the contribution to the project originates from a direct relation to
the use of the project infrastructure.
For compliance with the regulatory requirements, where relevant tariffs shall be fixed in compliance
with the polluter-pays and the full-cost recovery principles. In particular, compliance with the
polluter-pays principle requires that:
applied user charges and fees recover the full cost, including capital costs, of environmental
services;
the environmental costs of pollution, costs of resource depletion, and preventive measures are
borne by those who cause pollution/ depletion;
charging systems are proportional to the social marginal production costs which include the
full costs, including capital costs, of environmental services, the environmental costs of
pollution and the preventive measures implemented and the costs linked to the scarcity of the
resources used.
Compliance with the full-cost recovery principle includes that:
tariffs aim to recover the capital cost, the operating and maintenance cost, including
environmental and resource costs;
43
See Article 16 (Determination of revenues) of Commission Delegated Regulation (EU) No 480/2014.
\36
the tariff structure maximises the project’s revenues before public subsidies, while taking
affordability into account.
However, when relevant, e.g. for a project supplying a public service in the environmental sector,
affordability considerations should be taken into account in the application of the polluter-pays and
the full-cost recovery principles. Key aspects regarding their application and the relative affordability
implications are discussed in Annex V.
As shown in table 2.4, the cash outflows of operating costs deducted from the cash flows of revenues
determine the net revenues of the project. These are calculated for each year until the time horizon.
According to Article 61 Reg. 1303/2013, for the purpose of the EU contribution calculation ʻoperating
cost-savings generated by the operation shall be treated as net revenue unless they are offset by an
equal reduction in operating subsidies’.
Table 2.4 Operating Revenues and Costs. EUR thousands
Years
Total 1-3 4 5 6 … 29 30
Service 1 0 11,355 11,423 11,492 … 11,979 11,979
Service 2 0 243 243 243 … 243 243
Total revenues 407,862 0 11,598 11,666 11,735 … 12,222 12,222
Personnel 0 1,685 1,685 1,685 … 1,685 1,685
Energy 0 620 623 626 … 648 648
General expenditure 0 260 260 260 ... 260 260
Intermediate services 0 299 299 299 … 299 299
Raw materials 0 2,697 2,710 2,724 … 2,821 2,821
Total operating costs 153,487 0 5,561 5,577 5,594 … 5,713 5,713
Net revenues 254,375 0 6,037 6,089 6,140 … 6,509 6,509
Personnel costs are assumed to be fixed along the
During the construction phase no reference period, while energy requirements are
operating revenues and costs usually occur. variable and follow the expected production growth.
2.7.5 Sources of financing
The next step is the identification of the different sources of financing that cover the investment costs.
Within the framework of EU co-financed projects, the main sources can be:
Union assistance (the EU grant);
national public contribution (including, always, the counterpart funding from the OP plus
additional grants or capital subsidies at central, regional or local government level, if any);
project promoter’s contribution (loans or equity), if any;
private contribution under a PPP, (equity and loans) if any.
Here, the loan is an inflow and it is treated as a financial resource coming from third parties. Table 2.5
below provides an illustrative example including contributions from private investors.
Table 2.5 Sources of financing. EUR thousands
Years
Total 1 2 3 4 5 6 7-30
Union assistance 47,054 3,148 27,956 15,950 - - - -
Public contribution 47,054 3,148 27,956 15,950 - - - -
Private equity 16,212 1,085 9,632 5,495 - - - -
Private loan 16,212 1,085 9,632 5,495 - - - -
Total resources 126,531 8,465 75,176 42,890 0 0 0 0
The total sources of financing
should always match the initial The Union assistance is calculated in
line with the provisions of Art. 61 of In the example, the private financing is given
investment cost.
Reg. 1303/2012 and by applying a 50 % by 50 % equity and 50 % loan.
maximum co-financing rate of the
priority axis. \37
2.7.6 Financial profitability
Determination of investment costs, operating costs, revenues and sources of financing enables the
assessment of the project profitability, which is measured by the following key indicators:
financial net present value – FNPV(C) - and financial rate of return – FRR(C) - on investment;
financial net present value – FNPV (K) - and the financial rate of return - FRR (K) - on national
capital.
Return on investment
The financial net present value of investment (FNPV(C)) and the financial rate of return of the
investment (FRR(C)) compare investment costs to net revenues and measure the extent to which the
project net revenues are able to repay the investment, regardless of the sources or methods of
financing.
The Financial net present value on investment is defined as the sum that results when the expected
investment and operating costs of the project (discounted) are deducted from the discounted value of
the expected revenues:
n S0 S1 Sn
FNPV(C) = at St ...
t 0 (1 i) 0
(1 i)1
(1 i) n
where: St is the balance of cash flow at time t, at is the financial discount factor chosen for discounting
at time t and i is the financial discount rate.
The financial rate of return on investment is defined as the discount rate that produces a zero FNPV,
i.e. FRR is given by the solution of the following equation44:
St
0
1 FRR t
The FNPV(C) is expressed in money terms (EUR), and must be related to the scale of the project. The
FRR(C) is a pure number, and is scale-invariant. Mainly, the examiner uses the FRR(C) in order to
judge the future performance of the investment in comparison to other projects, or to a benchmark
required rate of return. This calculation also contributes to deciding if the project requires EU financial
support: when the FRR(C) is lower than the applied discount rate (or the FNPV(C) is negative), then
the revenues generated will not cover the costs and the project needs EU assistance. This is often the
case for public infrastructures, partly because of the tariff structure of these sectors.
The return on investment is calculated considering:
(incremental) investment costs and operating costs as outflows;
(incremental) revenues and residual value as inflows.
Thus, cost of financing is not included in the calculation of the performance of the investment FNPV(C)
(but is included in the table for the analysis of the return on capital FNPV (K), see below).
Moreover, as mentioned above, capital, income or other direct taxes are included only in the financial
sustainability table (see below) and not considered for the calculation of the financial profitability,
which is calculated before deductions.
44 Please note that the solution of the FRR equation is proxied by computation, as in general it cannot be found analytically.
\38
Table 2.6 Calculation of the return on investment. EUR thousands
Years
1 2 3 4 5-9 10 11-29 30
Total revenues 11,598 … 12,011 … 12,222
Residual value 4,265
Total inflows 0 0 0 11,598 … 12,011 … 16,487
Total operating costs 5,561 … 5,662 … 5,713
Initial Investment 8,465 75,176 42,890
Replacement costs 11,890 9,760
Total outflows 8,465 75,176 42,890 5,561 … 17,552 … 5,713
Net cash flow -8,465 -75,176 -42,890 6,037 … -5,540 … 10,774
FNPV(C) - 34.284
FRR(C) 1.4%
A financial discount rate of 4 % has
been applied to calculate this value.
Return on national capital
The objective of the return on national capital calculation is to examine the project performance from
the perspective of the assisted public, and possibly private, entities in the MS (ʻafter the EU grantʼ).
The return on national capital is calculated considering as outflows: the operating costs; the national
(public and private) capital contributions to the project; the financial resources from loans at the time
in which they are reimbursed; the related interest on loans. As far as replacement costs are concerned,
if they are self-financed with the project revenues, they will be treated as operating costs (as in table
2.7). Otherwise, if new sources of financing (either equity or debt) are needed to sustain them, these
sources will be displayed within the outlays at the time they are disbursed. The inflows are the
operating revenues only (if any) and the residual value. Subsidies granted to cover operating costs
shall be excluded because they are transfers from one to another national source45. Table 2.9 shows
this account and readers may see, by comparison with table 2.6 that the former focuses on sources of
national funds, while the latter focuses on total investment costs, with the remaining items being
identical.
The financial net present value of capital, FNPV(K), in this case, is the sum of the net discounted cash
flows that accrue to the national beneficiaries (public and private combined) due to the
implementation of the project. The corresponding financial rate of return on capital, FRR(K), of these
flows determines the return in percentage points.
When computing FNPV(K) and FRR(K), all sources of financing are taken into account, except for the
EU contribution. These sources are taken as outflows (they are inflows in the financial sustainability
account), instead of investment costs (as it forms part of the financial return on investment
calculation).
While the FRR(C) is expected to be very low, or negative for the public investments to be financed with
EU funds, the FRR (K) will be higher and, in some cases, even positive. On the other hand, for public
infrastructure, a negative FNPV(K) after EU assistance does not mean that the project is not desirable
from the operator’s or the public’s perspective and should be cancelled. It just means that it does not
provide an adequate financial return on national capital employed, based on the benchmark applied
(i.e. 4 % in real terms). This is actually a quite common result, even for revenue generating projects
receiving EU assistance. In such cases it is particularly important to ensure the financial sustainability
of the project.
45 However, in case of calculation of return from the point of view of one specific source only (e.g. promoter’s capital, private equity, etc. – see
below) they shall be included and treated accordingly as inflows or outflows.
\39
When relevant, the return on the project promoter’s capital (either public or private) can also be
calculated46. This compares the net revenues of the investment with the resources provided by the
promoter: i.e. the investment cost minus the non-reimbursable grants received from the EU or the
national/regional authorities. This exercise can be particularly useful in the context of state aid in
order to verify that the intensity of the aid (EU and national assistance) provides the best value for-
money with the objective of limiting public financial support to the amount necessary for the project to
be financially viable. In fact, when the project expects a substantial positive return (i.e. significantly
above the national benchmarks on expected profitability in the given sector) it shows that the grants
received would bring supra-normal profits to the beneficiary.
Table 2.7 Calculation of the return on national capital. EUR thousands
Years
1 2 3 4 5-9 10 11-29 30
Total revenues 11 598 … 12 011 … 12 222
Residual value 4 265
Total inflows 0 0 0 11 598 … 12 011 … 16 487
Public contribution 3 148 27 956 15 950
Private equity 1 085 9 632 5 495
Loan repayment
1 789 1 789 1 789
(including interest)
Total operating &
5,561 … 17,552 … 5 713
replacement costs
Total outflows 4 233 37 588 21 445 5 561 … 19 341 … 5 713
Net cash flow -4 233 -37 588 -21 445 6 037 … -7 329 … 10 774
FNPV(K) 11 198
FRR(K) 5.4 %
The loan is here an outflow and is only included when
reimbursed. In this example, it is assumed to be paid In this example, replacement costs are self-financed
back in ten constant payments starting in year 5. with the project revenues. Accordingly, they are treated
as operating costs.
2.7.7 Financial sustainability
The project is financially sustainable when the risk of running out of cash in the future, both during the
investment and the operational stages, is expected to be nil. Project promoters should show how the
sources of financing available (both internal and external) will consistently match disbursements year-
by-year. In the case of non-revenue generating projects (i.e. not subject to the requirements set out in
Article 61 of Regulation (EU) No 1303/2013), or whenever negative-cash-flows are projected in the
future (i.e. in years in which large capital investments are required for asset replacements), a clear
long-term commitment to cover these negative cash flows must be provided47.
The difference between inflows and outflows will show the deficit or surplus that will be accumulated
each year. Sustainability occurs if the cumulated generated cash flow is positive for all the years
considered (table 2.8). The inflows include:
sources of financing;
operating revenues from the provision of goods and services; and
transfer, subsidies and other financial gains not stemming from charges paid by users for the
use of the infrastructure.
The residual value should not be taken into account unless the asset is actually liquidated in the last
46 For example, as set out in Implementing Regulation on application form and CBA methodology, the analysis of the financial profitability of
project promoter's capital is required in case of productive investments.
47A vague statement that the Member State will cover any cash needs of the project over its life in some way is not a promising approach to
planning the financial sustainability of the project. In cases where project revenues need to be complemented by public funds during project
operations to ensure long-term financial sustainability, these appropriations should be established by specific laws, other budgetary
provisions, institutional agreements or contracts.
\40
year of the analysis.
The dynamics of the inflows are measured against the outflows. These relate to the following:
initial investment
replacement costs
operating costs
reimbursement of loans and interest payments
taxes on capital/income and other direct taxes.
It is important to ensure that the project, even if assisted by EU co-financing, does not risk suffering
from a shortage of capital. In particular, in the case of significant reinvestments/upgrades, proof of
disposal of sufficient resources to cover these future costs should be provided in the sustainability
analysis. In this sense it is recommended to carry out a risk analysis that takes into account the
possibility of the key factors in the analysis (usually construction costs and demand) being worse than
expected (see Annex VIII).
Table 2.8 Financial sustainability. EUR thousands
Years
1 2 3 4 5-9 10 11-29 30
Sources of financing 8 465 75 176 42 890
Total revenues 11 598 … 12 011 … 12 222
Total inflows 8 465 75 176 42,890 11 598 … 12 011 … 12 222
Initial investment 8 465 75 176 42,890
Replacement costs 11 890 9 760
Loan repayment
1 789 1 789 1 789
(including interest)
Total operating costs 5,561 … 5 662 … 5 713
Taxes 604 … -733 … 651
Total outflows 8 465 75 176 42 890 5,561 … 19 341 5 713
Net cash flow 0 0 0 6,037 … -7 329 … 6 509
Cumulated net cash
0 0 0 6,037 … 20 726 … 133 835
flow
The cumulated cash flow should be Financial sustainability is verified if the cumulated
zero (or positive) during the net cash flow row is greater than zero for all the
construction phase years considered.
FINANCIAL SUSTAINABILTY FOR INFRASTRUCTURE UPGRADE
If projects fall within an already existing infrastructure, such as capacity extension projects, the overall financial
sustainability of the infrastructure operator, including the project (more than that of the single extended
segment), should be checked after the project (i.e. in the scenario ʻwith the projectʼ), even if the analysis of
incremental cash-flows shows that the project will not run out of cash-flow. This is to ensure that not only the
project but also the operator will not run out of cash-flow, or possibly experience negative cash flows, after
implementation of the project, and is particularly relevant in the case of infrastructure that has previously
suffered from severe underfunding.
2.7.8 Financial analysis in Public Private Partnership (PPP)
EU co-financed investment projects may be partly financed by private investors. PPP may be an
important tool for financing investment projects when there is appropriate scope to involve the
private sector. In order to attract private investors, who generally have different aims, aspirations and
a higher aversion to risk than public bodies, proper incentives should be provided, but up to an
amount which is not granting an unduly high revenue.
Many types of PPP exist, usually dependent on the specificities and characteristics of each project. The
most common PPP models are: Private Operation and Maintenance; Design Build Operate (DBO);
\41
Parallel Co-finance of capex; Design, Build, Finance and Operate (DBFO)48. Attention should be paid to
the structure of the PPP as it may affect the project’s eligible expenditure. In particular, the degree of
risk transfer to the private sector changes under each model project type, ranging from models with
limited risk transfer (e.g. operation and maintenance risk) through to models with higher risk transfer
(e.g. design, construction, financing and operations risk). The following steps shall be considered in
the financial analysis of major projects implemented as a PPP:
Under PPP, the public partner is usually, but not always, the owner of the infrastructure and
the private partner is the operator obtaining revenues through tariff payments. A consolidated
analysis should first be carried out in order to calculate the overall investment profitability.
The return on capital shall then be calculated separately for the private partner and public
partner:
o in order to check profitability of the private capital to avoid unduly high profit generated
by the EU support, the rate of return on private equity – FRR(Kp) – shall be calculated
comparing all the revenues accrued by the private partner, net of the operational costs49
borne, including the concession fee (if any), with the financial resources provided during
investment (either through equity or loans) (see table 2.9). The results shall be compared
with national benchmarks on expected profitability in the given sector. Whenever the
private partner is selected on the basis of the most economically advantageous tender
criterion, through open public procurement, it is expected that such alignment with
national benchmarks is automatically fulfilled;
o a similar exercise can be replicated to calculate the rate of return on public equity -
FRR(Kg) – which compares the revenues accrued by the public partner, usually coming
from the concession fee, net of the managerial costs of the contract, with the resources
provided during investment (either through equity or loans). The result should be
compared with the financial discount rate in order to ensure the project is not over-
financed.
Table 2.9 Calculation of the return on private equity. EUR thousands
Years
1 2 3 4 5-9 10 11-29 30
Total revenues 11 598 … 12 011 … 12 222
Total inflows 0 0 0 11 598 … 12 011 … 12 222
Private equity 1 085 9 632 5 495
Loan repayment
1,789 1 789 1,789
(including interest)
Total operating &
5 561 … 17 552 … 5 713
replacement costs
Concession fee 1 800 … 1 800 … 1 800
Total outflows 1 085 9 632 5 495 7 361 … 21 141 … 7 513
Net cash flow -1 085 -9 632 -5 495 4 237 … -9 129 … 4 709
FNPV(Kp) 26,806
FRR(Kp) 14.2%
A concession fee is usually included within the The residual value is excluded because in many
costs borne by the private operator. PPP contracts the infrastructure is returned to the
public sector at the end of the period.
48 See Jaspers (2010) JASPERS Horizontal Task Outputs – Working Paper Combining EU Grant Funding with PPP for Infrastructure:
Conceptual Models and Case Examples.
49 Replacement costs could be also included if, according to the legal structure of the PPP, they are at the expense of the private partner.
\42
GOOD PRACTICES
- Price and technical contingencies are excluded from the investment cost for the financial profitability
calculation, although they are eligible costs (up to 10 % of the initial investment cost).
- The inflation rate is based on official national projections of the Consumer Price Index (CPI).
- For O&M costs fixed and variable components are calculated separately.
- In the counterfactual case, the chosen regime of regular and periodic maintenance and operations does not lead
to disproportionate losses of operational performance. Any predicted change of operational performance is
shown to realistically correspond to the chosen maintenance and operations regime and to related incremental
benefits calculations (such as time savings and modal shift).
- Fixed maintenance costs are expressed in % of the net cost of the assets for both civil works and plant
components. Variable maintenance costs are expressed in unit cost per output of assets (e.g. EUR/ton, EUR/km,
etc.).
- When a project adds new assets to complement a pre-existing service or infrastructure, both additional
contributions from existing users and contributions from new users of the new service/infrastructure are taken
into account to determine the project revenues.
COMMON MISTAKES
- Replacement costs are not considered in the calculation of residual values.
- The total investment cost in the CBA or its individual elements is inconsistent with the values presented in the
feasibility study or in other more advanced engineering design documents, if available.
- Costs for protection of archaeological remains in the project site, as well as environmental and/or climate
change integration measures are not included in the project cost.
- VAT is included in the financial analysis even though it is recoverable.
- Asset depreciation, interest and loan repayments, VAT and income tax, and dividends paid to shareholders are
included within the O&M costs.
- Subsides received to cover (part of) the operating costs are included in the calculation of the EU contribution as
revenues.
- Charges levied by governments in exchange for the goods or services rendered are confused with transfer
payments and excluded from the operating revenues. For instance, a charge paid by farmers to the irrigation
authority. Although the charge is called ʻtaxʼ, this is not a transfer but a charge directly paid by users in exchange
for the use of water. Accordingly, it must be considered as a project’s revenue. Another example is the ʻtaxesʼ
paid by the citizens for waste collection and disposal services.
- In the FRR(K) calculation, cash-flows relative to replacement costs are computed twice: as operating outlays
and as equity contribution from the project promoter.
- In the case of loans involved in project financing, loan conditions are not explained.
- Nominal interest rates are used to calculate the interest payments, where the analysis is carried out at constant
prices.
2.8 Economic analysis
2.8.1 Introduction
As set out in Article 101 (Information necessary for the approval of a major project) of Regulation (EU)
No 1303/2013, an economic analysis must be carried out to appraise the project’s contribution to
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welfare50. The key concept is the use of shadow prices to reflect the social opportunity cost of goods
and services, instead of prices observed in the market, which may be distorted. Sources of market
distortions are manifold (see also Annex III):
non-efficient markets where the public sector and/or operators exercise their power (e.g.
subsidies for energy generation from renewable sources, prices including a mark-up over the
marginal cost in the case of monopoly, etc.);
administered tariffs for utilities may fail to reflect the opportunity cost of inputs due to
affordability and equity reasons;
some prices include fiscal requirements (e.g. duties on import, excises, VAT and other indirect
taxes, income taxation on wages, etc.);
for some effects no market (and prices) are available (e.g. reduction of air pollution, time
savings).
The standard approach suggested in this guide, consistent with international practice, is to move from
financial to economic analysis. Starting from the account for the return on investment calculation, the
following adjustments should be:
fiscal corrections;
conversion from market to shadow prices;
evaluation of non-market impacts and correction for externalities.
After market prices adjustment and non-market impacts estimation, costs and benefits occurring at
different times must be discounted. The discount rate in the economic analysis of investment projects,
the Social Discount Rate (SDR), reflects the social view on how future benefits and costs should be
valued against present ones. Annex II discusses the empirical approaches used for SDR estimation and
provides examples of estimates at country level.
SOCIAL DISCOUNT RATE: THE EUROPEAN COMMISSION BENCHMARK
According to Annex III to the Implementing Regulation on application form and CBA methodology, for the
programming period 2014-2020 the European Commission recommends that for the social discount rate 5 % is
used for major projects in Cohesion countries and 3 % for the other Member States. Member States may
establish a benchmark for the SDR which is different from 5% or 3 %, on the condition that: i) justification is
provided for this reference on the basis of an economic growth forecast and other parameters; ii) their
consistent application is ensured across similar projects in the same country, region or sector. The Commission
encourages MSs to provide their own benchmarks for the SDR in their guidance documents, possibly at the start
of the operational programmes and then to apply it consistently in project appraisal at national level.
Source: EC (2014)
After the use of the appropriate SDR, it is possible to calculate the project economic performance
measured by the following indicators: Economic Net Present Value (ENPV), Economic Rate of Return
(ERR) and benefit/cost ratio (B/C ratio). In the following sections the steps to move from financial to
economic analysis are described.
2.8.2 Fiscal corrections
Taxes and subsidies are transfer payments that do not represent real economic costs or benefits for
society as they involve merely a transfer of control over certain resources from one group in society to
another. Some general rules can be established to correct such distortions:
prices for input and output must be considered net of VAT;
50 In certain limited cases a cost-effectiveness analysis can be performed, notably for major projects driven by necessity to ensure compliance
with EU legislation, provided that the conditions specified in Annex III to the Implementing Regulation on application form and CBA
methodology are met. For a more detailed discussion about cos-effectiveness analysis and its scope for application see Annex IX.
\44
prices for input should be considered net of direct51 and indirect taxes;
prices (e.g. tariffs) used as a proxy for the value of outputs should be considered net of any
subsidy and other transfer granted by a public entity52.
As concerns the methods of eliminating transfer payments, if it is possible to determine their exact
value, they should be directly eliminated from the cash flows. For example, VAT payments on
construction costs can be simply dropped off in the economic analysis. If it is not possible to determine
their exact value, they should be eliminated from the project cash flows using conversion factors (see
section 2.8.4).
In some projects the fiscal impact can be significant because, for example, the revenues generated by
the project may decrease the need to finance budgetary deficits by public debt or taxation.53
Despite the general rule, in some cases indirect taxes (or subsidies) are intended as a correction
for externalities. For example, taxes on NOx emissions to discourage negative environmental
externalities. In this and in similar cases, it is justified to include these taxes (subsidies) in project
costs (benefits), provided that they adequately reflect the underlying marginal cost (Willingness-To-
Pay (WTP)), but the appraisal should avoid double counting (e.g. including both energy taxes and
estimates of full external environmental costs).
2.8.3 From market to shadow prices
When market prices do not reflect the opportunity cost of inputs and outputs, the usual approach is to
convert them into shadow prices to be applied to the items of the financial analysis. A simplified
operational approach for the estimation of the shadow prices is presented in the Figure below.
Figure 2.3 From market to shadow prices
Market prices
Outputs Inputs
Non tradable Tradable
Major items Minor items
Other Labour
Willingness-to- Long run Shadow Standard
Border prices
pay marginal cost Wage Conversion Factor
Shadow prices
Source: Adapted from Saerbeck (1990)
51 Social security payments, on the contrary, shall be included and considered as a delayed salary. See Evans (2006).
52 As specified in section 2.9.7, this is, however, an exceptional case since the practice in economic analysis is to replace tariffs with
willingness-to-pay.
53 One Euro of uncommitted income in the public sector budget may be worth more than in private hands because of the distortionary effects
of taxation. Under non-optimal taxes, Marginal Cost of Public Funds (MCPF) values higher or lower than unity should be used to adjust the
flows of public funds to and from the project. If there are no national guidelines on this issue, MCPF=1 is the default rule suggested in this
guide.
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In practice, the following (simplified) operational approach can be applied to convert financial items
into shadow prices.
Project inputs:
if they are tradable goods, border prices are used54. If a project uses an imported input, e.g.
gas and oil, the shadow price is the import cost plus insurance and freight (CIF) in more
liberalised (i.e. competitive and undistorted) markets, thus excluding any custom duties or
taxes applied once the good enters the national market. Border prices can be expressed as a
percentage of the price of the goods, as a fixed amount per unit or as a minimum price applied
as soon as the good passes the border. Where the relevant economic border lies is a matter to
be ascertained on a case-by-case basis. In the context of the EU funds, the external border of
the EU may be considered relevant for most goods.
If they are non-tradable goods:
o the Standard Conversion Factor, which measures the average difference between world
and domestic prices of a given economy (see box for an example) is applied in the case of
ʻminorʼ items, e.g. administrative costs, intermediate services, etc.;
o ad hoc assumptions, depending on the specific hypotheses made on market conditions,
should be undertaken in the case of ʻmajorʼ items, e.g. land55, civil works, machinery,
equipment, etc. to reflect their long run marginal cost56;
o for manpower, the Shadow Wage is calculated.
The method generally used to operationally put into practice the different techniques presented above
is to apply a set of conversion factors to the project financial costs. Section 2.9.5 below briefly presents
the implications of this practice, while for a more detailed discussion about the existing empirical
approaches to convert project inputs into shadow prices see Annex III. The shadow wage is treated
separately in section 2.9.6 and in Annex IV.
Project outputs:
Users’ marginal Willingness-To-Pay (WTP), which measures the maximum amount
consumers are willing to pay for a unit of a given good, is used to estimate the direct benefit(s)
related to the use of the goods or services rendered by the project.
Section 2.9.7 shows the operational approach that should be followed to quantify the project outputs
at users’ WTP. Annex VI discusses, in detail, the current techniques to estimate WTP and the scope for
application.
54 This rule comes from the tradition of applied CBA to developing countries, with highly distorted national or local prices, for which
international prices are a good approximation of opportunity costs. Although the extent of price distortions in this context may be less
relevant, the rationale remains valid.
55 Many public investment projects use land as a capital asset, which may be state-owned or purchased from the general government budget.
Whenever there are alternative options for its use, land should be valued at its opportunity cost and not at historical or official accounting
value. This must be done even if land is already owned by the public sector. If it is reasonable to assume that market price captures
considerations about land’s utility, desirability and scarcity, then it can generally be considered reflective of the economic value of land. On
the other hand, whenever the project appraiser has knowledge of rental, purchase or expropriation prices which are lower or higher price
than the market price, specific assumptions must be made to measure the gap between the land’s opportunity cost and the distorted price.
56 Or, in some cases, their willingness to pay, or a combination of the two. The long run marginal cost is defined as the change in the long-run
total cost of producing a good or service resulting from a change in the quantity of output produced.
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EXAMPLE: APPLICATION OF THE SCF
An illustrative computation of the Standard Conversion Factor (SCF) for a hypothetical country is hereby
presented. As shown in Annex III, the simplified formula for the estimation of the SCF is:
SCF = (M+X)/ (M+X+TM)
where: M is the total value of import at shadow prices, i.e. CIF prices; X is the total value of export at shadow
prices, i.e. FOB prices; TM is the total value of duties on import.
It is assumed that the total value of export at FOB prices and of import at CIF prices, in a given year, including
both intra-EU and extra-EU trade of all products and services, are respectively EUR 25,000 million and
EUR 20,000 million. In the same year, the national general government and the EU collect EUR 500 million as
taxes and duties on imports, excluding VAT. Export taxes, duties and other monetary compensatory amounts on
exports are nil, as well as import and export subsidies.
International trade detailed data and main national accounts tax aggregates are provided both by Eurostat and
national statistics institutes. Hence, in this example:
M= EUR 25 000 million
X= EUR 20 000 million
TM= EUR 500 million.
𝟐𝟓,𝟎𝟎𝟎+𝟐𝟎,𝟎𝟎𝟎
The SCF formula leads to the following result: 𝑺𝑪𝑭 = = 𝟎. 𝟗𝟖𝟗
𝟐𝟓,𝟎𝟎𝟎+𝟐𝟎,𝟎𝟎𝟎+𝟓𝟎𝟎
The variables in the SCF formula generally do not undergo significant variations on a yearly basis. For this reason
the SCF could be either computed for a single year, or as an average of a number of years.
2.8.4 Application of Conversion Factors to project inputs
Transforming inputs market prices into shadow prices is completed, in practice, through the
application of Conversion Factors. These are defined as the ratio between shadow prices and market
prices. They represent the factor at which market prices have to be multiplied to obtain inflows valued
at shadow price. Formally:
𝑣𝑖
𝑘𝑖 = ⇔ 𝑣𝑖 = 𝑘𝑖 ∙ 𝑝𝑖
𝑝𝑖
where: pi are market prices for the good i, vi are shadow prices for the same good and ki are the
conversion factors.
If the conversion factor for one good is higher than one, then the observed price is lower than the
shadow price, meaning that the opportunity cost of that good is higher than that captured by the
market. Conversely, if the conversion factor is lower than one, then the observed price is higher than
the shadow price, due to taxes or other market distortions which add to the marginal social value of a
good and determine a higher market price.
In principle, Conversion Factors should be made available by a planning office and not calculated on a
project-by-project basis. When national parameters are not available, project-specific calculations can
be made but these must then be consistent across projects57. At least, corrections should be applied to
depurate market prices from fiscal factors, e.g. an excise tax on import. The following box provides an
example.
In the absence of evidence of market failures, the CFs should be set equal to 1.
57 It is up to the managing authorities to ensure such consistency.
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EXAMPLE: CONVERSION FACTOR FOR MATERIALS
As an example, let us assume that concrete is an input cost of the investment project. If the unit price of concrete
used for the project is EUR 10,000, of which 20 % is VAT58 and import tax rate is 7 % (regardless of the country
of origin), a simplified way to estimate the shadow price is to use the conversion factor (CF) computed as
follows:
CF = (1-i)*(1-VAT)
where i is the import tax rate of the input good entering the CBA. Thus, the shadow price (SP) can be estimated
by multiplying the CF by the observed market price (MP) of this good:
SP = (1-i)*(1-VAT)*MP
The CF will amount to CF= (1-0.07)*(1-0.2) =0.93*0.8 =0.744 and the shadow price would be equal to
SP=0.744*10,000=7,440.
Since the import tax rate could differ depending on the type of good considered, in order to compute the shadow
price of the aggregated item ʻmaterialsʼ the project appraiser could use the average tax rate applying to those
materials which are more commonly used in investment projects, such as bricks, iron, tubes, concrete,
bituminous materials, plastics and other chemical products (e.g. paints), wood, etc. The same approach can also
be applied for other cost items. As suggested in Annex III, the Input-Output matrix or the Use Table of a given
economy can be used to breakdown aggregated input factors such as civil works, equipment, materials, etc. into
their main sub-components, in order to disentangle the traded components to which the border price rule
applies, and then compute the conversion factor as a weighted average.
2.8.5 The shadow wage
Current wages may be a distorted social indicator of the opportunity cost of labour because labour
markets are imperfect, or there are macroeconomic imbalances, as revealed particularly by high and
persistent unemployment or by dualism and segmentation of labour conditions (e.g. when there is an
extensive informal or illegal economy). The project promoter, in such cases, may resort to a correction
of observed wages and to the use of conversion factors for computing shadow wages.
WAGE DISTORTION: EXAMPLES
- In the private sector, labour costs for a private company may be lower than the social opportunity cost because
the State gives special subsidies to employment in some areas.
- There may be legislation fixing a minimum legal wage, even if due to heavy unemployment there may be people
willing to work for less.
- There are informal or illegal sectors with no formal wage or income, but with a positive opportunity cost of
labour.
The shadow wage measures the opportunity cost of labour. Typically, in an economy characterised by
extensive unemployment or underemployment, this may be less than the actual wage rates paid. In
particular:
for skilled workers previously employed in similar activities, the shadow wage can be assumed
equal or close to the market wage;
for unskilled workers drawn to the project from unemployment, it can be assumed equal to or
not less than the value of unemployment benefits or other proxies when unemployment
benefits do not exist;
for unskilled workers drawn to the project from informal activities, it should be equal to the
value of the output forgone in these activities.
58 In this case, VAT is not recoverable by the project promoter and thus was included in the financial analysis.
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The methodology to estimate the shadow wage at the national/regional level is illustrated in Annex IV,
providing an example of computation which refers to year 2011. Member States are encouraged to
develop their own national/regional benchmarks following the approach depicted in the Annex. In the
absence of national/regional data, a shortcut formula for determination of the shadow wage is
illustrated in the box below.
SHADOW WAGE: SHORTCUT FOR ESTIMATION
A practical solution to determine the shadow wage can be the reduction of unit labour costs by a percentage
determined by the share of income taxation: SW = W*(1-t)
where: SW is the shadow wage, W is the market wage and t is the income taxation.
If a country is suffering from a high unemployment rate, the shadow wage may be inversely correlated to the
level of unemployment. The following formula might be adopted for unskilled manpower used on project
construction sites in order to take into account an ʻunemployment effectʼ, i.e. the excess supply of labour
compared to the market clearing level in the case of a persistently high unemployment: SW = W*(1-t)*(1-u)
where: u is the unemployment rate of the region.
For more detailed SW formulas at regional level see Del Bo et al. (2011).
2.8.6 Evaluation of direct benefits
The concept of marginal WTP is commonly used to estimate the shadow price of the project output. In
other words, to evaluate the project direct benefits, related to the use of the goods or services
rendered. The WTP measures the maximum amount of people who would be willing to pay for a given
outcome that they view as desirable. Different techniques, including revealed preference, stated
preference and benefit transfer methods, exist to empirically estimate the WTP. The adoption of one or
another method depends on both the nature of the effect considered and the availability of data. For a
detailed discussion of the methods to estimate the WTP and some examples of practical application
see Annex VI.
In absence of WTP estimates derived directly from users, or in the impossibility to adopt a benefit
transfer, other proxies of WTP can be used. A commonly accepted practice is to calculate the avoided
cost for users to consume the same good from an alternative source of production. For example, in the
case of water supply projects, the avoided cost of water transported in tank lorries; in wastewater, the
avoided cost of building and operating individual septic tanks; in energy, the avoided cost of substitute
fuels (e.g. gas vs. coal) or alternative generation technologies (e.g. renewable energy sources vs. fossil
fuels). The following box provides an empirical example of the application of this methodology.
EXAMPLE: AVERTIVE EXPENDITURE METHOD TO VALUE THE RELIABILITY OF WATER SUPPLY
Within the study ʻEx-post evaluation of investment projects co-financed by the ERDF/CF in the period 1994-
1999' the EC evaluated the impact of a water supply investment aimed at solving the problem of water shortages
and rationing affecting the citizens of Palermo during the 1970s and the 1980s. The project involved the partial
substitution of the water distribution network, representing 50 % of the overall network and serving about 60 %
of Palermo inhabitants. Before the project, water was rationed so that inhabitants were forced to equip
themselves with domestic tanks and electric devices for collecting and pumping water into the house water
systems with adequate pressure. After the project, in most cases, this equipment is no longer needed, especially
where water is supplied 24 hours per day and at a high pressure. The WTP of improved service delivery was
monetised in terms of avoided costs of maintaining and operating the electric pumps. These include the
investment costs for purchasing the pump, the energy costs, the maintenance costs and time spent by users for
the self-provision of water during the rationing periods. For about 73,000 users supplied by the renovated
network, the net present value of the service costs avoided over the 2003-2027 period is estimated at almost
EUR 67 million (2011 prices).
Source: EC (2012)
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In practice, the economic analysis evaluation of the project’s direct benefits is carried out by replacing
the financial revenues, in the form of user fees, charges or tariffs, with the estimation of the users WTP
for project outputs less changes in supply costs59. This operation is grounded on the following reasons:
in sectors not exposed to market competition, regulated, or influenced by public sector
decisions, the charges paid by the users may not adequately reflect the social value of actually
or potentially using a given good. A typical example is a publicly provided good, e.g. health
care, for which a administered tariff is paid by users;
in addition, the use of a good or service may generate additional social benefits for which a
market does not exist and therefore no price is observed. For example, time savings and
prevention of accidents for the users of a new, safer, transport service.
For both reasons, the WTP provides a better estimate for the social value of the good or service than
the observed tariffs. Also, the WTP is used for the projects providing outputs that are not subject to
charges (e.g. a free recreational area). For a review of the typical direct benefits per sector see
chapters 3 to 7.
For the evaluation of some outputs, when the WTP approach is not possible or relevant, long-run
marginal cost (LRMC) can be the default accounting rule. Usually WTP is higher than LRMC in
empirical estimates, and sometimes an average of the two is appropriate.
2.8.7 Evaluation of non-market impacts and correction for externalities
Impacts generated on project users due to the use of a new or improved good or service, which are
relevant for society, but for which a market value is not available, should be included as project direct
benefits (see section 2.8.6) in the economic analysis of project appraisal. In principle, the WTP
estimated for the use of the service should capture these effects and facilitate its integration in the
analysis. Examples of (positive) non-market impacts are: savings in travel time; increased life
expectancy or quality of life; prevention of fatalities; injuries or accidents; improvement of landscape;
noise reduction; increased resilience to current and future climate change and reduced vulnerability
and risk60, etc.
When they do not occur in the transactions between the producer and the direct users of the project
services but fall on uncompensated third parties, these impacts are defined as externalities. In other
words, an externality is any cost or benefit that spills over from the project towards other parties
without monetary compensation. Environmental effects are typical externalities in the context of
CBA61 (see box for some examples). For a review of the typical external costs and benefits per sector
see chapter 3.
Due to their nature, externalities are not captured with the evaluation of the project direct benefits and
they need to be evaluated separately. Again, a WTP (or willingness-to-accept (WTA)62) approach
should be adopted to include these effects into the appraisal.
Valuing externalities can sometimes be difficult even though they may be easily identified. For some
specific effects, however, studies available in the literature provide reference values to be used in
given contexts. This is, for example, the case of the ExternE63, HEATCO64or DG Move ʻHandbook on
estimation of external costs in the transport sectorʼ65, which provide some reference unit costs for
59 This is true as a general rule. Each sector, however, may present own specificities and traditions about the evaluation of the direct benefits.
For example, in some sectors, project revenue scan be used as a proxy of WTP in relation to the direct market impact, though the clear
limitation is that this would reflect a minimum rather than a maximum WTP, the latter being the correct measure of value. These specificities,
when occurring, are discussed in the sectorial guidelines (chapter 3).
60 The benefits of measures taken to enhance the resilience to climate change, weather extremes and other natural disasters should be
assessed and included in the economic analysis, and if possible quantified, otherwise they should be properly described.
61 See Pearce, Atkinson and Mourato (2006) for a review of recent literature.
62 See Annex VI .
63 ExternE is the acronym for ʻExternal Costs of Energyʼ and a synonym for a series of projects starting from early 90s till 2005. Results are
available at: http://www.externe.info/externe_2006
64 Developing Harmonised European Approaches for Transport Costing and Project Assessment, http://heatco.ier.uni-stuttgart.de/
65 See: http://ec.europa.eu/transport/themes/sustainable/doc/2008_costs_handbook.pdf
\50
emissions of carbon dioxide, noise and air pollutants. With this data, assessment of externalities
becomes relatively straightforward: this requires an estimate of the externality volume (e.g. increase
in decibels of noise to the exposed population) to be multiplied by the appropriate unit price (e.g. Euro
per decibel per person). The inter-temporal elasticity of environmental externalities to GDP per capita
growth could be used to take into account that their unit prices, which are usually expressed for a
given base-year, should have increasing values over the life cycle of the project.
Significant progress has been made in recent years in refining the estimates of unit values of non-
market impacts and improving methods to integrate such values into economic analysis.
Developments in this field, both empirical and theoretical are, however, still needed, in order to
broaden the range of externalities considered, such as the conservation of ecosystem services.
Considering that ecosystem services change is one of the vital aspects of welfare, this should be always
taken into account as potential for any project66.
Whenever money quantification is not possible, environmental impacts should at least be identified in
physical terms for a qualitative appraisal in order to give to decision-makers more elements to make a
considered decision. CBA and EIA are both required by EU regulations and should be considered in
parallel and, whenever possible, should be integrated and consistent.
ENVIRONMENT EXTERNALITIES: EXAMPLES
Noise. Any increase or decrease of noise emissions affects activities and health. It is mainly relevant for
infrastructures crossing or near densely populated areas.
Air pollution. Emissions of localised air pollutants such as nitrous oxide, sulphur dioxide, or small particulate
matter, etc. have negative impacts on human health, generate material damage and loss of crops and affect
ecosystems. It is relevant to all infrastructures which significantly modify the energy consumption mix of a given
region.
Greenhouse gases emissions. Projects can emit greenhouse gases (GHG) into the atmosphere either directly,
e.g. fuel combustion or production process emissions, or indirectly through purchased electricity and/or heat.
GHG emissions have a worldwide impact due to the global scale of the damage caused, thus there is no difference
in where the GHG emissions take place. On the other hand, some projects may lead to reduction of GHG
emissions throughout their life cycle, which means that those GHG-related externalities can be positive.
Soil contamination. This is caused by the presence of human-made chemicals or other alterations in the natural
soil environment, typically as consequence of industrial activity, agricultural chemicals or improper disposal of
waste. Its effects on production, consumption and human health can be deferred over time.
Water pollution. Water pollution is the contamination of water bodies, e.g. lakes, rivers, oceans, aquifers and
groundwater. This occurs when pollutants are discharged directly or indirectly into water bodies without
adequate treatment to remove harmful compounds.
Ecosystem degradation. New infrastructure projects can deplete water sources, increase habitat fragmentation
and contribute to deterioration of biodiversity, loss of habitats and species. The economic costs come in the form
of lost services when an ecosystem is degraded and loses its functions.
Landscape deterioration. This usually involves a loss of recreational or aesthetic value.
Vibrations. Mainly from transport projects, these affect the quality of urban life and can interfere with certain
production and consumption activities.
66 The ecosystems approach is a way of incorporating the natural environment in the decision making process that takes into consideration
the way that the natural environment works as a system. This framework offers a more comprehensive approach to understanding how
policies affect the wider environment. It is not an additional step within the appraisal process but a specific way of thinking about
environmental impacts. Use of this framework is particularly recommended where there are multiple environmental effects affecting both
market and non-market values. This can ensure that the entire range of environmental effects from a proposed policy or project is taken into
account in appraisal. For example, the UK Treasury has published supplementary guidance for policy appraisal that recommends the use of
the ecosystem services framework. See for example Dunn (2012).
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2.8.8 Evaluation of GHG emissions
Climate change impacts occupy a special position in the externalities assessment because:
climate change is a global issue, so the impact of emissions is not dependent on the location of
the emissions;
GHGs, especially carbon dioxide (CO2), but also nitrous oxide (N2O) and methane (CH4) have a
long lifetime in the atmosphere so that present emissions contribute to impacts in the distant
future;
the long-term impacts of continued emissions of greenhouse gases are difficult to predict but
potentially catastrophic;
scientific evidence on the causes and future paths of climate change is becoming increasingly
consolidated. In particular, scientists are now able to attach probabilities to the temperature
outcomes and impacts on the natural environment associated with different levels of
stabilisation of GHGs in the atmosphere.
The proposed approach to integrate climate change externalities into the economic appraisal is based,
in part, on the EIB Carbon Footprint Methodology67 and is consistent with the EU Decarbonisation
Roadmap 2050. It consists of the following steps:
quantification of the volume of emissions additionally emitted, or saved, in the
atmosphere because of the project. Emissions are quantified on the basis of project-specific
emission factors (e.g. t-CO2 per unit of fuel burnt, kg-CO2 per kilometre travelled, etc.) and are
expressed in tonnes per year. In the absence of project-specific data, default emission factors
from the economic literature can be used. The sectorial chapters provides instructions on
where to find data sources to be used as a benchmark;
calculation of total CO2-equivalent (CO2e)emissions using Global Warming Potentials
(GWP). GHGs other than CO2 are converted into CO2e by multiplying the amount of emissions
of the specific GHG with a factor equivalent to its GWP. For example, set the GWP of CO2 equal
to unity (=1), the GWP for CH4 and N2O are 25 and 298 respectively, indicating that their
climate impact is 25 and 298 times larger than the impact of the same amount of CO 2 emissions
(IPPC, 2007);
evaluation of externality using a unit cost of CO2-equivalent. Total tonnes of CO2e
emissions are multiplied by a unit cost expressed in Euro/tonne. It is suggested to use the
values illustrated in table 2.10, for the central scenario, going from EUR 25 per tonne of CO2e in
2010 and then assuming a gradual increase to EUR 45 per tonne of CO2e until 203068. Due to
the global effect of global warming, there is no difference between how and where in Europe
GHG emissions take place. For this reason, the same unit cost factor applies to all countries.
However, the cost factor is time-dependent in the sense that emissions in future years will
have greater impacts than emissions today.
Table 2.10 Unit cost of GHG emissions
Value 2010 69
Annual adders 2011 to 2030
(Euro/t-CO2e)
High 40 2
Central 25 1
Low 10 0.5
Source: EIB (2013).
67 Regarding volume of emissions, see EIB, 2013, Induced GHG Footprint. The carbon footprint of projects financed by the Bank.
Methodologies for the Assessment of Project GHG Emissions and Emission Variations, Version 10. Regarding the price of carbon, see EIB
(2013), The Economic Appraisal of Investment Projects at the EIB, chapter 4 ʻIncorporating Environmental Externalitiesʼ.
68 Note that the values reported are in 2006 EUR and would need to be adjusted to the price level used in the analysis.
69 For assets which emit GHGs beyond 2030, it is recommended as a lower bound to continue the adders at the 2011 to 2030 rate. However,
as several models suggest that marginal damage rises in time, analysts should review the available literature. The EIB is expected to adopt
figures beyond 2030 in the near future.
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Finally, if the change in carbon content of the project is significant, it is recommended that a carbon
switching price is calculated, which is the price for carbon at which a decision-maker is indifferent
between two (or more) specified project options70. This would offer another perspective on the impact
of a given project on GHG emissions and the way in which this might inform project selection.
COST OF GHG EMISSIONS: APPLICATION RULES
In order to determine the external cost of climate change emissions, the following simplified formula must be
applied: Cost of GHG emission = VGHG* CGHG
where:
- VGHG is the incremental volume of GHG emissions produced by the project, expressed in CO 2 equivalents;
- CGHG is the unit shadow price (damage cost) of CO2, actualised and expressed at prices of the year at which the
analysis is carried out.
As outlined in section 2.9.2, GHG emissions in future time periods should be discounted at the social
discount rate applied to the project as a whole, reflecting the marginal impact of the project. However,
it should be noted that the unit cost for GHG emissions may implicitly include a different social
discount rate which reflects the impact of non-marginal GHG policy on the long term and uncertain
damage from emission pathways. This is discussed further in Annex II.
2.8.9 The residual value
In economic analysis, the shadow price of the project’s residual value must be estimated. This may be
done in two mutually exclusive ways:
by computing the present value of economic benefits, net of economic costs, in the remaining
life-years of the project. This approach shall be adopted when the residual value is calculated
in the financial analysis with the net present value of future cash flows method (see section
2.8.3);
by applying an ad hoc conversion factor to its financial price. This is calculated as an average of
the CFs of the single cost components, weighted by the relative share of each component in the
total investment. This approach shall be adopted when the depreciation formula has been used
in the financial analysis.
2.8.10 Indirect and distributional effects
Shadow pricing of project inputs and outputs, and monetisation of externalities, already account for
the main relevant impacts of a project on welfare. Accordingly, indirect effects occurring in
secondary markets (e.g. impacts on the tourism industry) should not be included in the
evaluation of the project’s costs and benefits. The main reason for not including indirect effects is
not because they are more difficult to identify and quantify than direct effects, but because - if the
secondary markets are efficient71 - they are irrelevant in a general equilibrium setting, as they are
already captured by the shadow prices. Adding these effects to the costs and benefits already
measured in primary markets usually results in double-counting (see box).
70 See Hamilton and Stover (2012).
71 According to Boardman (2006), if the secondary markets are inefficient (e.g. there are economies of scale) and the project is large enough
to affect prices in the secondary markets, these additional welfare effects shall instead be attributed to the project and included in the
economic analysis.
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BENEFIT DOUBLE-COUNTING: EXAMPLES
Double Counting of Benefits. In considering the value of an irrigation project, both the increase in value of the
land and the present value of the increase in income from farming are counted as benefits. Only one of these
should be counted because one could either sell the land or keep it and get the gains as a stream of income.
Counting Secondary Benefits. If a road is constructed, one might count the additional trade along the road as a
benefit. However, under equilibrium conditions in competitive markets the new road may be displacing
commercial activity elsewhere, so the net gain to society may be small or zero. People forget to count the lost
benefits elsewhere (e.g. for newly generated traffic).
Counting Labour as a Benefit. In arguing for ‘pork barrelʼ projects, some politicians often talk about the jobs
created by the project as a benefit. But wages are part of the cost of the project, not the benefits. The social
benefit of employment is already given by using shadow wages. However, a separate analysis of labour market
impact can be helpful in some circumstances and is required by the Funds regulations.
On the other hand, shadow prices do not capture well, with a numeraire-based quantification, the
distribution of the project costs and benefits across users and other stakeholders. Thus, the
need for distinct analysis of the project impact on the welfare of specific target groups.
The distributional analysis requires the identification of a list of relevant effects and stakeholders that
will be affected in a noticeable way by the implementation of the project. Typical effects refer to
charges, time, reliability of service, comfort, convenience, safety, as well as environmental and
territorial impacts. Typical stakeholders are users, operators, infrastructure managers, contractors,
suppliers, and government (but the identification of stakeholders may differ across countries).
In operational terms, in order to summarise all the effects that are encountered by the project, a
matrix can be developed linking each project effect with the sectors and the stakeholders affected by
that impact. This methodology draws from the approaches of the SE Matrix suggested in the RAILPAG
Guide72 (see box), as well as the BIT table (Benefit Incidence Table, even called Morisugi table from the
name of its inventor) used in Japan for the appraisal of transport projects.
Alternatively, another method of analysing distributional issues consists of deriving explicit welfare
weights from social inequality aversion estimates to be attached to the project winners and losers.
This approach is illustrated in Annex V.
STAKEHOLDER MATRIX
The stakeholders matrix enables the presentation of the overall project in a way that relates effects (in the rows)
and stakeholders (in columns) summarising the main economic and financial implications of the project,
showing the transfers between stakeholders and the distribution of costs and benefits. It enables to estimate ‘net’
contributions, by cancelling out negative effects (for example displaced employment, displaced output) with
positive effects. It also enables equity considerations if welfare weights are incorporated into the analysis.
Non users
Users (or Service Contracting Firms
Tax payers
Stakeholders (by alternative operating & supplying (by
(local/regional/national/EU)
category) service companies companies sector)
users)
Effects
External/internal
Effect 1
Effect 2
Effect 3
…
Source: adapted from RAILPAG
72 RAILPAG (Railways Project Appraisal Guidelines), available at www.railpag.com
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2.8.11 Economic performance
Once all project cost and benefits have been quantified and valued in money terms, it is possible to
measure the economic performance of the project by calculating the following indicators (table 2.11):
Economic Net Present Value (ENPV): the difference between the discounted total social
benefits and costs;
Economic Rate of Return (ERR): the rate that produces a zero value for the ENPV;
B/C ratio, i.e. the ratio between discounted economic benefits and costs.
ECONOMIC PERFORMANCE INDICATORS
The difference between ENPV and FNPV is that the former uses accounting prices or the opportunity cost of
goods and services instead of imperfect market prices, and it includes as far as possible any social and
environmental externalities. This is because the analysis is done from the point of view of society, not just the
project owner. Because externalities and shadow prices are considered, some projects with low or negative
FNPV(C) may show positive ENPV.
The ENPV is the most important and reliable social CBA indicator and should be used as the main reference
economic performance signal for project appraisal. Although ERR and B/C are meaningful because they are
independent of the project size, they may sometimes be problematic. In particular cases, for example, the ERR
may be multiple or not defined, while the B/C ratio may be affected by considering a given flow as either a
benefit or a cost reduction.
In principle, every project with an ERR lower than the social discount rate or a negative ENPV should
be rejected. A project with a negative economic return uses too many socially valuable resources to
achieve too modest benefits for all citizens. From the EU perspective, sinking a capital grant in a
project with low social returns means diverting precious resources from a more valuable development
use. For a discussion about the use of the project performance indicators for economic analysis see
Annex VII.
Table 2.11 Economic rate of return. EUR thousands
CF Years
1 2 3 4 5 6-15 16 17-29 30
Willingness to pay 1 0 0 0 19,304 19,419 … 20,365 … 20,365
Willingness to pay 2 0 0 0 437 437 … 437 … 437
Reduced noise emission 0 0 0 4,200 4,200 … 4,200 … 4,200
Reduced air pollution 0 0 0 1,900 1,900 … 1,900 … 1,900
Total Benefits 0 0 0 25,841 25,957 … 26,902 … 26,902
Total operating costs 0.88 0 0 0 4,882 4,897 … 5,016 … 5,016
Initial Investment 0.97 8,228 73,071 41,689 0 0 … 0 … 0
Replacement costs 0.98 0 0 0 0 0 11.664 0 9.575 0
Residual value 0.97 0 0 0 0 0 … 0 … -4,146
Total costs 8,228 73,071 41,689 4,882 4,897 … 23,428 … 871
Net economic benefits -8,228 -73,071 -41,689 20,959 21,060 … 3,474 … 26,032
ENPV 212,128
ERR 14.8%
B/C ratio 2.04
This CF is lower than CFs for Financial Revenues have been The application of a CF lower
investment because it includes a replaced with user than 1 to the project inputs has
willingness to pay for the use These are positive the effect of reducing the social
shadow wage correction for
of the service rendered. externalities. cost and improving the
labour in a context of
unemployment. economic performance.
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GOOD PRACTICES
- Cost savings in O&M or investment are accounted for and included on the cost side as a negative, i.e. as
decreasing costs and with appropriate conversion factors.
- Project positive impacts on employment are captured by applying the Shadow Wage Conversion Factor to
(unskilled) labour cost and not including job creations as a direct benefit of the project.
- Project impacts on the overall economy (i.e. GDP growth) are excluded from the analysis of the project benefits.
- If specific indirect taxes are intended to correct for externalities, then these are included in economic analysis
to reflect the social marginal value of the related externalities, provided that they adequately reflect the
underlying WTP or marginal damage cost and there is no double-counting with other economic costs.
COMMON MISTAKES
- In the economic analysis a nil cost is given to the opportunity cost of land owned by a local municipality,
although it may have value in other uses (e.g. it may be rented to local farmers).
- Conversion factors are ʻborrowedʼ from other countries without justification.
- Revenues from tariffs are included as an economic benefit in addition to consumers’ marginal willingness to
pay for the service rendered.
- Failure to isolate the ʻincrementalʼ economic benefits of the project, i.e. the benefits which are not displaced
from other markets. This is especially evident in cases where it is attempted to measure secondary indirect
impacts.
- Together with the application of the shadow wage on the cost side, benefits from job creation are included on
the benefit side.
- Revenues from the sale of green certificates are included together with the external benefit of avoided GHG
emissions.
2.9 Risk assessment
As set out in Article 101 (Information necessary for the approval of a major project) of Regulation (EU)
No 1303/2013, a risk assessment must be included in the CBA. This is required to deal with the
uncertainty that always permeates investment projects, including the risk that the adverse impacts of
climate change may have on the project. The recommended steps for assessing the project risks are as
follows:
sensitivity analysis;
qualitative risk analysis;
probabilistic risk analysis;
risk prevention and mitigation.
The rest of the section presents the aforementioned steps.
2.9.1 Sensitivity analysis
Sensitivity analysis enables the identification of the ʻcriticalʼ variables of the project. Such variables are
those whose variations, be they positive or negative, have the largest impact on the projectʼs financial
and/or economic performance. The analysis is carried out by varying one variable at a time and
determining the effect of that change on the NPV. As a guiding criterion, the recommendation is to
consider ʻcriticalʼ those variables for which a variation of ±1 % of the value adopted in the base case
gives rise to a variation of more than 1 % in the value of the NPV.The tested variables should be
deterministically independent and as disaggregated as possible. Correlated variables would give rise
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to distortions in the results and double-counting. Therefore, before proceeding to the sensitivity
analysis, the CBA model should be reviewed with the aim of isolating the independent variables and
eliminating the deterministic interdependencies (e.g. splitting a variable in its independent
components). For example, ʻrevenueʼ is a compound variable, which depends on the two independent
items ʻquantityʼ and ʻtariffʼ, both of which should be analysed. Table 2.12 gives an illustrative example.
Table 2.12 Sensitivity analysis. Example
Variable Variation of the FNPV Criticality Variation of the ENPV Criticality
due to a ± 1 % variation judgement due to a ± 1 % variation judgement
Yearly population growth 0.5 % Not critical 2.2 % Critical
Per capita consumption 3.8 % Critical 4.9 % Critical
Unit tariff 2.6 % Critical N/A N/A
Total investment cost 8.0 % Critical 8.2 % Critical
Yearly maintenance cost 0.7 % Not critical 0.6 % Not critical
Per capita willingness to
Not applicable - 12.3 % Critical
pay
Annual noise emissions Not applicable - 0.8 % Not critical
Source: Authors
A particularly relevant component of the sensitivity analysis is the calculation of the switching values.
This is the value that the analysed variable would have to take in order for the NPV of the project to
become zero, or more generally, for the outcome of the project to fall below the minimum level of
acceptability (see table 2.13). The use of switching values in sensitivity analysis allows making some
judgements on the risk of the project and the opportunity of undertaking risk-preventing actions. For
instance, in the example below, one must assess if a 19 % investment cost increase which would make
the ENPV equal to zero thereby means that the project is too risky. Thus, the need to further
investigate the causes of this risk, the probability of occurrence and identify possible corrective
measures (see next section).
Table 2.13 Switching values. Example
Variable Switching values
Benefits/revenues
Minimum increase before the FNPV equals 0 104 %
Yearly Population growth
Maximum decrease before the ENPV equals 0 47 %
Minimum increase before the FNPV equals 0 41 %
Per capita consumption
Maximum decrease before the ENPV equals 0 33 %
Minimum increase before the FNPV equals 0 60 %
Tariff
Maximum decrease before the ENPV equals 0 Not applicable
Minimum increase before the FNPV equals 0 Not applicable
Per capita willingness to pay
Maximum decrease before the ENPV equals 0 55 %
Costs
Maximum decrease before the FNPV equals 0 82 %
Investment cost
Minimum increase before the ENPV equals 0 19 %
Maximum decrease before the FNPV equals 0 95 %
Yearly maintenance cost
Minimum increase before the ENPV equals 0 132 %
Maximum decrease before the FNPV equals 0 Not applicable
Annual noise emissions
Minimum increase before the ENPV equals 0 221 %
Source: Authors
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Finally, the sensitivity analysis must be completed with a scenario analysis, which studies the impact
of combinations of values taken by the critical variables. In particular, combinations of ʻoptimisticʼ and
ʻpessimisticʼ values of the critical variables could be useful to build different realistic scenarios, which
might hold under certain hypotheses. In order to define the optimistic and pessimistic scenarios it is
necessary to choose for each variable the extreme (lower and upper) values (within a range defined as
realistic). Incremental project performance indicators are then calculated for each combination. Again,
some judgments on the project risks can be made on the basis of the results of the analysis. For
example, if the ENPV remains positive, even in the pessimistic scenario, the project risk can be
assessed as low.
2.9.2 Qualitative risk analysis
The qualitative risk analysis aims shall include the following elements:
a list of adverse events to which the project is exposed;
a risk matrix for each adverse event indicating:
o the possible causes of occurrence;
o the link with the sensitivity analysis, where applicable;
o the negative effects generated on the project;
o the (ranked) levels of probability of occurrence and of the severity of impact;
o the risk level.
an interpretation of the risk matrix including the assessment of acceptable levels of risk;
a description of mitigation and/or prevention measures for the main risks, indicating who
is responsible for the applicable measures to reduce risk exposure, when they are considered
necessary.
To carry out the qualitative risk analysis, the first step involves the identification of adverse events
that the project may face. Building a list of potential adverse events is a good exercise to understand
the complexities of the project. Examples of events and situations with negative implications in the
implementation of the project and, in particular, generating cost overruns and delays in its
commissioning, are very varied and depend on the project specificities: landslides; adverse impacts of
extreme weather events; non-obtainment of permits; public opposition; litigation; etc.
Once the potential adverse events have been identified, the corresponding risk matrix may be built.
These are some brief instructions on how to operationally build it:
First, it is necessary to look at the possible causes of the risk materialising. These are the primary
hazards that could occur during the life of the project. All causes of each adverse event must be
identified and analysed, taking into account that several weaknesses of forecasting, planning and/or
management may have similar consequences over the project. The identification of the causes of
potential dangers can be based on ad hoc analyses or looking at similar problems that have been
documented in the past. In general the occurrence of a disaster is looked upon as a design weakness, in
the broadest possible sense, and therefore it is expected that all the potential causes of failure are
properly identified and documented. Examples can be: low contractor capacity; inadequate design cost
estimates; inadequate site investigation; low political commitment; inadequate market strategy, etc.
When appropriate, the link with the results of the sensitivity analysis should be made explicit by
showing which critical variables are affected by the adverse events. For example, for the adverse event
ʻunexpected geological conditionsʼ the corresponding critical variable is ʻinvestment costʼ, and so on.
However, depending on the nature of the event considered this is not always applicable (for example
no variable corresponds to qualitative events such as public opposition).
For each adverse event, the general effect(s) generated on the project and the relative consequences
on the cash flows should be described. For example, delays in the construction time will postpone the
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operational phase, which in turn, could threaten the financial sustainability of the project. It is
convenient to describe these effects in terms of what the project promoter (or the infrastructure
manager and services provider) might experience in terms of functional or business impacts. Each
effect should also be characterised by its consequences over the project calendar (short vs. long term
implications), relevant for both the prediction of the effect on the cash flows and the determination of
appropriate risk mitigation measures.
A Probability (P) or likelihood of occurrence is attributed to each adverse event. Below, a
recommended classification is given73, although in principle other classifications are possible:
A. Very unlikely (0–10 % probability)
B. Unlikely (10–33 % probability)
C. About as likely as not (33–66 % probability)
D. Likely (66–90 % probability)
E. Very likely (90–100 % probability)
To each effect a Severity (S) impact from, say, I (no effect) to VI (catastrophic), based on cost and/or
loss of social welfare generated by the project, is given. These numbers enable a classification of risks,
associated with their probability of occurrence. Below a typical classification is given (table 2.14).
Table 2.14 Risk severity classification.
Rating Meaning
I No relevant effect on social welfare, even without remedial actions.
Minor loss of the social welfare generated by the project, minimally affecting the project long run effects-
II
However, remedial or corrective actions are needed.
Moderate: social welfare loss generated by the project, mostly financial damage, even in the medium-long run.
III
Remedial actions may correct the problem.
Critical: High social welfare loss generated by the project; the occurrence of the risk causes a loss of the
IV primary function(s) of the project. Remedial actions, even large in scope, are not enough to avoid serious
damage.
Catastrophic: Project failure that may result in serious or even total loss of the project functions. Main project
V
effects in the medium-long term do not materialise.
Source: Authors
The Risk level is the combination of Probability and Severity (P*S). Four risk levels can be defined as
follows with the associated colours:
Risk level Colour Severity /
I II III IV V
Probability
Low A Low Low Low Low Moderate
Moderate B Low Low Moderate Moderate High
High C Low Moderate Moderate High High
Unacceptable D Low Moderate High Very High Very High
E Moderate High Very High Very High Very High
This exercise must be carried out during the planning phase so that decision makers can decide what
is the acceptable level and thus what mitigation measures must be adopted. During the risk analysis
included in the CBA, the remaining risks in the final design of the project are analysed. In principle no
unacceptable risks should remain. The classification is useful, however, to identify the potential
problems that the project might be confronted with.
Once the level of the remaining risks (P and S) is established, it is important to identify the mitigation
73 This is classification is in line with the provisions of the IPPCC report (http://www.climatechange2013.org/images/uploads/WGIAR5-
SPM_Approved27Sep2013.pdf) about the assessed likelihood of an outcome.
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and/or prevention measures foreseen.74 The diagram below shows, in a qualitative way, the kinds of
measures or combinations of measures to reduce the project risk prevailing in the various areas of the
above defined risk matrix. The identification of these measures requires a thorough knowledge of the
causes of risk and of the nature and the timing of the end effects.
Severity /
I II III IV V
Probability
A
Prevention or
B Mitigation
mitigation
C
D
Prevention Prevention and mitigation
E
The ʻintensityʼ of the measure should be commensurate to the level of risk. For risks with high level of
impact and probability, a stronger response and a higher level of commitment to managing them shall
be implemented. On the other hand, for low level risks, close monitoring could be sufficient. When the
risk level becomes unacceptable (a situation that should never materialise, in principle) the entire
project design and preparation must be revised. When identifying measures to mitigate existing risks,
it is mandatory to define who is responsible for their execution and in what stage of the project cycle
this will happen (planning, tendering, implementation, operation).
Finally, the impacts of the risk prevention and/or mitigation measures on the project’s resilience and
the remaining exposure to risk need to be assessed. For each adverse event, it is suggested to assess
the residual risk after the implementation of the measures. If risk exposure is assessed to be
acceptable (i.e. there are no longer high or very high risk levels), the proposed qualitative risk strategy
can be adopted. If a substantial risk remains, it is required to move to a probabilistic quantitative
analysis to further investigate the project risks (see next section).
Table 2.16 at the end of the section provides a simplified example of a risk prevention matrix for
illustrative purposes.
2.9.3 Probabilistic risk analysis
According to the CBA methodology, as described in Annex III to the Implementing Regulation on
application form and CBA methodology, the probabilistic risk analysis is required where the residual
risk exposure is still significant. In other cases it may be carried out where appropriate, depending on
project size and data availability.
This type of analysis assigns a probability distribution to each of the critical variables of the sensitivity
analysis, defined in a precise range of values around the best estimate, used as the base case, in order
to recalculate the expected values of financial and economic performance indicators.
The probability distribution for each variable may be derived from different sources, such as
experimental data, distributions found in the literature for similar cases, consultation with experts.
Obviously, if the process of generating the distributions is unreliable, the risk assessment is unreliable
as well. However, in its simplest design (e.g. triangular distribution, see Annex VII) this step is always
feasible and represents an important improvement in the understanding of the project’s strengths and
weaknesses as compared with the base case.
Having established the probability distributions for the critical variables, it is possible to proceed with
the calculation of the probability distribution of the FRR or net present value (NPV) of the project. For
this purpose, the use of the Monte Carlo method is suggested, which requires a simple computation
software The method consists of the repeated random extraction of a set of values for the critical
variables, taken within the respective defined intervals, and then the calculation of the performance
indices for the project (FRR or NPV) resulting from each set of extracted values. By repeating this
procedure for a large enough number of extractions, one can obtain a pre-defined convergence of the
74 Risk mitigation refers to actions aimed at systematic reduction in the extent of exposure to a risk. Risk prevention aims to systematically
reduce the likelihood of risk occurrence.
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calculation as the probability distribution of the IRR or NPV.
The values obtained enable the analyst to infer significant judgments about the level of risk of the
project. In the example shown in the table 2.15, ENPV can result in negative values (or ERR lower than
the SDR) with a probability of 5.3 %, disclosing a project with a low risk level. In other cases, however,
a mean (and/or median) value significantly below the base value can indicate future difficulties in the
materialisation of the expected project benefits.
Table 2.15 Results of Monte Carlo simulation. Example
Expected values ENPV ERR
Base case 36 649 663 7.56 %
Mean 41 267 454 7.70 %
Median 37 746 137 7.64 %
Standard deviation 28 647 933 1.41 %
Minimum value -25 895 645 3.65 %
Central value 55 205 591 7.66 %
Maximum value 136 306 827 11.66 %
Probability of the ENPV being lower than zero or ERR 0.053 0.053
being lower than the reference discount rate
Source: Authors
The result of the Monte Carlo drawings, expressed in terms of the probability distribution or
cumulated probability of the IRR or the NPV in the resulting interval of values, provide more
comprehensive information about the risk profile of a project. Figure 2.3 provides a graphical example.
Figure 2.3 Example of cumulated and punctual probability distribution of the ENPV
Cumulated distributions Punctual probabily
0,16
1,00
0,90 0,14
0,80 0,12
0,70 0,10
0,60
0,08
0,50
0,40 0,06
0,30 0,04
0,20 0,02
0,10
0,00
0,00 -21.840.583 18.710.035 59.260.653 99.811.271
-26.000.000 24.000.000 74.000.000 124.000.000
ENPV ENPV
Source: Authors
The cumulated probability curve (or a table of values) assesses the project risk, for example verifying
whether the cumulative probability for a given value of NPV or IRR is higher or lower than a reference
value that is considered to be critical. In the example shown in the above figure, the cumulative
probability of an ENPV value of EUR 18 824 851, which is set at 50 % of the base value, is 0.225, a
value high enough to recommend taking preventive and mitigation measures against the project risk.
For a more detailed illustration of how to perform a probabilistic risk analysis and how results should
be interpreted see Annex VIII.
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2.9.4 Risk prevention and mitigation
The implementation of the steps described above defines the risk prevention and mitigation strategy
of the project. Generally, a neutral attitude towards risks is recommended because the public sector
might be able to pool the risks of a large number of projects. In such cases, the assessment of the
switching values and of the scenario analysis results, followed by a well-established risk matrix (plus,
a probabilistic risk analysis if necessary) will summarise the risk assessment. In some cases, however,
the evaluator or the project promoter can deviate from neutrality and prefer to risk more (risk-taker)
or less (risk-adverse) for the expected rate of return. However, there must be a clear justification for
this choice.
Risk assessment should be the basis for risk management, which is the identification of strategies to
reduce risks, including how to allocate them to the parties involved and which risks to transfer to
professional risk management institutions such as insurance companies. Risk management is a
complex function, requiring a variety of competences and resources, and it can be considered as a role
for professionals, under the responsibility of the managing authority and the beneficiary. The project
promoter should, however, following the risk assessment, at least identify specific measures (including
responsibilities for their application) for the mitigation and/or prevention of the identified risks,
according to international good practice. For a more detailed discussion about the assessment of
acceptable risk levels and the definition of risk prevention and mitigation strategies see Annex VIII.
GOOD PRACTICES
- The sensitivity analysis is extended to all the independent variables of the project and, among them, the critical
variables are identified.
- A large enough numerical scale (i.e. a scale of 1-5) is used for adequate differentiation of probability of
occurrence and impact levels of the adverse effects.
- The cost of prevention/mitigation measures is included within the investment and/or O&M costs. This includes
risks linked to natural disasters or other similarly unforeseeable events which need to be either covered in the
technical design of the project and/or adequately insured (if possible).
- The switching values for critical variables are calculated also when projects show a negative FNPV(K) after EU
assistance. The necessary variation of a key variable to reach the benchmark is valuable information for the
appraiser.
- If, after all prevention/mitigation measures, there is still a considerable risk in the project, a probabilistic
analysis is carried out in addition to the qualitative assessment to quantify the probability of risk occurrence.
- Probability distributions of the input variables are adequately determined, for example on the basis of collected
experience in past projects.
COMMON MISTAKES
- Risks that are out of the control of the project promoter or other stakeholders (i.e. change of legislation) are
neglected in the analysis, although they may substantially contribute to the success/failure of the project.
- Too aggregated variables (e. g. benefits as a whole) are taken into account in the sensitivity and risk analysis. As
a consequence, it is not possible to identify which parameters the prevention/mitigation measures have focused
on.
- Independently from the type of analysis, risk prevention/mitigation measures are not identified.
- A too generic discussion on risk causes and prevention measures is carried out with no mention of their
likelihood of occurrence and/or identification of impacts.
- There is no identification of the risk ʻmanagerʼ, i.e. the function responsible for the implementation of the
identified risk prevention/mitigation measures.
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Table 2.16 Risk prevention matrix. Example
Adverse Variable Causes Effect Timing Effect on Probability Severity Risk Level Prevention and/or Residual risk
event cash flows (P) (S) Mitigation
measures
Set up of a Project
Delay in
Implementation Unit
establishing a
to be assisted by
Construction Investment Low contractor Delay in service positive cash
Medium C III Moderate technical assistance Low
delays cost capacity starting flow including
for project
benefits
management during
materialisation
implementation.
Higher (social)
Inadequate Investment The design of the
Project cost Investment costs in the
design cost costs higher Short D V Very high project must be Moderate
overrun cost first phase of
estimates than expected revised.
the project
Extra costs to
Not Inadequate site Interruption of
Landslides Long rehabilitate the A III Low Close monitoring Low
applicable investigation the service
service
Low political Delay in
commitment; establishing a
Delayed Delay in
Not Mismanagement positive cash
obtainment commencement Short A II Low Close monitoring Low
applicable of the licensing flow including
of permits of works
procedures benefits
process materialisation
Early definition of an
Inadequate appropriate social
market strategy Lower plan; Awareness-
Public Not Demand lower
Medium revenues and C V High raising activities and Moderate
opposition applicable Underestimation than expected
social benefits campaigns to raise
of threats the level of social
acceptance
Source: Authors
\63
2.10 Checklist
The following checklist closes the chapter. It is intended as a suggested agenda both from the
standpoint of the project promoter, who is involved in preparing the project dossier, and from that of
the project examiner, who is involved in reviewing the quality of the appraisal.
Step Question
Has an incremental approach been adopted?
Is the counterfactual scenario credible?
Has an appropriate time horizon been selected?
Have project effects been identified and monetised?
General
Have appropriate financial and social discount rates been adopted?
Does the economic analysis build on the financial analysis?
Is the methodology adopted consistent with the Commission’s or Member States’ own
guidance?
Is the social, institutional and economic context clearly described?
Have all the most important socio-economic effects of the project been considered in the
Presentation of the context of the region, sector or country concerned?
context
Are these effects actually attainable given the context?
Are there any major potential constraints to project implementation?
Does the project have clearly defined objectives stemming from a clear assessment of the
needs?
Is the project relevant in light of the needs?
Are the project objectives quantitatively identified by means of indicators and target values?
Definition of
objectives Is the project coherent with the objectives of the Funds and the EU operational programmes?
Is the project coherent with the national and regional strategies and priorities, as defined in
their development plans?
Are the means of measuring the attainment of objectives and their relationship, if any, with
the targets of the operational programmes indicated?
Does the project constitute a clearly identified self-sufficient unit of analysis?
Have combinations of self-standing components been appraised independently?
Has the technical, financial and institutional capacity of the promoter been analysed?
Has the impact area been identified?
Identification of the
project Have the final beneficiaries eventually profiting from the project been identified?
If the project is implemented by a PPP, is the PPP arrangement well described, are the public
and private parties clearly identified?
Whose costs and benefits are going to be considered in the economic welfare calculation?
Are all the potentially affected parties considered?
Has current demand for services been analysed?
Has future demand for services been forecasted?
Are the demand forecasting method and assumptions appropriate?
Technical feasibility Does the application dossier contain sufficient evidence of the project’s feasibility (from a
and environmental technical point of view)?
sustainability Has the applicant demonstrated that other alternative feasible options have been adequately
considered?
On what criteria was the project optimal option selected? Are these criteria appropriate for the
type of project?
Is cost of measures taken for correcting negative environmental impacts included in the cash
\64
flows considered in the CBA?
Is the technical design appropriate to the achievement of the objectives?
Is capacity utilisation rate in line with demand expectations?
Are the project cost estimates (investment and O&M) adequately explained and sufficiently
disaggregated to allow for their assessment?
Have depreciation, reserves, and other accounting items which do not correspond to actual
cash flows been excluded from the analysis?
Has the residual value of the investment been properly calculated and included in the
analysis?
In the case of using current prices, has a nominal financial discount rate been adopted?
Has VAT, if recoverable by the beneficiary, been excluded from the analysis?
Have transfers and subsides been excluded from the computation of the project revenues?
If tariffs are levied from users, how has the polluter-pays-principle been applied, what is their
Financial analysis cost recovery level in the short, medium and long-term?
If an affordability cap is applied to tariffs, has an affordability analysis been carried out?
Is the financial sustainability analysed at project and, where appropriate, operator level?
If the project is not financially sustainable by itself (produces negative cash-flows at some
point), is it explained how the required funds will be ensured?
Have the main financial performance indicators been calculated (FNPV(C), FRR(C),
FNPV(K), FRR(K)) considering the right cash-flow categories?
If private partners are involved, do they earn normal profits as compared with financial
benchmarks in the sector?
In the case of market distortions, have shadow prices been used to better reflect the social
opportunity cost of the resources consumed?
Is the Standard Conversion Factor calculated and applied to all minor non-traded items?
In the case of major non-traded items, have sector-specific conversion factors been applied?
Has the appropriate shadow wage been chosen for the labour market?
If cash-flows present fiscal requirements, have market prices been corrected?
Have non-market impacts been considered for the evaluation of the project economic
Economic analysis performance?
Have externalities been included in the analysis, including climate change effects?
Are the unit values for quantification of economic benefits and externalities and their real
growth over time adequately presented/explained?
Have the main economic performance indicators been calculated (ENPV, ERR and B/C ratio)
considering the right categories of cost and benefits? Is there any risk of benefit double
counting?
Is the economic net present value positive? If not, are there important non-monetised benefits
to be considered?
Is the sensitivity analysis carried out variable by variable and possibly using switching values?
Has the scenario analysis been carried out?
What is the proposed risk prevention and mitigation strategy?
Has a full risk prevention matrix been built?
Risk assessment
Have risk mitigation or prevention measures been identified?
If the project appears to be still exposed to risk, has a probabilistic risk analysis been carried
out?
What is the overall assessment about the project risk?
\65
3. Transport
3.1 Introduction
The EU transport infrastructure strategy, as defined in the TEN-T75 Guidelines, focuses on improving
transport infrastructure quality through new investment and the efficient use of pre-existing
infrastructure in order to improve accessibility, mobility and safety, as well as to match transport
demand. Related investments priorities are defined under the thematic objective 7 ʻPromoting
sustainable transport and removing bottlenecks in key network infrastructuresʼ, which focuses on:
supporting a multimodal Single European Transport Area by investing in the trans-European
transport network (TEN-T) network (investment priority 7a);
enhancing regional mobility through connecting secondary and tertiary nodes to TEN-T
infrastructure (7b);
developing and improving environmentally-friendly and low-carbon transport systems,
including inland-waterways and maritime transport, ports and multimodal links, and
promoting sustainable regional and local mobility76 (7c);
developing and rehabilitating a comprehensive, high quality and interoperable railway system
(7d).
According to the Common Strategic Framework, actions financed under the ERDF and the Cohesion
Fund in the transport field shall be planned in close cooperation with the Connecting Europe Facility
(CEF), which is a directly managed fund created in 2012 for accelerating cross-border investments in
the field of trans-European networks, maximising the synergies between transport, energy and
telecommunications policies, and ensuring funding from both the public and private sectors.
The CEF will concentrate on projects with a high EU added value, in particular in the core network for
cross-border infrastructure (as pre-identified in the Annex of the CEF Regulation) and for railway,
while the Cohesion Fund and the ERDF will concentrate on high EU added-value projects to remove
bottlenecks in transport networks by supporting TEN-T infrastructure, for both the core and the
comprehensive network.
In addition, transport investments must be closely linked to the needs identified in national transport
plans (cf. thematic ex-ante conditionality 7.1), based on a rigorous assessment of transport demand
(both for passengers and for freight). These plans should identify missing links and bottlenecks and
should set out a realistic and mature pipeline for projects envisaged for support from the ERDF and
Cohesion Fund. The aim is to ensure a better interoperable integration between transport modes and a
stronger focus towards the Trans-European Networks in 2020 and beyond.
As illustrated in the box below, EU policies and interventions have mainly focused on: development of
the infrastructure network; regulation and competition among and between modes intended to open
up the national markets and make transport services more competitive and interoperable at the EU
level; setting prices correctly (including charging for infrastructure use and internalisation of external
costs); and providing safe infrastructure and/or improving safety conditions.
75 In order to establish a single, multimodal network that integrates land, sea and air transport throughout the Union to facilitate the
consolidation of the common market, in 1996 the EU policymakers defined the Trans-European Transport Network (TEN-T), which has been
successively adapted and today plays a central role in the attainment of the Europe 2020 Strategy objectives.
76 Any project that modifies the hydromorphological characteristics of a water body causing deterioration of the status has to be assessed in
line with Art. 4.7 WFD.
\66
THE EU POLICY FRAMEWORK
Strategies
White Paper on Transport (March 2011)
Proposal from the Commission for a European Parliament and Council regulation on Union guidelines for the
development of the trans-European transport network (COM/2011/0650)
Roadmap to a Single European Transport Area -Towards a competitive and resource efficient transport system -
White Paper (COM/2011/144)
Keep Europe moving - Sustainable mobility for our continent, Mid-term review of the European Commission’s
2001 Transport - White Paper (COM/2006/314)
European transport policy for 2010: Time to decide – White Paper ( COM/2001/370)
Roadmap to a Single European Transport Area: Facts and figures
Urban public transport policy
Connecting Europe Facility
Trans European Network - Transport (TEN-T)
European Commission 2014, Building the Transport Core Network: Core Network Corridors and Connecting
Europe Facility, COM(2013) 940 final
European Commission, 2013, The Fourth Railway Package – Completing the Single European Railway Area to
Foster European Competitiveness and Growth
European Commission, 2011, Regulation of the European Parliament and the Council establishing the Connecting
Europe facility
TEN-T: A policy review – ʻTowards a better integrated trans-European transport network at the service of the
common transport policyʼ, Green Paper
Decision 661/2010/EU of the European Parliament and the Council of 7 July 2010 on Union guidelines for the
development of the trans-European transport network
Trans-European Networks: Towards an integrated approach, COM/2007/0135
Competition and pricing
European Commission, 2007, Regulation of the European Parliament and the Council N. 1370 on public
passenger transport services by rail and by road
Road Tolling Directive 2004/52/EC and Decision 2009/750/EC
Directive 2006/38/EC ‘Euro-vignette’ amending Directive 1999/62/EC on the charging of heavy goods vehicles
for the use of certain infrastructures (see following box)
Directive 2004/49/EC amending Directive 2001/14/EC on the allocation of railway infrastructure capacity and
the levying of charges for the use of railway infrastructure and safety certification
Directive 2011/76/EU amending Directive 1999/62/EC on the charging of heavy goods vehicles for the use of
certain infrastructures
Rail Interoperability
Directive 2008/57/EC of the European Parliament and the Council of 17 June 2008 on the interoperability of the
rail system within the Community: OJ L 191/1 of 18 July 2008
Commission Decision of 25 January 2012 on the technical specification for interoperability relating to the
control-command and signalling subsystems of the trans-European rail system
\67
3.2 Description of the context
The objectives of a transport project, namely the specific functions the infrastructure has to perform,
must be consistent with the territorial context of the region or country (or cross-border area) where
the project is built. As a minimum, the following information should be presented in order to outline
the baseline elements.
Table 3.1 Presentation of the context. Transport sector
Assumptions
- National and regional GDP growth
- Demographic change
Socio-economic - Industrial and logistics structure and developments (freight transport)
trend - Forecasts in employment
- Forecast in indices of specific economic sectors in which the area covered by the infrastructure
is suited (e.g. value added growth in tourism)
- Reference to EU directives and sector policy documents
- Reference to the long-term national, regional and local planning documents and strategies,
Political, including, for example, the General Transport Development Plan and the Public Transport
Institutional and
Development Plan
Regulatory
- Reference to the priority axis and the intervention areas of the OP
- Any pre-existing planning authorisations and decisions
- Detailed information about the existing transport infrastructure in the area
- Information about competition from alternative transport modes
- Planned and/or recently executed investments that may affect the project performance
Existing service - Information about historic and present traffic patterns
conditions - Statistics in motorisation, mobility and accessibility of the area
- Technical characteristics of the service currently provided
- Service quality, frequency and safety
- Infrastructure capacity
Source: Authors
3.3 Definition of objectives
The next step is to clearly state the main objectives of the transport project. These are generally
related to the improvement in travel conditions for goods and passengers both inside the impact area
and to and from the impact area (accessibility), as well as improvements in both the quality of the
environment and the wellbeing of the population served. In more detail, projects will typically deal
with the following objectives:
reduction of congestion within a network, link or node by resolving capacity constraints;
improvement of the capacity and/or performance of a network, link or node by increasing
travel speeds and by reducing operating costs and accidents;
improvement of the reliability and safety of a network, link or node;
minimisation of GHG emissions, pollution and limitation of the environmental impact
(important examples are projects supporting the shift from individual, i.e. cars, to collective
transport);
adjustment to EU standards and completion of missing links or poorly linked networks:
transport networks have often been created on a national and/or regional basis, which may no
longer meet the transport requirements of the single market (this is mainly the case with
railways);
improvement of accessibility in peripheral areas or regions.
Objectives must be aligned with the priorities identified in the OP and Transport Master Plan/Strategy
in the context of ex ante conditionality. When feasible, they should be quantified and targeted with the
\68
use of indicators, logically linked to the project benefits (see section 3.7). For example, indicators
including expected traffic volumes, travel times, average speeds, etc., can be used to show the link
between the materialisation of the project benefits and the achievement of the stated objectives.
3.4 Project identification
A good starting point for briefly, but clearly, identifying the infrastructure is to state its functions,
which should be coherent with the investment objectives. This should be followed by a description of
the project typology, that is whether it is a completely new facility, or a link to a larger infrastructure,
or an extension/upgrade of a pre-existing one77 (see box). Finally, a detailed list of the physical
realisations must be included.
INVESTMENT TYPOLOGIES
New infrastructures to satisfy increasing transport demand
Completion of existing networks (missing links)
Extension/renovation of existing infrastructures
Investment in safety measures on existing links or networks
Improved use of the existing networks (i.e. better use of under-utilised network capacity)
Improvement in inter-modality (e.g. interchange nodes)
Improvement in networks interoperability
Improvement in the management of the infrastructure investment
The identification of the project as a self-sufficient unit of analysis is usually a challenging issue in the
transport sector. This is because most transport projects belong to a wider network and any
investment decisions and implementation are not isolated, but are part of a larger system of public
interventions, as well as the need to be physically integrated with other complementary
infrastructures. In project identification, the basic principle is that its scope must always be a stand-
alone socio-economic and technical unit: i.e. it should generally be functional and independently useful
from a transport perspective without depending on the construction of other projects (which may
however provide synergies). That considered, the following basic rules can be applied (see also section
2.6):
when the project consists of realising a given section, sub-portion or phase of a well identified
transport investment, the CBA (and the supporting feasibility study) should be focused on the
entire investment, regardless of the object of the EDRF/Cohesion Fund assistance;
when the project contributes to implementing a larger investment strategy or plan,
encompassing a set of interventions all aimed at achieving the same priority, each intervention
should undergo a CBA. For example, a project may consist of the completion of a trans-national
link under the TEN–T. Here, the economic appraisal should not focus on the entire link, but
only on the project’s section where different options are available.
77 For example, the construction of a third lane for a two-lane motorway, the laying of a second track or the electrification and automation of
an existing rail line.
\69
3.5 Forecasting traffic volume
3.5.1 Factors influencing demand analysis
When developing a demand analysis for transport investments, particular attention should be paid to
the sensitivity of traffic to some critical variables such as:
demographic changes, including, amongst others, the number of people split into age
structure, level of education and number of people of productive and non-productive age;
socio-economic changes, including, amongst others, GDP level in analysed area, incomes,
level of unemployment, economic structure of regions being served currently or in the future
by the transport infrastructure;
industrial and logistics structure and developments: location of concentrated industrial
activities, natural resources, main transport hubs (ports and airports), logistics structure, and
expected developments in supply chain organisation (clustering, unitisation, change in
distribution patterns);
elasticity with respect to quality, time and price (see box): travel demand characteristics,
structure and elasticity are particularly important in those projects related to charged
infrastructures, since the expected traffic volumes are determined by fare levels and the
transport conditions;
capacity constraints on competing modes and strategies in place, for example in terms of
investments foreseen. This point is particularly relevant for long term investments: in the time
span required to complete the intervention, the traffic that may be potentially acquired by the
new infrastructure may shift to other modes and, if so, then it may be difficult to move it back.
spatial changes leading to changes in the distribution of traffic potential;
change of traffic management policies, e.g. existence of constraints in using the car in
determined areas (this is particularly the case of urban public transport) or establishment of
taxes or subsidies for competing modes;
technological changes impacting the cost structure for the project and its alternatives
through changes in e.g. fuel efficiency, fleet composition or productivity.
Given the uncertainty of the future trends of these variables, it is generally recommended to develop,
as a minimum, three traffic scenarios (high, most likely and low), which should further feed into risk
analysis. These should be based on different developments of both exogenous (e.g. GDP growth) and
endogenous (e.g. pricing policy) variables. Demand forecasting should be completed for the scenario
without-the-project, and for each project option (see below).
PRICING POLICIES
Fares, tolls and other pricing policies will influence the expected volume of demand and the distribution of
demand across transport modes. It is therefore important, whenever a different pricing hypothesis is introduced,
to reconsider the demand estimates and allocate the correct traffic volumes to each mode. With regard to pricing
criteria, it is important to distinguish between:
- fares which maximise the proceeds for the managers/constructors of infrastructures: these kinds of fares
maximise the capacity for self-financing;
- efficiency fares: these take into consideration the social surplus and also consider the external costs (congestion
as well as the environmental and safety costs).
Efficient pricing should, in principle, be based on social marginal costs and requires the ‘internalisation of
external costs’ (polluter pays principle), including congestion and environment costs. Social efficiency requires
that users pay both the marginal private or internal and external costs that they impose on society. An efficient
structure of charges confronts users with the marginal social costs of their decisions.
\70
3.5.2 Hypotheses, methods and input
In order to develop traffic forecasting, some justified specific assumptions should be adopted with
regard to:
the project’s impact area, in order to limit the traffic study and the related economic impacts.
It is important to identify the demand without the project and the impact of the new
infrastructure, as well as identify other transport modes potentially involved;
the degree of complementarity and competition among transport modes. In particular,
competing modes and alternative routes, fares and costs for users, pricing and regulation
policies, congestion and capacity constraints and expected new investments should be
assessed;
the deviations from past trends, including changes in tax regime, energy prices or toll
collection policy;
the relative sensitivity of demand patterns (such as modal share or volume of traffic) to
changes in the transport supply.
Traffic modelling78 is usually required for demand analysis, which enables the simulation of traffic
distribution on the network thereby providing indication of how trips will respond, over time, to
changes in transport supply and demand. Trip developments may be the consequence of changes in
the demand for transport and/or in the transport network itself (i.e. the building of new transport
infrastructure and/or provision of operated services).
Different models exist, ranging from the development of relatively simple spreadsheet models79
(which are generally bespoke and constructed by users for a particular calculation) to network models
that describe a defined impact area and are generally more complex since they can involve ʻfeedback
loopsʼ, where the resulting state of the network can impact on user decisions. These complex models
incorporate significant volumes of information on the demand structure, the transport network and its
dynamics (e.g. timetables, interconnections, etc.) to describe large numbers of transport movements
over a specified period. Data is typically coded in the form of attributes for each transport link in the
network, including speed, quality, and the travel modes that use each link.
The choice of the appropriate model depends on a large number of factors, including the nature of the
options to be tested, geographical location, scope, size and likely key impacts so that is not liable to
adopt a ‘one size fits all’ approach to developing transport models in order to assess this range of
issues. In general, the larger the project framework complexity, the higher the need for more
sophisticated and complex models. Complex transport modelling is considered compulsory in large
projects, e.g. if its size can significantly influence other traffic services or regional transport pattern.
Although there is currently no detailed guidance at EU level for the development and application of
transport models, basic principles and features of modelling can be derived from national guidance,
which the project promoter should always refer to. These include:
traffic modelling is used to predict the travel choice made by users travelling through the
network, and to load the resulting trip movements to the modelled network based on a
selection of the most likely routing for each trip. The model then describes the loaded
transport network after this process has been completed;
the state of the transport network in future years on the basis of growth in travel demand,
committed network changes and changes in socio-economic data can also be defined. Future
years usually coincide at least with the opening year and a distant forecast year which is used
for assessment of long-term capacity needs or is the end year of economic evaluation;
78 A Transport Model is a computer-based representation of the movement of people and goods (trips) around a transport network within a
defined ‘study area’ possessing certain socio-economic and land-use characteristics.
79 For example, single junction, section or corridors models.
\71
many transport models require substantial input data derived from standard statistics and
special surveys for building a model of trips, a model of the network and for understanding
current traffic flows and demand structure for the purpose of model calibration. This is
essential for the model to be sufficiently accurate and have credibility for planning and
decision making;
the output from the transport model is used to design adequate sizing and features of the
investment, to verify the appropriateness of planned infrastructure capacity, and provides
quantitative information that informs the scheme design, the CBA and the EIA.
Whatever model and modelling process is adopted, all hypotheses and assumptions applied to
estimated existing and future demand should be made explicit by the project promoter. Although the
analysis of the input data for traffic modelling is not a task of the CBA, nevertheless, there should be
the source should be given of all quoted demographic, spatial and economic data.
3.5.3 Outputs of the traffic forecast
Taking into account the requirements for economic analysis, traffic forecast outputs are developed for
passenger and/or cargo traffic. Outputs shall include all information necessary for further technical
analyses as well as financial and economic analyses. Although each subsector has its own indicators of
traffic forecasts, the following demand parameters are usually collected to feed the CBA model:
number of vehicles (cars, trains, buses, airplanes, ships, etc.) in absolute value, per unit of time
(e.g. Annual Average Daily Traffic (AADT), trains per day, etc.) and/or per average trip length
(e.g. vehicles-km, trains-km, etc.);
number of vehicles broken down by category, speed class and road category;
number of passengers, passenger-hours and passenger-km80;
cargo traffic in tons, ton-hour and ton-km;
travel times and other network performance indicators.
Types of traffic response
Traffic types can be divided according to their behavioural response to a project. This qualification will
become relevant when it comes to the assessment of the socio-economic impacts of the project. The
classification proposed in this guide is as follows81:
existing traffic: current traffic on the network of reference (new projects) or on the
infrastructure to be upgraded/reconstructed;
diverted traffic: traffic which is attracted to the project from other routes or transport modes;
generated/induced traffic: additional traffic flows that result from a transportation
infrastructure improvement due to new users attracted by better conditions of transport82.
Depending on the traffic system perspective, and on the actual availability of data on generalised costs
80 Passenger-kilometre is the distance travelled by passengers on transit vehicles, airplanes, ships, trains, buses, etc.; It is determined by
multiplying the number of transported passengers by the average length of their trips. The same concept applies to freight for tons-km.
81 Please note that transport users can be categorised in a number of ways and several categories and ʻlabelsʼ exist in the academic literature
and studies. This is partly due to inconsistency in terms use across authors, and partly because the nature of the project may affect the extent
to which transport demand needs to be aggregated in the appraisal, which has probably contributed to blurring the picture. For instance, the
category ʻinduced trafficʼ is sometimes used as a synonym for ʻgenerated trafficʼ. In others cases, they are used as separate concepts, with the
former defined as the additional traffic that has been induced by the project (through mode changes, destination changes, trip re-timing, trip
frequency changes or new trips associated with different land uses) and the latter as the additional traffic induced within the entire multi-
modal transport system.
82 In the first instance, generated/induced traffic could be estimated on the basis of demand elasticity with respect to generalised transport
costs (time, tariffs, comfort). Nevertheless, since traffic is dependent upon the spatial distribution of economic activities and households, the
recommendation for a correct estimate is to analyse the changes in accessibility to the area induced by the project. This will normally require
the use of integrated regional development-transport models. In the absence of these instruments, it is necessary to estimate the generated
traffic with great caution and to carry out a sensitivity or risk analysis of this traffic component.
\72
from the traffic model, the assessment of socio-economic benefits for each of these categories can be
performed differently (see section 3.8 below).83
Also, for the purpose of the economic assessment, the traffic surveys should also provide information
on the share of trips by travel purpose, for instance business, commuting and leisure trips. An
additional distinction by short and long distance trips can be relevant for road and railways trips.
3.6 Option analysis
The project should be identified after the assessment of all promising strategic and technical
alternatives on the basis of physical circumstances and available technologies. The main potential for
distorting the evaluation is the risk of neglecting relevant alternatives, in particular low-cost solutions,
such as managing and pricing solutions, infrastructure interventions that are considered as not
ʻdecisiveʼ by designers and promoters, etc.
Possible design options in transport include: i) mode; ii) location/route; iii) alignment, iv) technical
solutions; v) interchanges; etc. Different options may have different demand, costs and impacts.
Options might include synergies in co-deployment of transport and NGA infrastructure, in line with the
Directive 2014/61/EU, in view of smartening the transport systems, improving efficiency in the use of
public funds, and significantly increasing the socio-economic impact of projects.
For option selection, the suggested approach is generally to use Multi-Criteria Analysis for shortlisting
the alternatives, then CBA to compare the results of the shortlisted options and consequently select
the most promising one. It is worth stressing that option analysis should be developed standardly in
concept stage feasibility studies prior to design and funding application preparation. In this case, the
promoter should properly describe the options analysis in the feasibility study, in order to
demonstrate that the available options have been subject to a robust assessment and that the selected
option was the best from a socio-economic perspective. Otherwise, if the appropriate analysis was not
formerly completed, it would then form part of the feasibility study, which is an annex to the project
application.
Finally, option analysis can also be used later to review the efficiency of previous designs, especially
when socio-economic circumstances have changed. This can lead to project re-design.
3.7 Financial analysis
3.7.1 Investment costs
Investment costs disaggregation is project-specific, although the transport sub-sectors are usually
characterised by common cost categories for both initial investment and renewals84. For an illustrative
list of investment outlays in the road and railway sectors, see the case studies at the end of the chapter.
As general remarks valid for any transport investment, the following can be highlighted:
estimates must be based on appropriate benchmarks with projects of comparable
characteristics, based on best available technologies, etc.;
it is recommended to present both the total cost of the project and the unit value (e.g. cost per
km, cost per unit of rolling stock, etc.);
costly engineering structures (tunnels, bridges, overpasses, etc.) should always be shown
separately in a cost statement to allow for benchmarking;
it is necessary to ensure that the project will include all the works required for its functioning
(for example, links to the existing networks, technological plants, stations with related
83 An exemplification of such distinction between approaches can be found in WB Transport Note No. TRN-11. Available at:
http://siteresources.worldbank.org/INTTRANSPORT/Resources/336291-1227561426235/5611053-1231943010251/trn-11EENote2.pdf
84 For example, in the case of railways investment costs are usually broken down into the following main items: preparation works; track
works; engineering structures; branches; environment protection; other.
\73
services, urban renewal works adjacent to public transport investments, etc.);
cost of land85 and costs for environmental protection, including e.g. noise barriers and other
noise protection, drainage, greenery, animal passages, etc., and/or for the integration of the
works in the territory (e.g. for the preservation of the landscape integrity, etc.) are usually
main items to be included in the investment costs.
3.7.2 Operation and Maintenance (O&M) costs
In the transport sector, O&M costs can be generally grouped into the following categories:
infrastructure operations, e.g. repairs, current maintenance, materials, energy, Traffic
Management System;
services operations, e.g. staff cost, traffic management expenses, energy consumption,
materials, consumables, rolling stocks maintenance, insurance, etc.;
services management, e.g. services management itself, fare/tolls collection, company
overheads, buildings, administration, etc.
As for the timing of the expenditure, O&M costs should cover (and is usually distinguished in):
routine maintenance: yearly work required to keep the infrastructure technically safe and
ready for day to day operation as well as to prevent deterioration of the infrastructure assets;
periodic maintenance: all activities intended to restore the original condition of the
infrastructure.
In financial analysis, O&M costs should be estimated in both the with and without project scenarios.
Significant difference may, however, exist between the two scenarios, especially when maintenance
and repair have been neglected in the past. For the estimation of O&M costs in the counterfactual
scenario, in particular, periodic and routine maintenance costs should correspond to reaching the
target without the project standard of operations with minimal investments. All assumptions taken
should be carefully documented in the project dossier.
3.7.3 Revenue projections
Financial inflows will be represented by the proceeds from the charges applied to users for the access
to the infrastructure or the sale of transport services, or related to sale or rent of land or buildings. The
estimate for the proceeds must be consistent with the demand elasticity and trends of explanatory
variables and, in a more general sense, with traffic modelling output.
The estimation of revenues should be based on the following elements:
traffic volume forecast (changes of passenger and cargo traffic);
projection of changes in charge system and pricing policy;
traffic forecast for each projection of charge system;
subsidy/compensation projection.
An indicative list of typical revenues to be considered for calculation of the financial profitability is
provided in the table below.
85 Particular attention must be paid here because land values also depend on the countryʼs legislation (e.g. on reuse or restoration of land).
While the purchase price of land must be used in financial analysis, the foregone use value of land should be used in economic analysis.
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Table 3.2 Typical sources of revenue by transport mode
Revenues from transport activities Revenues from non-transport
activities
Value of scrap material
Road Tolls and/or other users charges Rental of service stations
Advertisement on service stations
Access charges to railway line (in the case of Advertisement on trains and/or in railway
Railway infrastructure projects) stations
Tickets (in the case of rolling stock projects) Commercial premises in railway stations
Commercial premises in stations
Urban transport Tickets and subscriptions Advertisement on vehicles and/or on
stations or bus stops
Commercial services
Take-off or landing charge Real estate rental
Passenger charge Food services
Airports
Parking charge Transport services
Cargo charge Advertising services
Car parks
Commercial premises
Seaports and inland Basin, berth dues, etc.
Logistics
waterways Tariff for inland cargo ship
Advertising on vessels
Access charges to railway line Commercial premises
Intermodal facilities
Tariff/fee for cargo storage and transhipment Logistics
Source: Authors
If the situation on a given transport service is such that revenues from transport and non-transport
activities do not fully cover the cost of operation, the gap must be filled with other sources to avoid the
closure of the service. This usually implies that an operating subsidy or compensation is provided from
public funds. Under such circumstances, this type of inflow must be separated from the overall
revenue projection because, as highlighted in chapter 2, they do not concur for the calculation of the
EU contribution and the financial performance indicators (but they count for sustainability).
As a result of the revenue analysis, the projection of the total revenues for the entire time horizon of
the analysis should be prepared in both with and without-the-project scenarios.
PERSPECTIVE OF THE ANALYSIS AND REVENUES
As mentioned in chapter 2, it is recommended to carry out the financial analysis at a consolidated (owner +
operator) level. This is particularly feasible when there is only one operator, which provides the transport
service on behalf of the owner, usually by means of a concession contract. This is often the case of road and
urban transport services.
In other cases, on the contrary, the consolidation of the analysis cannot be feasible. In liberalised markets, the
number of operators can be very large, e.g. in airports but, to some extent, also in seaports and railways. Given
the high number of data that would be required, together with legal and information protection issues, the
financial analysis of these investments is more frequently carried out from the viewpoint of the infrastructure
owner. In such a case, the revenues to be accounted for in the CBA are those originating from the operators or
from third parties (e.g. tenants of commercial spaces, etc.) to the owner for the use of the infrastructure (usually
access charges, see below). Conversely, in the case of projects implemented by operators (e.g. rolling stock
renovation in urban transport), the revenues are those originating from the sale of the service to final users, as
well as any other operating revenues accruing to the operator for the use of the infrastructure by third parties.
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3.8 Economic analysis
In transport projects the main direct benefits are measured by the change of the following measurable.
The consumer surplus, defined as the excess of users’ willingness-to-pay over the prevailing
generalised cost of transport for a specific trip. The generalised cost of transport expresses the
overall inconvenience to the user of travelling between a particular origin (i) and destination
(j) using a specific mode of transport. In practice, it is usually computed as the sum of
monetary costs borne (e.g. tariff, toll, fuel, etc.) plus the value of the travel time (and/or travel
time equivalents, such as the inconvenience of long intervals) calculated in equivalent
monetary units. Any reduction of the generalised cost of transport for the movement of goods
and people determines an increase in the consumer surplus. The main items to be considered
for the estimation of the consumer surplus are:
o fares paid by users;
o travel time;
o road users Vehicle Operating Costs.
The producer surplus, defined as the revenues accrued by the producer (i.e. owner and
operators together) minus the costs borne. The change in the producer surplus is calculated as
the difference between the change in the producer revenue (e.g. rail ticket income increase)
less the change in the producer costs (e.g. train operating costs increase). This might be
particularly relevant for public transport projects or toll road projects, especially if the project
is expected to feature significant traffic (generated or induced) or a substantial change in fares.
The main items to be considered for the estimation of the consumer surplus are:
o fares paid by users (and received by the producer); and
o producer operating costs.
It must be noted that fares paid by users for the use of the infrastructure appear in the economic
analysis as a cost to the user in the estimation of the consumer surplus and as a revenue to the
producer in the estimation of the producer surplus. Thus, for existing traffic (see section 5.5.3 above
for definitions), this implies that fares are always cancelled out in the analysis. However, this is never
the case for the calculation of benefits to generated/induced traffic, which are generally approximated
via the Rule of Half (see box), and would also not apply in the cases where the benefits to the diverted
traffic are also estimated via the Rule of Half (see section 3.8.1). In such cases, the producer revenues
and associated user charge costs will not be cancelled out.86
This implies that the economic analysis of transport projects can be structured differently depending
on two main situations:
in cases where the project is not expected to change traffic volumes, there is no need to
estimate the changes of the consumer and producer surplus because the fares paid by users
will always be cancelled out. A simplified approach can therefore be adopted and the analysis
will just rely on the estimation of the net effects on users, in terms of travel time savings and,
for road projects, Vehicle Operating Cost savings87. The case study on road investment, at the
end of this chapter, provides an example of this approach;
in cases where the project is expected to change traffic volumes or when transport pricing
strategies are introduced or expected to be changed, the fares paid by users will not be
86 See e.g.: HEATCO D.5 (p.49): ʻSometimes operator revenues are not included in the appraisal since it is argued that this is only a transfer
from users to the operator which is not relevant for the economy as a whole. However, this reasoning is only valid for the existing traffic, but
not for the newly generated traffic. For the newly generated traffic the additional revenues of the operator are a measure of the additional
benefits of the additional traffic and must therefore be included in the evaluationʼ, or World Bank Transport Note No. TRN-11/2005 (p.7):
ʻUser benefits/disbenefits associated with money costs (e.g. road tolls and fares), when calculated under the RoH and variable demand, do
not net out with changes in the fare revenue element of the producer surplus calculation (i.e. they are not transfer payments)ʼ.
87 In some cases, the analysis can also be enriched with the evaluation of the change in carriersʼ operating costs, as illustrated in section 5.8.3.
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cancelled out. The analysis will therefore consist of estimating the net impacts on both the
consumer and producer surplus. This implies that fares need to be separately accounted for, as
well as all the changes in the producer operating costs (if not already captured in the financial
analysis - as it happens when the analysis is not consolidated). The case study on rail
investment provides an example of this approach.
In addition, any transport project may generate relevant non-market impacts on safety and the
environment that always need to be evaluated.
Table 3.3 reviews the main effects and the relative evaluation methods to be considered for the
economic appraisal of transport infrastructure projects. Fares are not included since they have already
been discussed in section 3.7.3.
Table 3.3 Typical economic benefits (costs) of transport project
Effect Valuation method
- Stated preferences
Travel time savings - Revealed preferences (multi-purpose household/business surveys)
- Cost saving approach
Vehicle Operating Costs savings - Market value
Operating costs of carriers - Market value
- Stated preferences
Accidents savings - Revealed preferences (hedonic wage method)
- Human capital approach
- WTP//WTA compensation
Variation in noise emissions
- Hedonic price method
Variation in air pollution - Shadow price of air pollutants
Variation in GHG emissions - Shadow price of GHG emissions
Source: Authors
In what follows, the main information needed and the practical instructions to evaluate the benefits
(costs) illustrated above are presented. It is worth noting that economic effects other than those listed
in table 5.3 can be generated. This pertains mainly to the wider impact on regional development,
which is frequently associated with large transport investments. For instance, the improvement of an
airport can influence socio-economic growth by activating the job market, developing local businesses,
increasing community activity and boosting tourism.
As previously mentioned, the approach of the Guide is to exclude indirect and wider impacts from the
CBA (see section 2.9.11). It is recommended, however, to provide a qualitative description of these
wider impacts on secondary markets, public funds, employment, GDP, etc. in order to better explain
the contribution of the project to the EU regional policy goals.
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THE RULE OF HALF
The Rule of Half (RoH) relies on the consideration that, without the project, non-travelling users Willingness To
Pay (WTP) is lower than the (prior) generalised cost of transport. After project implementation the (new)
generalised cost of transport is lowered so that some previously non-travelling people decide to travel.
Although the absolute WTP is not known, the average change in consumer surplus of the generated traffic can be
estimated as half of the difference between the original and the new generalised costs of transport on the
improved mode for a given origin-destination (O-D) relation. It is half because a linear demand/cost graph is
assumed where new users are spread evenly between two extremes: those requiring marginal motivation to
start travelling (their WTP is already on the cusp between travelling and not travelling, so they get the full
benefit of the change in generalised costs) and those requiring the full benefit of the change to the transport
system to be motivated to travel (they get marginal net benefit). The RoH can be therefore expressed by the
following formula:
gc = p+z+vτ
where: p is the amount paid for the trip by the user (tariff, toll); z is the perceived operating costs for road
vehicles (for public transport is equal to zero);τ is the total time for the trip; v in the unit value of travel time.
Total consumer’s surplus (CS0) for a particular i and j in the Business As Usual (BAU) scenario is shown
diagrammatically in the first figure. It is represented by the area beneath the demand curve and above the
equilibrium generalised cost, area CS0.
User benefit = Consumer’s surplusij1- Consumer’s surplusij0
where: 1 is the do-something scenario and 0 is the BAU scenario.
Supply, S ij0
CS 0
GC 0
Demand, Dij=f(GC ij)
0 T0 Trips, Tij
If there is an improvement in supply conditions the consumer’s surplus will increase by an amount of ∆CS, due to
a reduction in equilibrium generalised cost and the total user benefit (for existing and new users) can be
approximated by the following function, known as the rule of a half:
GC 0
1
ΔCS D(GC) dGC Rule of one Half ( RoH) (GC 0 GC1)(T 0 T 1)
GC1 2
For the generated demand only (i.e. for new users), the benefits may be approximated by the following formula :
∆CS(generated) ≈ 1/2*(GC0-GC1)*(T1-T0)’
In the case of a totally new infrastructure, the RoH will not be directly applicable and the measurement of the
benefits depends on the nature of the new mode, its placement in the mode hierarchy and transport network,
and will often need to be derived from the users’ WTP or calculated with other approaches. For example see
various integration and other methods suggested in World Bank Transport Note No. TRN-11 2005.
Source: Authors
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3.8.1 Travel time
Travel time saving is one of the most significant benefits that can arise from the construction of new,
or improvement of, existing transport infrastructure.
Passengers traffic time savings
In carrying out CBA, different methods are possible to value time for passengers, whilst a distinction is
usually made between the estimation of work and non-work travel time (including commuting).
The first method is to carry out specific empirical research and/or surveys in that country to estimate
both work and non-work travel time. The approach consists of interviewing individuals using the
stated preference method or conducting multi-purpose household/business surveys using the
revealed preference method and then to estimate a discrete choice model on these data.
As a second option, value of time can be estimated adopting the cost saving approach88. The
underlying logic is that time spent for work-related trips is a cost to the employer, who could have
used the employee in an alternative productive way. The recommended process for valuing work time
with the cost savings approach is as below.
Establishing wage rates for a given country or region: the gross hourly labour cost (Euro per
hour) must be derived from observed (or, in absence, from average national) wage rates. The
main data source should be the national statistical office;
Adjustment to reflect additional employee related costs: this would include paid holidays;
employment taxes; other compulsory contributions (e.g. employer pension contributions) and
an allowance for overheads required to keep someone employed. Social security payments and
overheads paid by the employer shall therefore be computed and added to the estimated
hourly labour cost.
The cost saving method is a simple approach to estimate a single value of work-time in a given country
or region. This can, however, be enriched with further considerations and analysis, if necessary and
feasible, as illustrated in the box below.
The preferred source from where to obtain value(s) of time at country level should be official national
data, based on local research, provided that the methodology used is sound, robust and follows the
general prescriptions illustrated above.89
For non-work travel time, the economic value of time savings is given by the difference between the
marginal valuation of time associated with travelling and that associated with leisure. The implication
is that there is no theoretical basis for deriving the economic value of non-work trips from the wage
rate; instead the values have to be inferred from behaviour.
In the absence of national data using stated or revealed preference methods, the usual solution to this
problem is to evaluate non-work travel time at a national average rate rather than at the rate the
travellers appear to value their time themselves. In other words, non-work time can be assumed as a
share of the work-related value. The review of the economic literature about value of time in specific
countries suggests that non-working time usually ranges between 25 % and 40 % of the work time.90
88 The cost savings approach is based on classical economic theory of marginal productivity. Any savings in production costs will be met
through an increase in production up until the point that the marginal cost of production once again equals marginal revenue. Reductions in
labour costs (due to shorter journeys) will therefore result in more units of labour being hired to increase production. This will occur up to
the point that the value of an extra unit of labour is equal to the cost of that labour. Thus the cost savings approach suggests that the value of
in-work time savings is the wage rate plus the overhead costs associated with the employment of an extra unit of labour.
89 If, in the coming years, a study on default values of time across countries and other transport values is launched by the EC, EIB or other EU
institutions, these default values should be adopted as a reference.
90 See for example: EIB (2013), The Economic Appraisal of Investment Projects at the EIB and London Economics, (2013), Guidance Manual
for Cost Benefit Analysis (CBAs) Appraisal in Malta. The values proposed within the HEATCO study also suggest similar ratios, ranging from
30 to 42 % of the value of working time.
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FACTORS AFFECTING VALUE OF TIME
- Labour market. The cost savings approach assumes that the gross wage rate in the labour market equals
the marginal value product which the labour yields. However, this is not the case whenever distortions of the
labour market exist. Thus, adjustments to reflect the level of unemployment in the country/region can be
applied and the estimated value of time corrected by the shadow wage rate.
- Industrial sector. Under the cost savings approach the economic value of work time savings is the marginal
productivity of the person making the saving; thus different workers will have different time valuations.
Ideally, values of time (VOT) should be developed for each worker classification. However, for the economic
appraisal to operate at this level of disaggregation also requires the demand forecasting to occur at the same
level.
- Mode. Considering the relative qualities and comforts of one mode compared to the other modes (all other
conditions being equivalent), value of travel time can be related to the mode of transport. For example, when
considering average VOT associated with travellers using a certain transport mode, the average value of time
of a bus traveller is usually lower than that of a car traveller. This is a characteristic of the fact that people
with lower income will select slower and cheaper modes of transport (e.g. the bus) than richer people. Thus,
it can be useful to differentiate the value of time by transport modes according to different people income
level groups (where air and high speed rail transport are associated with higher income groups).
- Walking and waiting time. All other things being equal, an individual typically prefers travelling within a
vehicle to spending time walking, waiting or transferring between services. This is borne out from evidence,
as such the value of non-working time saved walking and waiting is higher than time saved whilst travelling
within a vehicle. The exact magnitude of the difference between non-working in-vehicle time and walking
and waiting time is dependent upon national cultures and characteristics. For example, Mackie et al (2003)
have found within the UK walking time savings are valued at double in-vehicle time savings. Such variations
may be explained by a range of cultural, racial and economic factors which drive personal preferences. In
this regard, the World Bank recommends a weight of 1.5 for waiting and access time when national research
is missing.
- Trip distance. The relationship between the value of (non-work) travel time and journey length includes
increasing marginal disutility of travel time with journey length, greater significance of time constraints in
longer distance journeys and differences in the trip purpose mix at long, relative to short distances.
However, in practice it is expected that such situations will be rare so that a single value for travel time is
used irrespective of trip distance. However, in cases where robust local or national specific data indicates
that the values of non-work travel time savings increase with journey distance, data from revealed or stated
travel behaviour can be used to adjust the value of time.
- Travel conditions. The comfort associated with travelling conditions, including the ability of the traveller to
take advantage of the time spent travelling, also affects value of time. For example, VOT savings in congested
car driving situations exhibit higher values than those in uncongested situations. This reflects both the value
of reducing the variability of travel time and the unpleasantness of driving in congested conditions. In urban
public transport, the availability of air conditioning, less crowded busses, etc. are very important to justify
certain expenditures. Another critical aspect is the capacity to work during the trip, which is a key advantage
of rail transport with regard to road and (short haul) air travel and explains the behaviour of many
travellers.
Freight traffic time savings
Reduction in travel times will benefit freight traffic in the following ways:
reduced driver (and any other persons necessarily travelling with the load,) wage costs per
trip;
reduced vehicle operating costs per trip;
improved reliability, i.e. timely delivery of transported goods.
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The valuation of the first benefit follows the same logic of passenger’s traffic so that time savings for
truck drivers (or rail carriers’ crew members) is evaluated with the cost savings approach, whilst the
valuation of the second is discussed below in section 3.8.2.
The last benefit item may arise through a number of mechanisms. If travel and transport times become
more predictable, travellers and agents in freight transport would find it easier to arrive at the
destination at the preferred moment and therefore reduce their safety margins in departure time.
Also, in the case of perishables products, arriving at market earlier and in better condition thereby
attract better prices; and reduced stockholding required through re-structuring of logistics and the
supply sector. Its evaluation and inclusion within the economic benefits of a project is a complex issue
which will require detailed case by case analysis. The following aspects should be taken into account
when deciding whether to include time savings for freight:
such analysis shall be considered only where large step changes in transport infrastructure are
under consideration;
benefit associated with reliability depends very much on the market segment in question as
well as the time value of the commodity91;
owing to specific conditions of the market, logistics chain and general service, benefits from
time savings can be lost elsewhere. For instance, benefit from improved speeds is realised only
if they are not lost in other parts of the logistics chain. The situation and risks should be
analysed and demonstrated in any CBA. Key elements of the logistics chain influencing
potential time losses are the priority given, and capacity available to, the type of freight traffic
on the line, issues at transfer/marshalling/loading/unloading points and the administration at
border points;
care is needed to avoid double counting with vehicle operating costs savings calculations (for
example distance reducing effects on operating costs should not be counted in travel time
savings).
The methodology for the estimation of time value for freight should be based on the capital lock-up
approach. This is based on the concept that value of time related to the movement of goods includes
the interest costs on the capital invested in the goods during the time that the transport takes
(important for high-value goods,), a reduction in the value of perishable goods during transit, but also
the possibility that the production process is disrupted by missing inputs or that customers cannot be
supplied due to lack of stock.
The valuation of the freight’s value of time requires therefore an in-depth analysis of the MS’s
transport and logistic and supply sectors92. In a context of limited resources, it is suggested to refer to
the economic literature where it is possible to find country-specific default values. The literature
shows that reference unit values of time for freight vary significantly across countries: from over 1
EUR/tonne-hour to zero, and from small to large differentiation between commodities. For a review of
the main studies and reports see the Bibliography section.
In this regard, HEATCO provides a framework with reference values for the EU-25. However, these
values, particularly for rail freight, are relatively high as compared to other national-based studies
because they include a full set of potential benefits (e.g. potential carrier company efficiency
improvements). Thus, it is suggested to adopt them as a last resort and, in case, to include a scaling-
down factor (e.g. low escalation elasticity against GDP).
In any case, the methodology used by the project promoter should be clearly presented, with all
underlying assumptions and calculations made explicit. In general, since the values attributed to time
are critical, the recommendation is to clearly report the VOT adopted and to check for consistency. In
particular, MSs are encouraged to develop their own national guidance in order to propose unit
91 The value can differ substantially between commodity types, with perishables and container goods having the highest values and bulk
having the lowest (close to zero).
92 Shippers with own account transport can give information on the value of time that is related to the goods themselves.
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reference VOT for both passengers and freight, provided that the methodology is complaint with the
principles indicated in this guide.
TIME TRENDS IN THE VALUE OF TIME
The real value of work time is directly related to the real wage rate. Thus, it will grow with the projected wage
rate, which is typically assumed to equal the growth in GDP per capita. The economic literature suggests
escalating value of time for future years across the time horizon based on a default inter-temporal elasticity to
GDP per capita growth of 0.7 to 1.0. This elasticity is expected to vary very little across market segments and to
be stable over time. The value of non-work time is not related to the wage rate and as such there is no theoretical
justification for linking it to wage rate growth. However, its value is related to income and any changes in income
will affect that value. Studies in the UK93 and the Netherlands94 have indicated elasticity of value of time with
respect to income of approximately 0.5 to 0.8.
It is generally recommended that value of both work and non-work time be treated as increasing over time in
proportion to GDP per capita, unless there is local evidence to the contrary. For the sake of prudency, it is
however recommended to use the lower elasticity values illustrated above: 0.7 and 0.5 for, respectively,
work and non-work time. If HEATCO values are adopted as a last resort, the use of lower elasticity is
recommended. In line with the use of constant prices, the inflation effect must not be taken into account for
escalation.
Application rules
Once unit VOT are determined, benefit from time savings needs to be calculated separately, for:
Already existing traffic of passengers and goods. For benefit calculation, the following
procedure shall be adopted:
o take the forecast of existing traffic considering number of passengers/goods for each
origin–destination (O-D) pair and for each year across the time horizon;
o take the travel time for each pair (O-D), on the basis of estimated average travel speed, for
both with and without-the-project scenarios;
o split passenger traffic into motivations: work and non-work related trips95;
o calculate the time saving as the difference between travel time in the two scenarios;
o calculate the benefit for each traffic class using the unit values available.
Passengers and goods diverted from other transport modes or routes. When calculating
time costs for passengers diverted from other routes or means of transport, practice across
Europe varies and yet there is no consensus on the correct approach to take. Several methods
can be used reflecting different approaches followed in different countries. The treatment of
diverted traffic would in particular depend on project-specific circumstances, including
whether there is an increase in capacity, the degree of congestion that can occur as the
infrastructure approaches full capacity, and the availability of alternative modes with sufficient
capacity to accommodate traffic that cannot be accommodated in the without-the-project
scenario. In this guide the following, simplified, approach is suggested:
o the Rule of Half should be applied to the travel cost change to the shifted mode whenever
there is poor or no knowledge of the overall average generalised costs on O-D trips of
either the transferred from, or transferred to, mode. Its application requires an estimate of
mode shifted O-D movements;
93 See for example Fowkes, (2007) The design and interpretation of freight stated preference experiments seeking to elicit behavioural
valuations of journey attributes.
94 See for example De Jong, (2008), Preliminary Monetary Values for the Reliability of Travel Times in Freight Transport.
95 In practice, non-working trips can be further distinguished between commuting and leisure trips.
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o if there is good and sufficiently detailed and calibrated knowledge of average travel costs
between origins and destinations on all considered modes, the full difference between
travel costs on the switched to mode and switched from mode should be applied96. Time
savings are thus calculated as the difference between the estimated travel speed in the
with-the-project scenario and the travel speed in the alternative transport mode/route
from which traffic is diverted;
o in the case of a totally new infrastructure, the Rule of Half will not be directly applicable
and the measurement of the benefits depends on the nature of the new mode, its placement
in the mode hierarchy and transport network and it will often need to be derived from the
users’ willingness-to-pay.
Generated traffic. In order to calculate time savings for generated passengers and goods it is
recommended to estimate only a half time savings calculated for existing traffic, according to
the Rule of Half. On the basis of the forecast of generated traffic for every pair target-point, a
half of time savings per existing user will be assigned for the generated user for the same pair
target-point.
As for the practical use of travel time savings in the CBA, it is worth reminding that value of time must
be applied to passengers (or to tonnes, in case of cargo) and not to vehicles. If data from traffic
modelling is available per vehicle only, data on average vehicle occupancy rates will need to be used in
the calculations.
3.8.2 Road users Vehicle Operating Costs
Vehicle Operating Costs (VOCs) are defined as the costs borne by owners of road vehicles to operate
them, including fuel consumption, lubricants consumption, tires deterioration, repair and maintenance
costs, insurance, overheads, administration, etc. In fact, VOCs are correlated with type of vehicle and
average travel speed, but are also characteristics of roads such as design standards and surface
conditions.
Savings owing to VOCs reduction are a typical benefit of road transport projects. For example, the
rehabilitation/upgrade of an existing road typically implies better surface conditions and lower
congestion, which, in turn, mean higher average speed and lower VOCs under a certain speed range.
Nevertheless, projects in fields other than road may also affect VOCs. For example, a railway
investment attracting passengers from the road network. Passengers that that thus far have used the
road mode will benefit from not operating their vehicles any longer. And, in case of significant traffic
diversion, passengers that eventually decide to remain in the alternative road network may also
benefit from lower congestion and, consequently, from VOCs savings. Thus, VOCs are treated here as
general economic costs of transport.
96 However, practice across Europe shows that, in some circumstances, the ROH is applied in this case too. Whatever the chosen approach is,
it should be applied consistently at national level. See for example various integration and other methods suggested in WB Transport Note
No. TRN-11 2005. See also Economic Appraisal of Investment Project in the EIB, 2013, chapter 15 .
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EMPIRICAL ESTIMATION OF VOCs
A number of off-the-shelf models and computer software exists for the empirical estimation of VOCs. In some
traffic models, the output already contains project effects on VOCs, with- and without the intervention.
As regards price escalation over time, VOCs mainly depends on the (very difficult to predict) fuel cost evolution.
On the other hand, an evolution of the efficiency on the vehicles’ consumption shall also be taken into account.
Thus, considering these two effects being compensated each other, no price escalation is suggested.
Application rules
As with travel time, benefits from VOCs savings need to be calculated separately, for the following
factors.
Pre-existing traffic. The following procedure shall be adopted:
o take the forecast for existing traffic in terms of number and types of vehicles (passenger
cars, commercial vehicles, trucks and buses) for each origin–destination pair and for each
year across the time horizon;
o use unit VOCs (preferably from national studies, when available) estimated for each type of
vehicle depending on speed, road condition and road geometry;
o calculate the costs of vehicle operation in each scenario, by multiplying the quantity of
transport for set road categories, speed classes and vehicle types by the average costs of
operation for these classes and types;
o calculate the VOCs saving as the difference between the two scenarios.
Existing passengers who used the road mode. Diversion of existing users of the road system
(either passengers or freight) to rail or air transport modes will result in changes to vehicles
operating costs. VOCs of users who thus far have used the road mode are calculated in the
same way as travel time savings.
Generated/induced traffic. Again, in order to calculate VOCs savings for generated/induced
traffic, the same approach as for travel time is used. Thus, on the basis of the forecast of
generated traffic, half of VOCs savings per existing vehicle will be assigned to the generated
traffic.
3.8.3 Operating costs for service carriers
In railway, airport and port investments, typically, the first ʻusersʼ of the infrastructure are the
companies (carriers) that, in turn, operate the service for final users (passengers and cargo).
For example, as a result of an infrastructure upgrade, operating costs for railway carriers may change
due to greater effectiveness, such as power effectiveness, staff productivity or a shorter route. If
significant, this effect could be taken into account and included as a project benefit. For example,
savings may be estimated as a percentage reduction of vehicle operating costs per train-km or faster
ʻasset rotationʼ (i.e. better use of owned rolling stock)97.
Application rules
If the financial analysis is carried out at consolidated level, any variation in the operating costs borne
by the infrastructure owner and/or the service carriers (in other words, the ʻproducerʼ of the
transport service) will be already captured in the financial analysis and its economic valuation consists
of applying the conversions factors to the relative, previously estimated, cash flows.
97 An adequate fiscal correction of the rolling stock operating costs must be performed in each case.
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However, as shown above, in some cases the consolidation of the analysis is not feasible, so the point
of view of the project owner is adopted. In such cases, changes in operating costs on carriers could be
calculated and added to the economic appraisal where appropriate (see discussion on producer
surplus in section 5.8). Their estimation should be based on data coming from the carriers who offer
services within the analysis area. Their inclusion in the economic appraisal is however optional, for
two main reasons: i) usually, their contribution to the project results is relatively marginal, and ii) the
obtainment of data from companies can prove cumbersome.
3.8.4 Accidents
Given their nature, all transport activities imply a risk for the users of suffering an accident. Either by
mechanical failure or, more commonly, by the influence of human errors, accidents involving vehicles
are events that occur in all transport modes. The completeness, quality and integration of the
signalling (road, rail, etc.) and safety (rail, mainly) systems greatly contributes to reduce the accident
rates, and this should be taken into account in the economic analysis.
Safety benefits are (mainly) related to road traffic. However, the economic benefit arises not only as a
result of directly improving the road safety conditions, but also indirectly, e.g. by diverting passengers
to other, statistically safer means, such as rail and air transport. In both cases, this benefit should be
computed in the economic analysis, possibly distinguishing between fatalities, severe injuries98 and
slight injuries99 avoided.
According to the academic literature, the economic cost of accidents is mainly ascertained by the
following two components100:
direct costs: these costs consist of medical rehabilitation costs, both incurred in the year of the
accident and future cost over the remaining lifetime for some injury types, plus administrative
costs for police, the court, private crash investigations, the emergency service, costs of
insurances, etc.;
indirect costs: these costs consist of the net production loss to society, i.e. the value of goods
and services that could have been produced by the person, if the accident had not occurred.
The losses of one year’s accident will continue over time up to the retirement age of the
youngest victim.
In the case of fatalities, the evaluation of the ʻproduction lossʼ (i.e. the indirect cost component) is
associated with the concept of Value of Statistical Life (VOSL), defined as the value that society
deems economically efficient to spend on avoiding the death of an undefined individual.
The preferred method for the estimation of the economic cost of accidents is the use of stated
preference or revealed preference techniques based on the concepts of willingness to pay/willingness
to accept (i.e. either survey based techniques or the hedonic wage method).
In absence of this, the human capital approach can be adopted. The basic idea is that an individual is
ʻworthʼ to the society what he/she would have produced in the remainder of their lifetime. The
definition of the VOSL in this setting becomes ʻthe discounted sum of the individual’s future (marginal)
contributions to the social product, which corresponds to future labour income, provided the wage is
equal to the value marginal productʼ. In other words, the (marginal) value of a person’s production is
assumed to be equal to the gross labour cost. The box below provides the formula to be applied for
practical calculation, while examples of empirical estimations are illustrated in Annex V.
98 Casualties which require hospital treatment and have lasting injuries, but the victim does not die within the fatality recording period.
99 Casualties whose injuries do not require hospital treatment or, if they do, the effect of the injury quickly subsides.
100 In addition, some studies include the so-called value of safety per se to reflect that people are willing to pay large amounts to reduce the
probability of premature death irrespective of their production capacity. This WTP indicates a preference to reduce the risk of being injured
or even die in an accident. Given the subjectivity of this “ʻcost componentʼ, however, here it is preferred not to make explicit reference to it.
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VALUE OF STATISTICAL LIFE
It is common to include estimates of VOSL into the analysis of projects that affect mortality risks. The VOSL is an
estimate of the economic value society places on reducing the average number of deaths by one. Estimating the
VOSL involves assessing the rate at which people are prepared to trade off income for a reduction in the risk of
dying. According to the hedonic wage method, the computation of the VOSL is as follows:
𝐿
VOSL = ∑𝑇𝑡 (1+𝑖)
𝑡
𝑡
where: T is remaining lifetime; Lt is labour income; and i is the social discount rate.
Evidence from the literature shows that, by convention, the VOSL is usually assumed to be the life of a young
adult with at least 40 years of life ahead. For labour income, the annual gross wage rate can be taken as a
reference. Also, this approach assumes that the gross wage rate in the labour market equals the marginal value
product which the labour yields. However, this is not the case when distortions of the market exist. Thus, in
situations of severe unemployment, it is suggested to correct the gross wage rate by the Shadow Wage,
calculated for that given country or region.
For a correct computation of the economic cost of fatalities, direct medical and administrative costs
shall be then added to the estimated VOSL. This requires an in-depth analysis and surveys at national
level based on medical accounts, public health records, police records and insurances. In the absence
of national statistics, values can be inferred as a percentage of VOSL. For example, using HEATCO
values as a reference basis, they are estimated, on average, at 0.02 % of the VOSL.
In the case of injuries, the production loss depends on the severity of the injury and duration of
absence from work. Again, for empirical estimation, in-depth analysis and surveys are required. In
absence of this, ECMT (1998) suggests that the value of production loss for severe injuries is 13 % and
for light injuries 1 % of the VOSL (these ratios have been basically confirmed within the HEATCO
study). In turn, direct medical and administrative costs can be estimated, on average, at 15 % and
18 % of production losses for, respectively, severe and slight injuries.
As for the other economic costs, the preferred source to obtain unit accident cost should be national
research data (when available) rather than project-specific calculations. As concerns price escalation,
the same approach suggested for the value of time can be applied.
Application rules
Once unit values for different accidents types have been obtained, the physical impact of the project on
safety (i.e. the accident risk reduction) has to be estimated from national functions/data. The following
input data are needed:
statistics on the average number of light injuries, serious injuries and fatalities per accident;
accident rates per billion vehicle-km, using actual project specific values, or, in their absence,
standardised road-type specific accident rates;
vehicle-km forecast on the road network per year with and without project.
On this basis, the decrease in the number of fatalities and injuries can be calculated and the relative
benefit valued making use of the country-specific unit costs.
3.8.5 Noise
Noise pollution can be defined as the ʻunwanted or harmful outdoor sound created by human
activities, including noise emitted by means of transport, road traffic, rail traffic, air traffic, and from
sites of industrial activityʼ (see Directive 2002/49/EC). The economic cost of noise is given by:
the annoyance that results in any restrictions on enjoyment of desired activities;
negative effects on human health, e.g. risk of cardiovascular diseases (heart and blood
circulation), that can be caused by noise levels above 50 dB(A);
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given the noise emissions have a local impact, the magnitude of the effect is related to the
distance from infrastructure location: the closer to the project site, the higher the discomfort
from noise emission.
There are several methods to evaluate the effects (either a reduction or an increase) generated by
transport projects on noise.
The recommended method is stated preferences for a direct measurement of WTA compensation or
WTP for noise reductions (see box). Noise costs vary depending on the time of the day, population
density near the noise source and existing noise level.
Alternatively, a commonly used approach is the hedonic price method, which measures the economic
cost of additional noise exposure with the (lower) market value of real estate (see Annex VII). Given
the amount of houses affected by noise and the average house price a total cost can be calculated. In
particular, the sensitivity of real estate prices to changes in noise level is measured by the noise
Depreciation Sensitivity Index101.
As concerns price escalation, the same approach suggested for the value of time can be applied.
VALUE OF NOISE: DATA SOURCES
Based on a stated preference methodology (i.e. WTP for reducing annoyance and health damages), the HEATCO
study provides EU-25 country-specific unit marginal costs per person exposed to a certain noise level. To
evaluate the economic cost of noise using unit default values, the assessment requires estimating the
increase/decrease of noise to the exposed population, to be multiplied by the appropriate unit value. In
particular, the following input data must be available, as resulting from the EIA process and the relative
production of noise maps:
- exposed people: number of people living in each of the areas identified in the noise maps and their evolution
over time;
- expected change in noise exposure, i.e. the volume of noise (dB(A)) additionally generated or avoided to
exposed people because of the project.
Building from HEATCO, the IMPACT ʻHandbook on estimation of external costs in the transport sectorʼ provides
unit values of marginal cost of noise for different network types for road and rail traffic. In this case, unit costs
are provided per vehicle-km (€ct/vkm) and the cost of noise is directly calculated as the amount of traffic (cars,
trains, ships, etc.) additionally added or avoided to the transport network.102
3.8.6 Air pollution
Transport investments can considerably affect air quality either by reducing or increasing the level of
air pollutant emissions. Effects on air pollution largely depend on the type of investment, where the
variation in emissions can be either positive or negative, as compared to a baseline scenario. Any CBA
should integrate the economic cost of air pollution, which consists of the following elements:
health effects: the aspiration of air transport emissions increases the risk of respiratory and
cardiovascular diseases. The main source of disease is particles (PM10, PM2.5);
building and material damages: air pollutants can cause damage to buildings and materials
in two ways: i) soiling of building surfaces by particles and dust; ii) degradation of facades and
materials through corrosive processes due to acidifying pollutants (NOx, SO2);
crop losses: ozone as a secondary air pollutant (formed due to the emission of CO, VOC and
NOx) and acidifying substances (NOx, SO2) cause crop damage. This means an enhanced
concentration of these substances leads to a decrease in the amount of crop;
101 See European Union (2002), The State-Of-The-Art on Economic Valuation of Noise, Final Report to European Commission DG
Environment, April 14th 2002, Ståle Navrud, Department of Economics and Social Sciences Agricultural University of Norway.
102 However, differently from HETCHO, the ʻHandbookʼ provides unit costs at EU-15 or Germany-specific levels only. Thus, a transfer
procedure based on GDP per capita is needed to adapt values to the country-specific contexts.
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impacts on ecosystems and biodiversity: ecosystem damage is caused by air pollutants
leading to acidification (NOx, SO2) and eutrophication (NOx, NH3). Acidification and
eutrophication have a mainly negative impact on biodiversity.
To calculate the external costs caused by air pollution, the bottom-up approach is regarded as the
most elaborated and best practice methodology, above all for calculating site-specific external
environmental costs.103 This approach is based on an impact-pathway method, which requires the
following methodological steps:
Estimation of the volume of air pollutants additionally emitted or avoided. Emissions
should be calculated based on national emission factors per type of vehicle involved, taking
into account national vehicle fleet composition, multiplied by transport volume (mileage).104 If
national data is not available, default emission factors can be taken from the following sources:
o ʻEMEP/EEA air pollutant emission inventory guidebook 2013ʼ105, which provides detailed
literature on air pollutant emissions to different economic sectors, including transport; or
o TREMOVE database, where emission data are available per vehicle category and region
type (metropolitan, other urban, non-urban).
Evaluation of the total air pollution costs. Estimated quantity of emissions should be
multiplied by unit costs per pollutant (by region type and taking into account population
density), as available from international sources. The IMPACT study listing unit cost values for
the main relevant air pollutants (in Euro per ton), based on HEATCO and CAFE106 CBA reports,
can be taken as reference. In addition, the most recent study applying this approach for air
pollution cost is the European research project NEEDS107, which is one of the first studies that
gives reliable cost factors, also for ecosystem and biodiversity damage, due to air pollution.
If available national guidelines providing unit economic costs for emissions are available (based on
clear and adequate assumptions and methodology), it will be also possible to calculate the impact as a
cost per vehicle-km or ton-km. In this case, air pollution costs are evaluated based on traffic volumes,
speeds and road types at analysed road sections.
3.8.7 Climate change
Any CBA should integrate the economic cost of climate change resulting from positive or negative
variations of GHG emissions. With respect to transport, the main GHG emissions are carbon dioxide
(CO2), nitrous oxide (N2O) and methane (CH4). These emissions contribute to global warming resulting
in various effects such as rising sea levels, agricultural, health, ecosystems and biodiversity impacts,
increase in extreme weather effects, etc. Climate change has therefore a global impact and thus the
related cost is not dependent on the investment location (as instead happens for air pollutants).
The transport infrastructure GHG emissions assessment will mainly refer to consequences of the
project activities (vehicles using transport infrastructure including modal shift effects). In order to
estimate the total volume of emissions generated or avoided by type of vehicle for the various modes,
this should be calculated by multiplying the emission factors by the transport volume data, taking into
account considerations such as relationships between demand and capacity (speed flow), as well as
fuel consumption and speed relationships (in the case of road). Again, default emission factors can be
taken from ʻEMEP/EEA air pollutant emission inventory guidebookʼ or the TREMOVE database. Once
103 The bottom-up approach has been applied in a variety of European studies such as NEEDS (2006, 2007, 2008); HEATCO (2006a, b); CAFE
CBA (2005a, b); ExternE (2005); UNITE (2003a, b).
104 The estimated change of quantity of emissions must be, in all cases, consistent with the output of the Environmental Impact Assessment.
Please note that in the case of road projects, most emissions produced are in relation to fuel consumption, which, in turn, is a function of
speed (real travelling speed, meaning stop&go influences; even if it is normally simplified to average speed), vehicle types, road conditions
and geometry.
105 Available at http://www.eea.europa.eu/publications/emep-eea-guidebook-2013
106 Clean Air for Europe (CAFE) Programme, at: http://ec.europa.eu/environment/archives/cafe/activities/pdf/cafe_cba_externalities.pdf
107 New Energy Externalities Development for Sustainability http://www.needs-project.org/index.php?option=com_frontpage&Itemid=1
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the emissions volume is obtained, the methodology for valuing climate change costs follows the
general approach illustrated in section 2.9.9.
3.9 Risk assessment
Due to their criticality, it is advisable to carry out a sensitivity analysis of the money values assigned to
the goods without any market, especially values of time saving and accidents. In fact, in transport
projects very often the value of time savings can represent more than 70 % of all benefits. It is
therefore a parameter that must always be analysed and tested carefully. Other sensitivity tests may
be focused on investment and operating costs or on the expected demand, in particular the generated
traffic.
It is recommended to test at least the following variables:
value of time;
accident costs;
assumptions on GDP and other economic variables trend;
rate of increase of traffic over time;
number of years necessary for the realisation of the infrastructure;
investment and maintenance costs (as disaggregated as possible);
fare/tariff/toll.
Following the sensitivity analysis, a risk assessment must be carried out which typically includes the
following risk typologies.
Table 3.4 Typical risks in transport
Stage Risk
Regulatory - Changes in environmental requirements
Demand analysis - Traffic forecasts different than predicted
- Inadequate site surveys and investigation
Design
- Inadequate design cost estimates
- Building permits
Administrative
- Utility approvals
- Land costs higher than predicted
Land acquisition
- Procedural delays
Procurement - Procedural delays
- Project cost overruns
- Flooding, landslides, etc.
Construction
- Archaeological findings
- Contractor related (bankruptcy, lack of resources)
- Tolls collection lower than expected
Operation & Financial
- O&M costs higher than expected
Other - Public opposition
Source: Adapted from Annex III to the Implementing Regulation on application form and CBA methodology.
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Case study - Road Project
I Project Description
The project consists of the construction of a new 16.4 km of tolled108 motorway, which constitutes a
missing section on a TEN-T Corridor. The new motorway will reduce traffic on an existing road which
carries annual daily traffic of more than 18,000 vehicles, most of which is transit traffic, and has
reached its capacity limit. The current road leads traffic through several smaller settlements and one
middle-sized town located in a valley, causing nuisance to residents through high levels of pollution in
the form of noise and exhaust gases, and intersects with a number of lower category roads which adds
to congestion, separation effect, and poor traffic safety. It is further characterised by a huge increase of
traffic over the last 10 years (annual growth rate was 4.5 %) and a high share of freight vehicles
(current share of goods vehicles is around 35 %).
Given the difficult characteristics of the terrain, the new motorway will need to include several bridges
and overpasses as well as one tunnel. The technical description of the project and its components is as
follows:
Component Description
Motorway: 2x2 lanes (plus emergency lanes), width 27.5 m, length 16.4 km
Feeder road: 2x1 lane, width 11 m
Junctions: 3
Structures: 3 motorway bridges, total length 2,200 m
4 overpasses, total length 800 m, average width 8 m
1 tunnel, two tubes, length 2,200 m
The project promoter is the National Motorways Company which owns and operates the
infrastructure.
II Project objectives
The objectives of the project are to:
provide fast and reliable travel for the long distance and transiting traffic;
improve traffic safety;
reduce impact of traffic on settlements.
The project is consistent with the existing strategic national transportation plan and is also included in
the operational programme for Transport. In particular, the investment will contribute to the
following OP indicators.
Indicator OP 2020 target Project (% of OP target)
Length of new motorways (km) 120 16.4 (14 %)
III Demand and option analysis
A detailed demand analysis included in a feasibility study completed in 2013 was used as a basis for
the selection and final design of the preferred option. An options analysis also contained in this study
compared two modified versions of a basic project solution that had emerged from a previously
conducted pre-feasibility study. The pre-feasibility study had analysed a range of options regarding:
alignment;
108 Vignette for cars, distance related electronic toll collection for buses, light and heavy goods vehicles.
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technical solutions and design parameters (bypass road, new 2 lane road, 4 lane express road
or motorway);
number, location and type of junctions;
phased implementation (including construction of half profile express road).
While the pre-feasibility study appraised more general project solutions based on multiple criteria
taking into consideration the economic, engineering, traffic, environmental and social perspectives, the
feasibility analysis compared only two remaining modified options109 based on cost-benefit analysis,
where the highest ENPV dictated the preferred option.
The figures below depict the traffic forecast in the ʻwith-the-projectʼ scenario (figures on the right) and
the counterfactual ʻwithout-the-projectʼ scenario (figures on the left) for years 1 and 20 of the
operational stage of the project. A single mode traffic model was used, covering only road traffic. It
covers the impact area of the project, with a sufficiently disaggregated zoning system. It includes the
national road network and most of the relevant lower category roads. Future improvements of the
network (most importantly, the construction of the motorway which includes this project) are also
included in the network model. Origin-destination matrices are based on an origin-destination survey
from 2005. The assignment is based on minimising the cost of travel (including time, distance and toll
cost). The traffic model was calibrated with traffic count data from 2010, and validity tests show that
the model is sufficiently good in replicating the actual travel patterns. Future state matrices were
multiplied by growth rates, which are based on assumed changes in population, economic activity, car
ownership and transport cost. It was assumed that the traffic growth rate between 2015 and 2025 will
be around 2 % per year, and around 1 % after year 2025. It should be noted that no
generated/induced traffic or switch from other modes is expected, since the project is not located in a
major urban area and no specific changes in population, employment and land use pattern are
expected. In the opening year of the project, it is forecasted that 11 350 vehicles per day will shift from
the existing road to section N1 of the new road (9 650 vehicles per day on section N2). As a
consequence, the traffic load on the different sections of the existing road will be notably reduced (7
000 vehicles per day in section E3 compared to 18 400 in the without-project scenario).
Year 1
Year 20
Legend: blue - existing sections, red - new sections. Section name, a.a.d.t. cars, a.a.d.t. LGV+HGV.
109 The two options differ in their alignment and location of the interchange.
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The level of service (LOS) is estimated according to the HCM methodology. Currently, LOS is D and E
on some sections, which will deteriorate to F in near future. Once the motorway is constructed, the
LOS on the existing road will improve to B and C, and will remain sufficient until year 20. The LOS on
the motorway will reach C in year 20, which is an indication for adequate capacity.110
IV Project Costs and Revenues of the selected Option
Investment Cost
The cost estimate for works and supervision of the selected option is based on detailed design, as the
works have not been tendered yet. Land purchase is partially completed. The cost estimate is based on
constant prices of 2013.
Investment cost component Total cost
Planning/design fees, technical assistance 3 000 000
Land purchase 12 000 000
Building and construction, of which: 248 350 000
Earthworks 12 500 000
Vegetation 800 000
Road 48 000 000
Bridges 77 000 000
Tunnel 80 000 000
retaining walls 5 800 000
noise and safety barriers 7 500 000
public utilities 8 500 000
motorway information system 1 250 000
Buildings 1 000 000
other 5 940 000
Plant and machinery 0
Publicity 60 000
Supervision 5 000 000
Total Investment cost excl. contingencies 268 350 000
111
Contingencies (10% of construction cost) 24 835 000
Total Investment cost incl. contingencies 293 185 000
VAT (recoverable) 56 630 055
Total Investment cost including VAT 349 815 055
The total project investment cost shown in the table above is considered eligible except the VAT, which
is recoverable.
Estimates include all costs incurred for planning at feasibility stage and during the implementation
period of the project, while the cost of all preliminary activities (pre-feasibility studies, surveys carried
out before the feasibility study) are treated as a sunk cost and are thus not included.
Toll from freight vehicles is collected on behalf of the National Motorway Company by a toll collection
company, through the pre-existing electronic toll collection system based on a combination of GPS and
GSM technology. There is no physical investment necessary to extend the tolling on new sections, the
motorway operator pays a fee for each toll transaction made on his road and receives the collected toll.
110 Highway Capacity Manual (HCM) is guidance for the calculation of capacity and level of service for various road types (freeways,
highways, rural roads) and road intersections (unsignalised, signalised, roundabouts). It is published and updated by Transportation
Research Board (USA). Level of service for highways: A – free flow; B – reasonably free flow; C – stable flow; D – approaching unstable flow; E
– unstable flow; F – forced or breakdown flow. This method is used here as an example and does not preclude the use of other available
methods.
111 Based on experience a 10 % contingency at this stage of project development is sufficient for most of the projects.
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The following average unit costs were calculated to appraise the cost estimates of the most significant
investment components, which were found to be well within the cost range of other comparable
projects:
Investment component Unit cost
Motorway, total EUR 16.3 million/km
Motorway, excluding bridges and tunnels EUR 6.8 million/km
2
Bridges EUR 1,151 /m
Tunnel EUR 18.2 million/km
Operation and maintenance cost
Routine maintenance cost for the new road is estimated on the basis of average maintenance
requirements on the existing motorway network in the country and current maintenance practice of
the motorway operator. Average routine maintenance cost is thus assumed to be EUR 34 000 per km
of motorway112.
Routine maintenance cost for the existing road is assumed to be the same in the with and without-
project scenarios and is thus excluded from the assessment.
Periodic maintenance of the new road is estimated on the basis of the expected schedule of periodic
maintenance works. The timing of the works was determined on the basis of the observed
maintenance cycle in the network of existing motorways in the country (e.g. re-pavement after 10
years, bridge repair after 15 years, retaining walls repair after 20 years, etc.); average cost of these
works is also based on cost observed in the past.
Periodic maintenance of the existing road is excluded from the analysis. The decrease of traffic will
extend the life of the infrastructure elements by a few years and consequently the maintenance cycle
will be longer, however, it is assumed that maintenance measures will remain the same.
Operating cost of road includes toll collection cost; traffic management of the new section will be done
from the existing traffic control centre without any additional cost and is thus excluded from the
assessment. It is assumed that toll collection cost is EUR 0.12 per transaction (i.e. passage of a
motorway section between the two junctions).
Revenue
A toll is only collected from goods vehicles: for light goods vehicles (including buses) EUR 0.10 /km;
for heavy goods vehicles EUR 0.20 /km. The assumed share of light goods vehicles (including buses) is
55 %, for heavy goods vehicles it is 45 %.
V Financial and Economic Analysis
The analysis is performed using a 30-year reference period which is common for road projects. A
residual value of the investment is considered at the end of the reference period; the residual value is
EUR 13 million in the financial analysis which is calculated on the basis of the net present value of cash
flows generated after the reference period (based on the perpetuity formula) and EUR 150 million in
the economic analysis (based on the depreciation formula and corrected by the conversion factor). The
financial and economic analyses use constant prices. A real discount rate of 4 % is used in the financial
calculations, while a 5.0 % social discount rate is used in the economic analysis, in line with EU wide
benchmark set by the Commission. VAT is reimbursable and thus excluded from the analysis.
Financial analysis
112It could be assumed that due to the increasing wages and energy price there would be some real increase of the operation and
maintenance cost per km. This increase will be at least partially compensated by the increased productivity (due to better materials and
technology). Since it is difficult to estimate the rate and pace of these two processes it is assumed that the O&M cost per km will remain
constant throughout the evaluation period.
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The cash-flows for the financial analysis are shown in the following table, including the calculation of
the relevant financial performance indicators of the project.
The markedly negative financial net present value of the investment (FNPV(C) = -EUR 248 million)
shows that the project requires EU assistance to make it viable.
The project is a net revenue generating operation in the meaning of Article 61 of Regulation (EU)
1303/2013. In this case, the contribution from the EU Cohesion Fund to the project has been
determined using the method based on the calculation of the discounted net revenue113. The resulting
pro-rata application of discounted net revenue is 93.4 %. This, multiplied with the eligible cost shown
in section IV above (EUR 293.2 million) and with the co-financing rate of the relevant priority axis of
the OP (85 %), gives a EU grant for the project of EUR 232.7 million.
The remainder of the investment is provided by the promoter entirely from equity, without the need
to contract loans. The equity contribution will be financed through additional paid-in capital from the
State, for which a formal commitment exists.
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 15 20 25 30
EU GRANT
Construction Operation
Calculation of Discounted Investment Cost (DIC) NPV 4 %
Investment cost excluding contingencies mEUR 259.7 103.6 101.8 63.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
DISCOUNTED INVESTMENT COST (DIC) mEUR 259.7 103.6 101.8 63.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Calculation of Discounted Net Revenues (DNR) NPV 4 %
Revenue mEUR 40.9 0.0 0.0 0.0 2.2 2.3 2.3 2.4 2.4 2.5 2.5 2.7 2.9 3.1 3.4
O&M costs mEUR 27.9 0.0 0.0 0.0 0.9 0.9 0.9 0.9 0.9 0.9 0.9 7.8 0.9 1.0 1.0
Residual value of investments mEUR 4.2 0 0 0 0 0 0 0 0 0 0 0 0 0 13
DISCOUNTED NET REVENUES (DNR) mEUR 17.2 0.0 0.0 0.0 1.4 1.4 1.5 1.5 1.5 1.6 1.6 -5.1 2.0 2.2 15.6
ELIGIBLE COST (EC) 293.2
Pro-rata application of discounted net revenue = (DIC - DNR) / DIC: 93.4%
CO-FINANCING RATE OF PRIORITY AXIS (CF): 85.0%
EU GRANT ( = EC x PRO-RATA x CF): 232.7
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 15 20 25 30
FRR(C)
Construction Operation
Return on Investment NPV 4 %
Investment cost mEUR -259.7 -103.6 -101.8 -63.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Revenues mEUR 40.9 0.0 0.0 0.0 2.2 2.3 2.3 2.4 2.4 2.5 2.5 2.7 2.9 3.1 3.4
O&M costs mEUR -27.9 0.0 0.0 0.0 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -7.8 -0.9 -1.0 -1.0
Residual value of investments mEUR 4.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 13.2
Project cash-flow mEUR -248.2 -103.6 -101.8 -63.0 1.4 1.4 1.5 1.5 1.5 1.6 1.6 -5.1 2.0 2.2 15.6
FRR(C) (before EU grant) -8.8%
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 15 20 25 30
FRR(K)
Construction Operation
Loan Balance EU grant
Beginning balance mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Loan disbursements mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Interest payments mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Principal repayments mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Ending balance mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
National Financing Sources
National public (grant) mEUR 24.0 22.5 13.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
National private (equity) mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Return on National Capital NPV 4 %
National public (grant) mEUR -58.6 -24.0 -22.5 -13.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
National private (equity) mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Interest payments mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Principal repayments mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M costs mEUR -27.9 0.0 0.0 0.0 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -7.8 -0.9 -1.0 -1.0
Revenues mEUR 40.9 0.0 0.0 0.0 2.2 2.3 2.3 2.4 2.4 2.5 2.5 2.7 2.9 3.1 3.4
Residual value of investments mEUR 4.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 13.2
National cash-flow mEUR -41.4 -24.0 -22.5 -13.9 1.4 1.4 1.5 1.5 1.5 1.6 1.6 -5.1 2.0 2.2 15.6
FRR(K) (after EU grant) -2.9%
113 As set out in Article 61(3)(b) of Regulation (EU) 1303/2013
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Note that the FNPV(K) on national capital remains negative because the EU grant is covering only
85 % of the gap, while the remainder is covered by a national public grant.
The project appears to be financially sustainable, as the investment cost during implementation is
covered by an equal amount in financing sources and its cumulated net cash flow during operations is
positive during the entire evaluation period.
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 15 20 25 30
FINANCIAL SUSTAINABILITY
Construction Operation
Fianncial sustainability
National public (grant) mEUR 24.0 22.5 13.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
National private (equity) mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
EU grant mEUR 88.4 89.2 55.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Loan disbursement mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Revenues mEUR 0.0 0.0 0.0 2.2 2.3 2.3 2.4 2.4 2.5 2.5 2.7 2.9 3.1 3.4
Total cash inflows mEUR 112.4 111.7 69.0 2.2 2.3 2.3 2.4 2.4 2.5 2.5 2.7 2.9 3.1 3.4
Investment cost mEUR -112.4 -111.7 -69.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M costs mEUR 0.0 0.0 0.0 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -7.8 -0.9 -1.0 -1.0
Interest payments mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Principal repayments mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Total cash outflows mEUR -112.4 -111.7 -69.1 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -0.9 -7.8 -0.9 -1.0 -1.0
Net cash-flow mEUR 0.0 0.0 0.0 1.4 1.4 1.5 1.5 1.5 1.6 1.6 -5.1 2.0 2.2 2.4
Cumulated net cash-flow mEUR 0.0 0.0 0.0 1.4 2.8 4.3 5.8 7.3 8.9 10.5 12.3 14.3 15.6 20.3
Economic analysis
For the purpose of socio-economic assessment, the investment cost estimate was corrected for fiscal
effects by factor 0.91 (excl. cost of land which was not subject to fiscal correction). The routine
maintenance cost was corrected by factor 0.88. Fiscal correction factors are based on share of transfer
payments in labour and energy cost and their respective share in overall cost.
The socio-economic analysis includes following monetised benefits, which are consistent with the
project objectives, i.e. faster travel on a safer road with separated carriageways, travel time savings,
vehicle operating cost savings, accident cost savings.
Project benefits, related to the reduction of negative impacts (pollution and noise) within settlements
were not quantified, given that these were not considered to be of importance in monetary terms, but
the socio-economic analysis does include project impact on the emission of CO2 as the main global
environmental impact of transport.
Travel time savings (in minutes saved per person) are quantified with the help of the traffic model on
the basis of average speeds achieved by cars and goods vehicles on the existing and new road links
(see table below), their length and assumed traffic volumes. As a consequence of the project, it is
estimated that the average car using the full length of the new motorway will save around 12 minutes
in year 1, while goods vehicles will save around nine minutes. Time savings for vehicles remaining on
existing road are around four minutes per vehicle.
Average speed (km/h)
Without project With project
Year 1 Year 20 Year 1 Year 20
Length LGV+ LGV+ LGV+ LGV+
Section (km) Cars HGV Cars HGV Cars HGV Cars HGV
E2 1.7 51.4 46.5 41.0 40.2 64.7 53.8 62.5 53.4
E3 3.6 35.2 35.2 31.9 31.9 38.8 38.6 32.5 32.4
E4 3.1 42.7 42.1 32.3 31.8 57.2 53.0 52.9 49.6
E5 3.7 40.6 39.3 34.5 33.9 54.8 51.0 53.9 50.2
E6 5.6 69.0 57.6 55.1 47.5 79.1 63.6 78.7 63.6
N1 5.7 104.8 75.2 98.4 72.4
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N2 10.7 113.0 74.5 107.7 72.5
N3 2.0 79.7 70.0 78.6 69.6
To monetise the benefit of VOT savings, the following additional assumptions114 were made:
Variable Assumption Comment
Average occupancy, cars 1.8 persons Based on different surveys carried out in
Average occupancy, goods vehicles 1.2 persons the country
Trip purpose mix, cars 20 % work trips
80 % non-work trips
Trip purpose mix, goods vehicles 100 % work trips
Unit value of time, work trips EUR 12.90 per hour Estimate based on average wage in the
country (EUR 9 per hour) and assumed
labour related overhead (33 %)
Unit value of time, non-work trips EUR 4.30 per hour Estimated at 1/3 of value of time for work
trips
Escalation factor for VOT GDP per capita growth, with elasticity
factor of 0.7
Vehicle operating costs (VOC) savings are calculated for different types of vehicles taking into
consideration national vehicle fleet, speed and road capacity, road condition and road geometry. The
software used applies nationally calibrated values and crew cost has been excluded to avoid double-
counting.
Accident cost savings are related to the fact that the majority of the traffic will be diverted to a safer
motorway, with separated carriageways for each direction and grade-separated crossings with lower
category roads. Analyses of traffic safety revealed that the traffic fatality risk on the existing road is
10.7 fatalities per one billion vehicle-km, whereas on a motorway it is 3.1 fatalities per one billion
vehicle-km. It was estimated that the construction of the new road will save around 0.6 fatalities in the
opening year and around 0.9 fatalities in the final year of analysis.
A prevented road fatality in the country is estimated at EUR 677 500 (estimate based on values
derived from a literature review). It is assumed that this value will grow at the same rate as real GDP
per capita, with an elasticity factor of 1.0.
CO2 savings are related to the fact that due to the more favourable alignment the distance travelled for
the majority of the traffic will reduce, while the traffic flow remaining on the existing road will be
smoother. The assumed unit cost is EUR 31 per tonne of CO2 (in 2013 prices), with an annual growth
of EUR 1.
The resulting cash flows and their ENPVs are shown in the following table.
114 The unit values applied in this case study are illustrative and are not to be taken as benchmarks.
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►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 15 20 25 30
ERR
Construction Operation
Socio-economic costs NPV 5.0 %
Project investment cost mEUR -197.6 -94.9 -92.1 -57.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 151.0
Project O&M costs mEUR -21.0 0.0 0.0 0.0 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -6.9 -0.8 -0.8 -0.9
Total economic costs mEUR -218.6 -94.9 -92.1 -57.0 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -6.9 -0.8 -0.8 150.2
Socio-economic benefits NPV 5.0 %
B1. Time savings mEUR 266.7 0.0 0.0 0.0 10.7 11.5 12.3 13.2 14.1 15.0 16.0 20.7 25.4 30.5 37.7
B2. VOC savings mEUR 26.5 0.0 0.0 0.0 1.3 1.4 1.5 1.5 1.6 1.7 1.8 2.1 2.4 2.7 3.0
B3. Accident savings mEUR 9.2 0.0 0.0 0.0 0.4 0.4 0.5 0.5 0.5 0.5 0.6 0.7 0.9 1.0 1.2
B4. CO2 savings mEUR 3.1 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.3 0.4 0.5
Total economic benefits (B1+B2+B3+B4) mEUR 305.5 0.0 0.0 0.0 12.5 13.5 14.4 15.4 16.3 17.4 18.5 23.7 28.9 34.6 42.3
Net benefits (ENPV) mEUR 87.0 -94.9 -92.1 -57.0 11.8 12.8 13.7 14.6 15.5 16.6 17.7 16.8 28.1 33.7 192.5
ERR 7.1%
B/C RATIO 1.40
In terms of ENPV, the main benefit of the project are travel time savings (87 % of total), followed only
distantly by vehicle operating cost savings (9 %), accident cost savings (3 %), and CO2 savings (1 %).
All in all, the results of the socio-economic analysis (ERR: 7.1 %, ENPV: EUR 87.0 million) show that
the project generates a positive welfare change and is thus worthy of receiving EU assistance.
VI Sensitivity analysis
This is performed by calculating the percentage change of the FNPV(C) and the ENPV as a consequence
of a 1 % change in key costs and benefits. If the absolute percentage change in ENPV is higher than
1 %, then the respective variable is deemed to be critical.
Variable tested FNPV(C) elasticity ENPV elasticity
Investment cost +1 % -1.07 % -2.70 %
Traffic on new road +1 % +0.27 % +2.04 %
O&M cost +1 % -0.12 % -0.24 %
Toll revenue +1 % +0.17 % n.a.
VOT +1 % n.a. +3.08 %
VOC +1 % n.a. +0.31 %
Accident saving +1 % n.a. +0.11 %
CO2 saving +1 % n.a. +0.03 %
The sensitivity analysis reveals that the project’s financial performance is not very sensitive to any
change in the input variables.
On the other hand, the economic performance is quite sensitive to changes in assumed investment cost
and demand and value of travel time savings, which are considered critical variables. This is also
reflected in their switching values (i.e. necessary changes in the variables for the ENPV to become
negative), which are +37 % for the investment cost and -32 % for the VOT savings (as compared to the
base case assumptions). Given that these values are, broadly speaking, within realistic possibilities, it
was decided to carry out a probabilistic risk analysis in addition to the standard qualitative risk
analysis.
VII Risk analysis
Given that the sensitivity analysis revealed no critical variables for the financial analysis, the risk
analysis concentrates – for the sake of simplicity - solely on the economic analysis of the project and is
done in both qualitative and quantitative terms.
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The qualitative risk analysis is presented in the following risk matrix. It takes into account
uncertainties related to all aspects of the project. Note that prevention and mitigation measures are
only defined for the remaining risks of the highest level.
Probability Severity Risk Prevention/mitiga
Risk Effect Causes
(P) (S) level tion measures
PLANNING AND ADMINISTRATIVE RISKS
EIA completed,
Building permit
delay A III Low documentation for
acquisition
building permit is ready.
Approvals obtained,
Utilities (and other) coordination on-going,
delay A I Low
approvals spatial plan is prepared
and approved.
Changes in
EIA procedure carried
environmental A I Low
out.
requirements
LAND ACQUISITION
Land purchase partially
Cost of land cost B III Low
completed.
Delays of land mode Land purchase partially
delay B IV
purchasing rate completed.
No additional
Additional
cost A I Low requirements appeared
requirements
so far.
Construction site
Land for temporary
A I Low accessible, no need for
access to the site
temporary access.
DESIGN
Inadequate site Surveys were undertaken
surveys and cost A III Low during design, conditions
investigation known.
All infrastructure
Changes in the
cost A III low components/parameters
requirements
agreed.
Inadequate design
cost B III low Design mainly completed.
cost estimates
CONSTRUCTION RISKS
Decision to submit
the application for
EU funds
Inadequate depending on
construction cost Tender price not yet tender results,
cost D IV high
estimates (compared known. contingencies
to received bids) included in the
budget, credit line
for additional
funding is available
Project implementation
Surveys were
did not start yet, it
Cost overruns (during undertaken during
cost D IV high includes a tunnel
construction) design, design was
construction which
audited
involves geological risks.
Inadequate mode Estimate based on
cost C III
construction quality rate experience.
Flooding, landslides
cost A III low
and similar
Archaeological No known archaeological
cost B I low
findings findings in adjacent areas.
Inadequate
Tender price not yet
supervision cost cost C I low
known.
estimates
Project implementation
Inadequate temporary did not start yet, cost
cost C I low
works cost estimates compared to total cost is
low.
Contractor’s delay B III low Possible, adequate
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bankruptcy requirements concerning
financial strength will be
included in tender
dossier.
Financial situation may
affect contractor’s ability
Contractor’s resources delay B III low
to finance works and the
stock of materials.
mode Could be delayed by a
Public procurement delay C III
rate year (experience).
OTHER RISKS
Master plan approved, no
Protester action cost A I low
civil initiatives active.
High priority project for
the country, international
Change of strategy cost A I low
commitments, low cost
invested so far.
Vignette system, no
intention to introduce
Introduction of direct % direct tolling of the cars at
B III low
tolls (toll evasion) traffic the moment, transiting
trucks will be prohibited to
use lower category roads.
Reduced capacity to fund
Lack of national mode
delay A IV projects, but project
finance rate
remains high priority.
Traffic study available,
% Audit the traffic
Traffic (demand) risk C IV high uncertainties regarding
traffic model.
long term forecast.
Evaluation scale: Probability: A. Very Unlikely; B. Unlikely; C. About as likely as not; D. Likely; E. Very likely.
Severity: I. No effect; II. Minor; III. Moderate; IV. Critical; V. Catastrophic.
Risk level: Low; Moderate; High; Unacceptable.
The qualitative risk analysis basically displays two critical risks: i) construction cost risk (increase of
contract price compared to designer’s estimate; increase of out-turn cost compared to contract price,
amongst others due to considerable geological risk); and ii) demand risk.
These two risks were therefore subject to a quantitative risk analysis.
A Monte Carlo risk simulation was used to assess the probability distribution of the project’s socio-
economic performance indicators (ENPV), repeated in 4,000 iterations. An asymmetrical triangular
probability distribution was applied115, with the following assumptions concerning possible ranges for
investment cost and traffic benefits (min., max.):
investment cost (-5 %; +20 %);
traffic on the new road (-30 %; +15 %).
The assumed range of investment cost is based on ex-post evaluation of motorway projects in the past
which analysed cost development during the project cycle, and which found that for standard project
final out-turn cost is in the range of -5 % to +20 % compared to the designer’s estimate.
Monte Carlo analysis simulates the variation of the traffic on the new road which affects the related
benefits (time savings, vehicle operating cost, accident savings). The parameters (min., max.) were
derived through panel assessment which considered sporadic evidence for some of the projects and
published articles. Probability density and cumulative probability distributions for the ENPV are
shown below. In the base scenario the ENPV is around EUR 87 million, the most likely risk adjusted
ENPV is around EUR 77 million. The probability of negative ENPV is 15 %.
115 This was deemed most suitable considering the available data.
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Probability density of ENPV Cumulative probability distribution
The risk analysis suggests that there is a probability for a negative ENPV due to residual risks that are
outside of the project promoter’s control, namely geological conditions where a tunnel is to be built
(geological survey cannot exclude all risks), construction market prices (tender prices not always
following the experience of previous projects) and demand (traffic behaviour not always following
foreseeable patterns). All necessary risk prevention measures have already been undertaken during
project design, such as detailed geological and hydrological surveys, and the elaboration of a traffic
model which provided parameters for dimensioning of the road elements. As a mitigation measure
regarding traffic forecast, a recommendation is to audit the traffic model and continuously improve it,
if and where necessary, e.g. by obtaining the latest input data to feed into the model.
Considering the careful project preparation process thus far (incl. risk prevention measures) and the
positive expected ENPV, the calculated risk of negative ENPV is deemed acceptable and the project
should be released for the next stage (tendering). Nevertheless, the final approval of the project and
application for EU funding are not forthcoming until the results of tender are known. If the tender
would result in significantly higher prices than estimated (i.e. more than 10 %) it is recommended
repeating the CBA and risk analysis with new inputs and reconsidering the further project
development and implementation.
\100
Case study - Railway
I Project Description
The project consists of the upgrading of a double-track railway section, part of the TEN-T Priority axis
Y. The existing line is 94.75 km long (from the Y end of station A to the X end of station B), all double
tracked, electrified and equipped with automatic line block, and is used for both passenger and freight
traffic116.
Current traffic averages approximately 40 pairs of trains per day. The average technical speed allowed
by the current condition of the line is about 81 km/h (design speed equivalent, commercial speed is
lower). The line is not interoperable as it is not equipped with ERTMS (European Rail Traffic
Management System). The main performance problems of the existing line are caused by the speed
limiting alignment parameters and by the significant lack of past maintenance.
Further to the realignments (speed upgrade variants) provided under the project, the section length
shall be reduced from 94.75 km to 89.5 km. The project works include notably:
renewal of 63 464 double track km on the existing alignment and construction of 26 036
double track km on a new alignment. Upon upgrading, approximately 60 % of the line section
will allow a maximum speed of 160 km/h;
construction of two single pipe tunnels of 1,260 m total length;
construction of 13 705 km retaining walls and 1 260 km slope protection and river bed
correction.
renewal or repair of 32 bridges, construction or repair of 106 culverts;
rehabilitation of passenger buildings in four stations and six halts (about 14 725 m²);
enlargement and protection of station platforms, construction of 6 pedestrian tunnels and
repair of a grade crossings;
reduction or re-arrangement of station tracks, replacement of 144 turnouts, extension of
freight siding to 750 m length;
installation of 7 Electronic Interlockings, ERTMS Level 2 including GSM-R and rehabilitation of
the existing Automatic Train Protection (INDUSI/PZB type) system as fall-back;
closure of 7 existing level crossings, replacement of two level crossing by overpasses and
installation of automatic protection systems with four half barriers for the remaining 33 level
crossings;
rehabilitation/installation of the electric traction system on the entire length of 89.5 km;
rehabilitation of telecommunication systems (voice and data communication, passenger
information equipment, two transmission lines based on optic fibre).
The following design parameters were applied in consideration of the applicable standards/targets:
116 A wider corridor analysis has also been performed at an earlier stage and provides complementary information on the wider scale
justification of the upgrading programme. However, for the purpose of this case study a project level analysis was considered reasonable, in
particular since this approx. 100 km section improvement provides a meaningful impact on the traffic flows in particular at the level of the
origin/destination A/B.
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Criteria Parameter
Maximum speed of passenger trains 160 km/h (on approx. 60 % of line length), 120 km/h on the rest
Maximum speed of freight trains 120 km/h
Clearance UIC – B.
Maximum axle load 22.5 t
Maximum gradient 12.5 ‰ (within this section the max. gradient will be only 3‰).
Minimum length of sidings 750 m
Distance between axis in open line 4.20 m
Distance between axis in stations At least 4.75 m (Article 29(3) RET), but regularly 5.00 m.
Height of platforms in stations 55 cm
Level crossings Automatic 4 half barriers + CCTV
Compatibility of signal equipment ERTMS Level 2 with LS/Indusi ATP as fall-back
II Project Objectives
Fundamentally the project aims to improve the level of railway service on an important corridor, in
particular by reducing travel times, increasing capacity and improving safety, thereby contributing to
the overall attractiveness of the rail transport mode within the country and also at trans-European
level.
Specifically, the upgrade towards the target speed of 160 km/h for passenger and 120 km/h for freight
trains (within ERTMS Level 2 environment) will allow a travel time reduction from the current
approximately 96 to 55 minutes journey time for long distance passenger trains.
The main results expected are:
reducing the travel time for the existing rail users;
reducing operating costs for service providers;
diverting traffic from road to rail with benefits for travellers as well as for society through a
reduction of external costs and attracting new traffic to rail; and
improving traffic safety.
The project is consistent with both the existing strategic national and EU (TEN-T) plans and the
priorities of the Operational Programme Transport (OPT). It contributes to the achievement of the
following OPT indicators:
Indicator Unit Target
2015
Output
Total length of reconstructed or upgraded railway lines km 209.18
Result
Value of time savings for passengers and freight transported by upgraded M EUR/year 86.93
railways
III Options and Demand Analysis
The following main alternatives have been studied within the feasibility study:
Baseline (ʻwithout projectʼ) scenario
Assumes the business as usual scenario, under which the railway infrastructure company continues to
operate the line following current trends, i.e. with the current level of both routine and periodic
\102
maintenance (slightly lower than required) – with the effect of continuing the slight trend of lowering
the average speed (by approx. 0.5 % per year) of the line in time.
With-Project Alternatives:
Alternative 1: Online rehabilitation of the line to the initial design speed (120 km/h) without
any new upgrades/new alignments.
Alternative 2: Moderate speed upgrade to 160 km/h on approx. 60 % of the line by 2020 -
where this could be achieved with low to moderate investment costs (avoiding very costly
structures such as long tunnels and bridges).
Alternative 3: Maximal speed upgrade to 160 km/h on approx. 80 % of the line by 2020.
The alternatives have been compared within the feasibility study on the basis of CBA, as well as other
considerations (such as environmental impact including on Natura 2000 areas) and Alternative 2,
providing the best economic return (highest ERR and B/C ratio), was selected as the preferred
option117 - which was taken forward to detailed design and is the subject of this analysis.
Demand118
The current traffic volumes (average between A and B) are approximately:
30 pairs of passengers trains/day (approx. 4,900 pax/day);
9 pairs of freight trains/day (approx. 12,000 ton/day).
The forecast is derived from a model based on the impact of exogenous (GDP growth, population
growth, motorisation, travel time by road, fuel cost growth) and endogenous (travel time by rail, rail
fare growth) factors - with appropriate calibration.
During implementation the impact of the project is negative , reflecting the disruptions over the
construction period, then gradually positive after adding operation of the corridor. The positive effect
reflects additional traffic mainly diverting from roads – as a result of travel time savings.
Overall, the forecast results in an average incremental growth of the railway traffic, roughly equivalent
to 1.1 % per annum. for passengers and 0.4 % per annum for freight over the appraisal period. The
traffic forecast results without and with – project are illustrated in the graphics below:
117 Within the preferred alignment option, the FS discussed other lower level technical variants, including track capacity options within
stations, etc.
118 The demand and operational analyses are not meant to be presented within the case study, therefore what is presented here is just an
outline summarising the results of the full analysis – which is subject to a distinct section of the feasibility study. The demand and operational
analysis includes full details on the modelling/forecasting methodology as well the demand functionality, operational plans and capacity
utilisation (per sections and stations) as a basis for defining the optimal/rationale capacities actually required.
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IV Project Costs for the Selected Option
Investment Cost
The cost estimate for works and supervision of the selected option is based on a detailed design
estimate (broken down transparently into quantities and unit costs per components). The works have
not been tendered yet and land purchase is partially completed. The cost estimate is made at constant
prices of year Y.
Total Project costs Ineligible costs Eligible costs
In EUR
(A) (B) (C)=(A)-(B)
1 Planning/design fees 14 024 673 14 024 673
2 Land purchase 12 756 615 12 756 615
3 Building and construction 648,131,978 648 131 978
4 Plant and machinery 38 354 080 38 354 080
5 Contingencies 51 721 770 51 721 770
6 Price adjustment (if applicable) 0 0
7 Technical assistance 0 0
8 Publicity 125 747 125 747
119
9.1 Supervision 13 111 376 255 491 12 855 885
9.2 Other costs 922 259 922 259
10 Sub-TOTAL 779 148 498 255 491 778 893 007
11 VAT 186 995 640 186 995 640 0
12 TOTAL 966 144 137 187 251 131 778 893 007
The average cost per (double-track) km of the project, including ancillary investments in stations, etc.
is approx. EUR 8.7 million (ex-VAT), which is in line with similar projects in the country.
Infrastructure Operation and Maintenance (O&M) cost
The average maintenance unit costs for the railway line used in the analysis are:
for the ʻwithout projectʼ scenario – EUR 29 717 per track km per year (as per actual costs
incurred over the last 5 years – reflecting the business as usual assumptions);
for the ʻwith projectʼ scenario – EUR 37 500 per track km per year, as estimated for good
maintenance standards based on local costs
Another factor influencing the overall O&M expenditure of the project is the reduction in the length of
the rail section. Overall, however, there would be an increase in the O&M costs in the ʻwithʼ project
scenario as compared to the ʻwithoutʼ project scenario.
The diversion of traffic from roads may have a marginal impact (reduction) on the road O&M, but this
is usually considered not significant enough for appraisal and is therefore ignored.
119 This cost item corresponds to the supervision services over the Defects Notification Period, which extends beyond the eligibility period of
the programme.
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Residual value
The residual value has been calculated as the net present value of the financial/economic flows 120 over
the remaining lifetime (52 years) outside the reference period (30 years). This method is considered
to reflect more realistically the actual value of the assets than the traditional ʻaccountingʼ method
based on linear depreciation.
V Financial and Economic Analysis
General
The analysis is performed using a 30-year reference period which is common for railway projects.
The financial and economic analyses use constant prices (year Y). A 4 % discount rate in real terms is
used in the financial calculations, while a 5 % social discount rate is used in the economic analysis, in
line with EU wide benchmark set by the Commission. VAT is excluded from the analysis since it is
recoverable.
Financial Analysis
Since the line is operated by more than one operator the financial analysis is done from the
perspective of the infrastructure owner/manager; therefore the relevant revenues are the track access
charges (TAC) paid by the freight and passengers operators.
Additional revenues are generated by the project as a result of the incremental traffic (trains-km)
forecasted within the traffic analysis. The calculation is based on the current level of the track access
charges (i.e. average EUR 2.11 /train-km for passengers and EUR 3.29 /train-km for freight), which is
assumed not to change in real terms over the appraisal period. The choice of not raising the level of the
TAC following the line upgrading was made on the basis of the policy line taken in terms of
transferring maximum benefits of the upgrade to the end users (rather than trying to recover part of
it) – in view of improving the attractiveness of the rail mode and thus contributing to the mode shift
objective. Note also a temporary drop in revenues during the three years of the construction period as
a result of the disruptions inherent to the works under operation (track capacity limitations, delays,
etc.).
The project is a net revenue generating operation in the meaning of Article 61 of Regulation (EU)
1303/2013. To determine the contribution of the Cohesion Fund to the project, the method based on
the calculation of the discounted net revenue was applied121, which is shown in the following table.
The analysis shows that the project is not able to repay around 95 % of the invested capital.
120 Note that this means the resulting financial and economic residual values are very different, reflecting the very different profiles of the
financial and economic flows.
121 As set out in Article 61(3)(b) of Regulation (EU) 1303/2013
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►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 15 20 25 30
EU GRANT
Construction Operation
Calculation of Discounted Investment Cost (DIC) NPV 4 %
Investment cost excluding contingencies MEUR 727.4 227.2 214.4 285.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
DISCOUNTED INVESTMENT COST (DIC) MEUR 670.8 218.4 198.2 254.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
670.8
Calculation of Discounted Net Revenues (DNR) NPV 4 %
Incremental revenues (track access charges) MEUR 35.1 -0.1 -0.1 -0.2 0.2 0.4 0.8 1.2 1.5 2.3 2.4 2.8 3.2 3.7 4.1
Incremental O&M costs MEUR -15.7 0.0 0.0 0.0 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1
Residual value of investments MEUR 13.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 44.3
DISCOUNTED NET REVENUES (DNR) MEUR 33.1 -0.1 -0.1 -0.2 -0.9 -0.7 -0.3 0.1 0.5 1.2 1.3 1.7 2.2 2.6 47.4
26.2
ELIGIBLE COST (EC) MEUR 778.9
Pro-rata application of DNR = (DIC - DNR) / DIC: 95.1%
CO-FINANCING RATE OF THE PRIORITY AXIS (CF): 85.0%
EU GRANT ( = EC x PRO-RATA x CF): MEUR 629.4
80.8%
In this case, the EU grant has been calculated by multiplying the eligible cost shown in section IV above
(EUR 778.9 million) by the pro-rata application of discounted net revenue (95.1 %) and the co-
financing rate of the relevant priority axis of the OP (85 %) - resulting in EUR 629.4 million. The
remainder of the investment is co-financed out of national (state-budget and railway company122)
funds. No loans are planned.
The following profitability indicators (before-tax, real) are calculated – see cash flow tables below:
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 15 20 25 30
FRR(C)
Construction Operation
Return on Investment NPV 4 %
Investment cost excluding contingencies MEUR -718.4 -242.7 -229.9 -306.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M costs MEUR -15.7 0.0 0.0 0.0 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1
Revenues MEUR 35.1 -0.1 -0.1 -0.2 0.2 0.4 0.8 1.2 1.5 2.3 2.4 2.8 3.2 3.7 4.1
Residual value of investments MEUR 13.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 44.3
Project cash-flow / FNPV(C) - before EU Grant MEUR -685.3 -242.8 -230.0 -306.8 -0.9 -0.7 -0.3 0.1 0.5 1.2 1.3 1.7 2.2 2.6 47.4
-678
FRR(C) - before EU grant -8.3%
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 15 20 25 30
FRR(K)
Construction Operation
Return on National Capital NPV 4 %
National financing MEUR -143.4 -46.6 -44.1 -58.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M costs MEUR -16.3 0.0 0.0 0.0 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1
Revenues MEUR 36.5 -0.1 -0.1 -0.2 0.2 0.4 0.8 1.2 1.5 2.3 2.4 2.8 3.2 3.7 4.1
Residual value of investments MEUR 13.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 44.3
National cash-flow / FNPV(K) - after EU grant MEUR -109.5 -46.7 -44.3 -59.1 -0.9 -0.7 -0.3 0.1 0.5 1.2 1.3 1.7 2.2 2.6 47.4
FRR(K) - after EU grant -2.1%
Note that the FNPV(K) remains negative because the EU grant is not covering the entire gap but only
85 % of it.
To ensure overall sustainability, increased operational subsidies from the state are necessary to cover
the negative operating cash flow over the construction period and the first three years of operation
122 The national budget’s co-financing contribution is 15 % of the amount resulting from multiplying the eligible cost with the Pro-rata
application of discounted net revenue. The railway company covers the ineligible cost of the project (including the pre-financing of the VAT,
which is recoverable) and the part of the eligible cost that is not covered by the public grants (EU + national funds).
\106
(which is a consequence of (i) the initial drop in revenues and (ii) the increased O&M costs required
for good operation.
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 15 20 25 30
FINANCIAL SUSTAINABILITY
Construction Operation
Financial sustainability 779
National public co-financing MEUR 149.6 46.6 44.1 58.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
EU grant MEUR 629.6 196.1 185.8 247.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Revenues MEUR -0.1 -0.1 -0.2 0.2 0.4 0.8 1.2 1.5 2.3 2.4 2.8 3.2 3.7 4.1
Total cash inflows MEUR 778.7 242.6 229.8 306.3 0.2 0.4 0.8 1.2 1.5 2.3 2.4 2.8 3.2 3.7 4.1
Investment cost MEUR -779.1 -242.7 -229.9 -306.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M costs MEUR 0.0 0.0 0.0 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1
Total cash outflows MEUR -242.7 -229.9 -306.6 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1 -1.1
Net operating cash-flow MEUR -0.4 -0.1 -0.1 -0.2 -0.9 -0.7 -0.3 0.1 0.5 1.2 1.3 1.7 2.2 2.6 3.0
Tax* MEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Operating cost subsidies MEUR 0.1 0.1 0.2 0.9 0.7 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Cumulated net cash-flow MEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.6 1.8 3.1 10.9 20.8 32.9 47.1
* The tax line is 0 over the entire period because taxation is completed at the level of the whole company (rail infrastructure manager) –
where the overall costs are actually higher than the revenues and the break-even is reached through subsidies covering the operating loss.
Economic Analysis
The following general assumptions are noted:
123
Parameters Assumption
Average occupancy, cars 1.6 persons
Average occupancy, goods vehicles 1.2 persons
Trip purpose mix, cars 15 % business
30 % commuting
55 % other
Trip purpose mix, rail 10 % business
30 % commuting
60 % other
Average train load (pax) 120 persons
Average train load (freight) 640 tons
Average track-access charge passengers trains EUR 2.1 / train-km
Average track-access charge freight trains EUR 3.29 /train-km
Average fare per passenger-km train EUR 0.07
Average fare per passenger-km bus EUR 0.05
Value of time (passengers) EUR 12.6 /h for business
EUR 6.2 /h for commuting
123 The values are country-specific and are provided here for the purpose of the case study only.
Note: for actual appraisals, national/project specific values as appropriate should be determined and used.
\107
EUR 5.2 /h for other purposes
Vehicle operating costs per vehicle-km (roads) EUR 0.2 for cars
EUR 0.27 for minibus
EUR 0.95 for trucks
Train operation costs per train-km EUR 3.95 for long-distance passengers
EUR 3.3 for short-distance passengers
EUR 4.01 for freight trains
Train operation costs per hour-train EUR 348.3 for long-distance passengers
EUR 200.3 for short-distance passengers
EUR 93.4 for freight trains
Average conversion factors to investment cost (shadow 0.91 for investment cost
prices)
0.88 for O&M costs
The economic analysis looks to monetise the project impact on three levels:
consumers Surplus (rail users);
producers Surplus (rail and bus operators);
externalities (emissions and accidents).
Consumers Surplus
For the existing rail users, the consumer surplus is given by the change in the generalised user cost,
namely in the time and fare cost.
Since the fares are assumed not to change in result of the project, the relevant impact is the time
saving. The travel time (with project) was determined based on a train running simulation considering
the profile of the upgraded line. For the scenario ʻwithout-the-projectʼ the estimation was based on the
current running times, adjusted over time according to the maintenance profile assumptions made for
this scenario.
Calculation of benefits related to reduction of pollution and noise within settlements was not
undertaken.
For the new rail users (diverting from roads124 – bus and car users respectively – and new demand
generated), the consumer surplus was estimated following the ʻrule of halfʼ formula – which essentially
assumes half of the savings in the generalised cost of the existing users. Since the fares are not
changing, this means half of the travel time savings.
For the users remaining on the road the marginal benefit from reducing the traffic volumes is
considered not significant enough to be included in the appraisal (in particular since the respective
road is not congested) and is therefore ignored.
124 Note the methodological choice of estimating the surplus for the diverted traffic just as for the generated traffic (rule of half) as compared
to the other alternative acceptable method, namely the calculation based on the difference between the generalised cost in the ʻshifted fromʼ
mode (road) and ʻshifted toʼ mode (rail). The rule of half method was chosen in particular since in this case there are no capacity constraints,
either now or in the foreseeable future.
\108
Producers Surplus
The producers surplus is given by the project impact (mainly as a result of the new rail traffic mostly
diverted from roads but also as a result of the change in train operating costs for the existing rail
users) on:
the rail operators, namely the change in:
o the train operating costs (savings)125;
o the rail fare revenues (additional gains).
The road operators, namely the change in:
o the vehicle (bus) operating costs (savings)126;
o the (bus) fare revenues (losses).
The cost impact on the infrastructure manager is quantified under the project costs (investment,
residual value and O&M), whilst the revenues change impact (track access charges) is ignored as it
represents a transfer (of equivalent value) from the rail operators surplus.
Externalities
Accidents cost savings result essentially from the traffic shifted from roads to rail, knowing the
accident costs (measured in aggregate costs per vehicle-km based on previous research in the
country) are substantially lower on rail than on roads. Additional safety benefits are brought by the
improved protection of the line (elimination of some level crossings, full barrier protection at the
others).
Fatalities number/ 100 million Fatalities number/ 100 million
vehicles-km passengers-km
Roads 5.80 3.6
Rail 10.50 0.1
Emissions cost savings (air pollution and climate change costs) are also a result of the mode shift from
road to rail.
The unit costs per passenger-km and ton-km presented in the following table are based on a national
study of external costs in the transport sector and are adjusted to base year constant prices. Escalation
rates were applied to reflect the increase of damage costs of CO 2 and air pollutant emissions over time,
which is in line with the recommendation made in this guide and other international studies on the
matter.
Passengers (pax-km)
Road cost EUR/pax-km 0.015
Rail Cost EUR/pax- km 0.007
Freight (ton-km)
Road cost EUR/ton-km 0.026
Rail Cost EUR/ton-km 0.006
125 The train operating cost savings primarily result from the reduced length of the section (by approx. 5 km) further to realignments, but also
further to the reduction in the travel time and thus of the time based utilisation cost, as well as the more homogeneous speed profile of the
line leading to less acceleration, etc.
126 The assumed mode shift from bus to rail leads to a slight reduction in bus services and hence bus operating cost savings. The reduction in
bus services may generate disbenefits in terms of increased bus intervals/waiting time but since in this case (i) the reduction in the bus
services is marginal, and (ii) the current bus frequency is relatively high, the impact was considered marginal and was therefore ignored.
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Noise impacts are considered marginal and thus ignored given the rural environment (mostly outside
inhabited areas).
The resulting cash flows and their present values are shown in the following table.
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 15 20 25 30
ECONOMIC ANALYSIS
Construction Operation
ECONOMIC COSTS NPV 5 %
Economic investment cost MEUR 641 220.8 209.2 279.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Residual value MEUR -71 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -305.2
Infra O&M costs MEUR 12 0.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
Total economic costs MEUR 582 220.8 209.2 279.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 -304.3
ECONOMIC IMPACTS NPV 5 %
CONSUMERS (USERS) SURPLUS 857
RAIL EXISTING USERS
Value of time savings MEUR 801 -2.0 -1.8 -3.0 7.0 10.0 13.0 17.0 22.8 37.2 40.8 61.9 92.5 134.2 193.3
Value of train fares change MEUR 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
NEW RAIL USERS
Generalised users cost surplus (half of the
change in time and fare cost) MEUR 56 0.0 0.0 0.0 0.2 0.4 0.5 0.7 1.1 3.0 3.2 4.2 6.3 9.4 13.9
PRODUCERS SURPLUS 466
Train operating costs savings MEUR 93 -0.4 -0.3 -0.5 -0.3 -0.2 2.3 2.6 3.4 6.1 6.5 8.4 10.9 13.7 17.2
Vehicle operating costs savings (road) MEUR 284 -1.0 -0.9 -1.6 2.9 5.1 7.2 9.1 12.3 20.9 22.0 26.8 31.6 36.0 40.9
Rail fare revenues increase MEUR 254 -0.7 -0.6 -1.1 1.7 3.2 5.7 7.3 10.1 19.2 20.1 23.4 28.2 33.2 38.9
Bus fare revenue loss MEUR -166 0.5 0.4 0.7 -1.5 -2.9 -3.7 -4.8 -6.6 -12.5 -13.0 -15.2 -18.3 -21.6 -25.2
EXTERNALITIES 140
Accidents MEUR 24 -0.1 -0.1 -0.1 0.1 0.3 0.4 0.5 0.7 1.4 1.5 2.0 2.8 3.8 5.1
Emissions MEUR 116 -0.2 -0.2 -0.3 0.4 1.2 1.7 2.2 3.3 6.1 6.6 9.7 13.5 18.5 25.3
Total economic impacts MEUR 1,462 -3.8 -3.5 -5.9 10.5 17.0 27.2 34.7 47.2 81.4 87.6 121.2 167.5 227.4 309.2
Net benefits (ENPV) MEUR 880 -224.7 -212.7 -284.9 9.5 16.1 26.2 33.7 46.3 80.4 86.7 120.3 166.6 226.4 613.5
880
ERR 10.6%
B/C RATIO 2.51
The economic rate of return (ERR) is 10.6 %, and economic net present value (ENPV) is
EUR 880 million.
The following chart illustrates the weight of the benefit categories in the overall impact.
\110
VI Risk Assessment
Sensitivity analysis
The main purpose of the sensitivity analysis is to determine the ‘critical’ variables of the model. Such
variables are those whose variations, positive or negative, have the greatest impact upon the project’s
economic results.127
The ‘critical’ variables are conventionally considered those for which an absolute variation of 1 %
gives rise to a corresponding variation of not less than 1 % in the ENPV – elasticity is unitary or
greater.
VARIABLES Variation of ENPV
+1 % of variable -1 % of variable
Investment costs -1.01 % 1.01 %
Maintenance costs -0.02 % 0.02 %
Baseline traffic (without project) 1.3 % -1.3 %
Incremental traffic (induced by project) 0.2 % -0.2 %
Time savings 1.03 % -1.03 %
Savings of road VOC
Accident savings 0.5 % -0.5 %
Externalities
TOC savings 0.10 % -0.10 %
The variables identified as critical are thus (i) the traffic, (ii) the investment costs and (iii) the time
savings. These three variables are taken further to the switching value calculation and risk analysis.
Switching Values
For each critical variable a switching value has been computed, i.e. the value for which the ENPV
becomes zero, or in other words the maximum (negative) variation range over which the project
would be still breaking-even economically. The results are summarized in the following table.
CRITICAL VARIABLES Value for which
ENPV = 0
Investment cost 161 %
Baseline traffic - 36 %
Time savings -77 %
127 Only the impact upon the economic indicators is considered, since the results of the financial analysis are all negative and the switching
values for the financial indicators are well outside the normally expected range.
\111
The above values indicate that the project cost could be as much as 61 % higher than assumed, or the
baseline traffic can be 36 % lower than estimated, or the time savings 77 % lower than assumed, and
the project would still be economically breaking-even. This shows that the economic case of the
project is quite solid.
Although not very relevant for the financial indicators, given their highly negative profile, switching
values were calculated for the FNPV(C) to show the variation range required to reach financial break-
even.
CRITICAL VARIABLES Value for which
FNPV(C) = 0
Investment cost -95 %
Revenues +1952 %
O&M costs -4371 %
The above results confirm the very negative financial profile of the project – which would require huge
variations of the parameters – completely outside the realistic range – to reach break-even.
Risk analysis
Considering the particulars of the project, the following specific risks are considered.
Construction
The construction includes some technical challenges, e.g. replacement of existing tracks under railway
operation, construction/repair of 32 bridges, construction of 1.26 km of new tunnels. Works will
require the employment of technical expertise and capacity, as well as proper co-ordination and
supervision of activities.
Land acquisition
Land acquisition is an issue as the project includes some 26km of new alignment. However, the work
plan (to be included in the tender documents) provides for a staged handing-over of the site, starting
with the online sectors, whilst the expropriation procedure would be carried out in parallel. The
procedure should be also eased by the recent new expropriation law.
Maintenance
Maintenance is a key issue for the long and short term sustainability of the investment. Regular
maintenance is required in order to maintain the upgraded line in its design parameters (e.g.
160 km/h speed). Failure to ensure this would lead to speed restrictions which in turn would cancel
out the benefits of the investment.
Demand
A traffic risk is inherent to any transport infrastructure project. This is equally true for the baseline
traffic (without project) assumptions and for the incremental traffic (with project) forecasted.
The traffic risk also relates to the above factors as the improved level of service and efficiency gains for
users (and in turn the demand reaction) depends on the operators’ ability (both for passengers and
freight) to exploit the potential provided by the improved infrastructure for enhancing the level of
service provided.
The following matrix summarises the qualitative assessment of the above risks in terms of significance
and probability of occurrence.
\112
Risk Probability Impact Overall Mitigation measures Residual
risk risk
Contracting experienced
supervision services;
Construction risks D III High Medium
improving the staffing and
training of PMU
Staged handing-over of site
starting with the online
Land acquisition D III High
sections, in parallel with Low
finalising land acquisition
Maintenance budget for the
line to be increased, within a
Operation - maintenance C III Medium Low
wider network reform
programme
A parallel service
improvement programme to
be planned, including a more
Demand risk C IV High Medium
competitive passengers
timetable, new rolling stock,
etc.
Evaluation scale: Probability: A. Very Unlikely; B. Unlikely; C. About as likely as not; D. Likely; E. Very likely.
Severity: I. No effect; II. Minor; III. Moderate; IV. Critical; V. Catastrophic.
Risk level: Low; Moderate; High; Unacceptable.
The project promoter will need to carefully assess the above risks and plan appropriate mitigation
measures.
However, even with the assumed mitigation, the risk of construction cost overruns. In addition, the
risk of time savings not actually materialising cannot be excluded, therefore a quantitative risk
analysis was considered to add useful information.
Quantitative risk analysis
The quantitative risk analysis was performed using the following steps:
assigning the probability distributions to the critical variables identified above;
running a Monte Carlo simulation;
interpreting the results.
Probability distribution
Since no studies have been performed in the country thus far concerning the distribution of variables
such as investment costs, O&M expenses, traffic etc., the probability distributions of the critical
variables have been assigned based on a review of the international literature and practice.
Construction costs
Flyvberg et al. (2003) has investigated cost overruns for 167 large-scale transport infrastructure
projects. The tendency is clearly right skewed, where cost overruns are commonly occurring. In fact,
an average of 20 % cost overrun among the 167 road projects is calculated with the worst project
having a 223 % cost overrun and -33.6 % cost under-run.
Time savings
A triangular distribution with a minimum of -50 % of the variable, a most likely value of 0 % changes
in estimated value and a maximum value of +5 % was assumed.
\113
Baseline traffic
A Gauss profile distribution was assumed ranging from -50 % to +50 % with the mean of 0 % changes
in estimated value.
The risk analysis has been performed with a specialised software for 5,000 simulations. The technique
used is Monte Carlo simulation which involves a random sampling method of each different
probability distribution selected for the actual model set-up. The three variables are considered
independent of each other, so each ʻextractionʼ takes a random value for each variable to compute the
corresponding ERR. The distribution of the ERRs obtained is presented below:
The above chart indicates that there is a 99.8 % probability for the ERR to be higher than 5.5 %, from a
range of possible values starting from 4.4 % to 14.2 %.
The most likely value of ERR is 9.4 % with a standard deviation (quantifying the variation of the
results from the expected value) of 1.4 %.
The results of the risk analysis clearly reconfirm the strong economic case of the project.
\114
Case study – Urban Transport
I Project Description
City X is a medium sized city of 300 000 inhabitants. The motorised mobility in the city is ensured by
private transport as well as an extended bus network. The modal share in the city is 45 % public
transport (bus) and 55 % individual transport.
The residential area Y, 7 km North-East of the city centre, is rapidly expanding. Mobility demand is
increasing rapidly and the road connecting the residential area Y to the city centre/business area is
heavily congested at peak hours. To ease this situation, the City Transport Authority is proposing to
improve public transport connections to the city centre and implement a package of measures to
promote public transport and encourage modal shift, including:
Construction of 9 km of tram line (double track), with accompanying infrastructure (traffic
signalling, traction infrastructure, necessary road works), as well as a new tram depot;
Purchase of 15 new tram sets;
Implementation of a Traffic Management System (TMS), including Passenger Information
System at stops, integrated electronic ticketing, automatic vehicle location systems for public
transport, public transport priority.
In addition, existing bus services in the area will be redefined with a feeder function to the new line.
The public transport modal share is expected to improve, passing from the current 45 % to 47 %.
In this case study, time savings are expected in the transport system, due to the introduction of the
new tram system and the reorganisation of the bus services, for the traffic diverted from the bus
services and the individual cars to the tram. In addition, the impact of the shift to tram usage and the
re-organisation of bus services will also translate into lower pollutants emissions from traffic, thus
contributing to climate change mitigation128.
The institutional set up, in terms of relations between entities involved in project implementation and
operations, is briefly described below. The implications of this institutional set-up for the analysis of
cash flows, financial sustainability and assessment of State aid are duly taken into account in the rest
of the analysis and will be highlighted when relevant in this case study129.
The City is the project beneficiary. As beneficiary, the City will receive the EU grant, and also draw a
loan from an International Financing Institution (IFI) to co-finance the implementation of the project.
In addition, it will co-finance the remaining part with own resources.
The City holds the strategic management of the public transport system through the Transport
Authority, which is the budget unit of the City in charge of overall mobility policy130.
The City has entered a Public Service Contract (PSC) with the in-house Transport Operator. The PSC
establishes the responsibilities, modalities for operation and compensations for public transport
services. The contract is compliant with national and EU legislation regulating the provision of public
128 It is worth highlighting that these conclusions are case-study specific and are not necessarily applicable to all tramways projects. Specific
circumstances such as, for instance, construction impacts or the type of bus fleet available (diesel, hybrid, electric) should be considered in
order to understand the real incremental impact.
129 The institutional set-up of this case study must be taken as a mere illustrative example. Cities will select their own institutional solutions,
based on specific circumstances and relevant EU and national legislation. The concept that this case study wants to highlight is that the
implications of the selected institutional set up must be adequately reflected in the analysis of cash flows, financial sustainability and
assessment of State aid.
130 As illustrated in European Court of Auditors’ Special Report “Effectiveness of EU-supported public urban transport projects the for
projects subject to its approval”, 2014, the Commission and the Member States should always ensure that “the projects are included in a
mobility policy which: addresses the consistency of all modes and forms of transport, including parking policy, in the entire urban agglomeration;
demonstrates that it is a priority and the most appropriate project; indicates to what extent it will contribute to its overall objectives (e.g. modal
shift).
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service obligations131.
According to the PSC, the City will remain the owner of all the project assets (infrastructure, rolling
stock and TMS), which will be made available for use to the public Transport Operator against
payment of a lease. The City will also bear expenditures on replacements of project assets.
The Transport Operator holds the responsibility of operating and maintaining the project assets and
bears all associated expenditures.
II Project objectives
The general objective of the project is to ensure an efficient public transport service in the urbanised
areas of the City.
Specific objectives include:
reducing road traffic congestion, accidents and negative environmental impacts, positively
influencing the quality of urban life and the environment;
improving the quality of the public transport travel experience, through increased quality
standards;
shortening travel time of public transport of vehicles and passengers without worsening traffic
conditions.
As a secondary effect, it is expected that the project will also increase the attractiveness of the area
around the planned investment through increased public transport availability.
The project objectives are in line with the national, regional and municipal strategies related to the
overall territorial and spatial development as well as those related to the transport sector. In
particular, the project responds to a priority defined in the City’s multi-modal Mobility Plan, namely
identifying needs and solutions for urban mobility. The objectives of the project are also coherent with
the policies of the Commission on urban mobility132 and are well aligned with the objectives of the
Operational Programme Transport. In particular, the project will contribute to the achievement of the
following OP indicators:
Indicator OP Project
2023 target (% of OP target)
Output indicators
Total length of new or improved tram lines (km) 32 8 (40 %)
Result indicators
Incremental number of passengers using urban public 40 10 (25 %)
transport (M passengers/year) 400
III Demand and Options Analysis
Options analysis
In most transport projects different project options can generate different levels of traffic, so that a
detailed definition of project options precedes the demand analysis estimating and forecasting the
level of traffic for each of the project options.
The multi-modal Mobility Plan identified the need for improving the connections between residential
131 At the time of writing, the relevant reference is to Regulation (EC) No 1370/2007 on public passenger transport services by rail and by
road.
132 At the time of writing, the latest EC position is expressed by the Urban Mobility Package released on 17/12/2013, which central element is
the Communication "Together towards competitive and resource efficient urban mobility” (COM(2013) 913 final).
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area Y and the city centre as a priority, given the current heavily congested conditions and the
foreseeable worsening of the traffic burden due to the fact that residential area Y is expanding.
In the Mobility Plan, a first screening of available options, with a multi-modal perspective, was done
based on a Multi-Criteria Analysis (MCA). Selection criteria included technical feasibility, costs,
environmental impacts and social acceptability133. Based on this screening, alternative project options
such as the increase of road capacity by enlarging road infrastructure and the construction of an
alternative road connecting the area Y and the city centre were discarded. The public transport option
was considered the most effective and the number of alternatives was narrowed down to three, as
follows.
Option 1: strengthening of bus services with implementation of bus lanes and fleet renewal, as
well as implementation of TMSs with public transport priority.
Option 2: new tram line (7.5 km, along Alignment A running along the existing road) with tram
rolling stock purchase, re-organisation of bus services with a feeder function, as well as
implementation of TMSs with public transport priority.
Option 3: new tram line (9 km, along Alignment B, mostly along the existing road, but with a
small detour to allow another residential area along the way to be served) with tram rolling
stock purchase, reorganisation of bus services with a feeder function, as well as
implementation of TMSs with public transport priority.
The without-the-project (counterfactual) scenario, against which the project options are compared,
assumes a continuation of business as usual, maintaining the level of expenditures which would
guarantee the basic functionality of assets. This implies a slight worsening of the modal share of public
transport.
In the feasibility study a full CBA on all three project options was performed. Traffic forecasting was
done separately for each of the three options, and implications in terms of investment costs, O&M,
renewals, as well as benefits, were assessed separately. Option 3 was selected as it scored the highest
economic internal rate of return. This case study shows the CBA carried out for the selected option
only.
Transport demand
The demand analysis is carried out based on a multi-modal network traffic model (traffic diagnostic
and forecasting) owned by the City. The model is calibrated with data from the most recent
comprehensive traffic study (the Transport Authority carries out traffic surveys every 5 years). Model
results are used to inform both the financial and the economic analyses. Traffic forecasts were carried
out separately for the without-the-project scenario and for each of the three project options. Forecasts
were made for three years (year 4 – first full year of operations, year 15 and year 25) and linear
interpolation was used to forecast the remaining years. This case study shows the traffic forecasts
carried out for the selected option only.
It is assumed that the city is congested and with a high level of suburban living. The average trip length
is 7 km for buses and trams and 8 km for cars, while the average speed is 14 km/h for buses and 20
km/h for cars in the scenario without-the- project; and 14.3 km/h for buses, 19 km/h for trams and 20
km/h for cars in the scenario with-the-project (unchanged, since it is assumed that possible
congestion relief effects will be counterbalanced by the implementation of TMS with public transport
priority).
The traffic, after the traffic stabilisation and the corresponding shifts following project completion,
shows a moderate traffic growth rate of 2 % from the opening (year 4) to year 10, 1 % up to year 15
and no growth afterwards134. Demand data for the without-the-project scenario and for the selected
133 This list is only indicative. Selection criteria should reflect priorities and be decided by the Plan owner.
134The actual growth rates must be assessed on a case by case basis. Cautious assumptions are to be preferred in order to avoid
overestimation of benefits.
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option are summarised in the following table. All data are expressed in millions (m) passengers or
passengers-hours (h) per year.
Year 1 Year 4 Year 10 Year 15 Year 25
(start of (first full year of
construction) operation)
Without-the-project scenario
Passengers
Bus
42.4 45.0 50.2 52.7 52.7
Trams
- - - - -
Private transport
52.0 55.2 61.6 64.7 64.7
Passenger-h
Bus
21.2 22.5 25.1 26.4 26.4
Trams
- - - - -
Private transport
20.8 22.1 24.6 25.9 25.9
With-the-project scenario
Passengers
Bus
42.4 37.0 41.3 43.4 43.4
Trams
- 10.0 11.2 11.7 11.7
Private transport
52.0 53.7 59.9 62.9 62.9
Passenger-h
Bus
21.2 18.1 20.2 21.2 21.2
Trams
- 3.7 4.1 4.3 4.3
Private transport
20.8 21.5 24.0 25.2 25.2
Based on the traffic model results, demand in the with-the-project scenario has been qualified as
existing (i.e. passengers already travelling in the without-the-project scenario), diverted (i.e.
passengers diverted from bus and private cars to tram) and generated (i.e. passengers who were not
travelling in the without-the-project scenario). The model shows that, in the with-the-project scenario,
the incremental traffic (tram) is diverted from bus for 80 % of the total, diverted from individual
transport for 15 % and newly generated for 5 %.
Transport supply
The information on current transport supply and foreseeable changes as a consequence of the project
is provided by the Transport Operator and is compliant with the provisions on transport production as
laid out in the Public Service Contract signed between the Transport Authority and the Operator. The
planned supply is also compliant with the assumptions of the traffic model.
The following table summarises the main information about the current and planned public transport
supply (bus and trams) and the expected private transport production. All data are expressed in
millions (m) vehicles-km per year.
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Year 1 Year 4 Year 10 Year 15 Year 25
(start of (first year of
construction) operation)
Without-the-project scenario
Bus
9.6 9.6 9.6 9.6 9.6
Trams
- - - -
Private transport
346.4 368.0 410.4 431.3 431.3
With-the-project scenario
Bus
9.6 8.0 8.0 8.0 8.0
Trams
- 1.0 1.0 1.0 1.0
Private transport
346.4 358.0 399.2 419.6 419.6
IV Project Costs and Revenues of selected option
Investment Cost
The total cost of the project is estimated at EUR 160 million net of VAT (EUR 197 million gross),
based on tender prices (the tenders for the construction works and the rolling stock purchase have all
been awarded).
Total project costs Ineligible costs Eligible costs
(A) (B) (C)=(A)-(B)
Planning/design fees 3.0 - 3.0
Land purchase 5.0 - 5.0
Building and construction 73.0 - 73.0
Tram infrastructure (incl. tracks and 63.0 - 63.0
traction)
Tram depot 10.0 - 10.0
Plant and machinery or equipment 57.5 - 57.5
Tram rolling stock 37.5 - 37.5
Traffic Management System 20.0 - 20.0
Contingencies 14.5 - 14.5
Technical assistance - - -
Information and promotion 0.3 - 0.3
Contract supervision 6.5 - 6.5
Sub-TOTAL 159.9 - 159.9
VAT 36.8 36.8 -
TOTAL 196.6 36.8 159.9
The beneficiary completed the land purchase procedures (EUR 5 million)135. Contract supervision is
set at 5 % of construction and equipment expenditures (EUR 6.5 million).
Contingencies are set at 10 % of project cost, which seems reasonable given the type of project, its
state of advancement (tender awarded, works not started yet) and the associated residual risks.
The unit cost per km of tram line constructed (double track) appears reasonable if benchmarked with
that of similar projects in cities with comparable network conditions.
The unit cost of the tram rolling stock appears reasonable, taking into account the technical
specifications of the rolling stock purchased.
135 Purchase of land is for the section of the route which does not go along the existing road.
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Unit costs are specified below.
Investment component Unit cost Total cost
Tram infrastructure (9 km) EUR 7 m/km (double track) EUR 63 m
Tram rolling stock (15 tram sets) EUR 2.5 m/tram set EUR 37.5 m
VAT is set at 23 % and is fully recoverable for the City under national legislation.136 For this reason,
VAT is a non-eligible cost for the project.
Operation and maintenance cost
The O&M costs are borne by the Transport Operator. The following O&M unit costs have been used in
the analysis:
Project component O&M unit cost
Tram (infrastructure* and rolling stock) EUR 6 /tram vehicle-km
Bus rolling stock EUR 3/bus vehicle-km
* Including tracks and overhead line system.
Unit costs include traction (including a yearly amount earmarked for replacement of overhead lines),
maintenance and repair (including spare parts and excluding replacements), staff and other
administrative costs (including the lease for the use of project assets).
No real growth of costs has been considered (see section 2.8.4 of the guide).
The impacts of different project components on the O&M have been assessed separately, taking into
account O&M savings due to the reorganisation of the supply of bus services and the incremental O&M
due to the new tram system. Savings due to reduction of the supply of bus veh-km do not
counterbalance the increase of costs due to operating the new tram line and new rolling stock.
The project results in an overall increase in the O&M expenditures of EUR 1.2 million/year, resulting
from additional O&M costs of EUR 6 million/ year for the tram system and a reduction of O&M costs of
EUR 1.2 million/year for the bus system.
Replacements
The necessary replacements of the new infrastructure, rolling stock and TMS have been considered
during the reference period of the project (25 years), based on the economic life of the individual
project assets, which were assumed to be as follows:
Investment component Economic life Replacement during reference
period in % of initial investment
Tram infrastructure 30 years -
Tram rolling stock 20 years 33 % every 10 years
TMS 8 years 100 %
Based on the provisions of the PSC, the replacement costs are borne by the City (project
beneficiary)137.
Residual value
The project does not generate net revenues (operating costs higher than operating revenues). The
136 The beneficiary pays VAT on the purchase of project assets (input VAT) and receives a payment from the Transport Operator for the use of
the project assets in the form of a lease, which is also a transaction subject to VAT (for the beneficiary, output VAT). Based on this scheme, the
VAT is found recoverable under national legislation, hence not eligible.
137 Replacement of overhead lines is in this case study treated as an yearly expenditure born by the Transport Operator in the context of tram
infrastructure and rolling stock O&M.
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residual value of the investment is hence calculated based on the net book accounting method. The
depreciation rates of the various investment components (taking into account the replacements) are
as follows:
Investment component Depreciation rate
Tram infrastructure 3.5 %
Tram rolling stock 5.5 %
TMS 13 %
Revenues
Project revenues stem from user fares and, based on the existing institutional set-up, accrue to the
Transport Operator. The public transport ticketing system is integrated between buses and trams.
The average ticket per passenger is EUR 0.33 /passenger, which in the first year of operations results
in an incremental inflow of EUR 0.7 million. The pricing policy will not change, i.e. tariffs will remain at
the same level with and without the project138. Traffic diverted from bus will not contribute to increase
of revenues, since the users were already paying a ticket before. The increased revenues come from
road users diverted to public transport and from generated users.
Unit Year 4 Year 10 Year 15 Year 25
(first year of
operation)
Traffic diverted from road m EUR 0.5 0.6 0.6 0.6
Generated traffic m EUR 0.2 0.2 0.2 0.2
Total revenues m EUR 0.7 0.7 0.8 0.8
The fare-box recovery ratio, i.e. the share of operating expenses recovered through user fares, is
expected to be around 52 % in the first year of operations.
Compensations for public service obligations
Compensations are provided by the Transport Authority to the Operator in the framework of the PSC.
The contract is on a net basis, i.e. the Operator bears both the cost risk and the revenue risk. The
Transport Authority pays compensations to the Transport Operator as a price per vehicle-km
produced (bus and tram), net of the revenues collected from user fares139. The existing PSC has been
found compliant with European Commission Regulations on the provisions of services of general
economic interest, so that the operating State aid, if granted according to the PSC provisions, can be
considered compatible with market rules140.
Compensations are not a cash flow in the consolidated financial analysis (inflow for the Operator,
outflow for the Transport Authority). However, they will be used in the financial sustainability
assessment.
Loan conditions
The beneficiary negotiated a loan with an IFI of EUR 15 million. The conditions agreed for the loan
138 This is, again, an illustrative assumption. The actual existing and planned pricing policy must be assessed by the analyst.
139 As indicated above for the selected institutional set up, the indication of the type of PSC (gross/net) is here only illustrative, to the
purposes of the case study. In general, the provisions of the PSC are defined between the parties in compliance with State aid rules. Each
feasibility study should analyse in depth the institutional set-up, including the relations between the City and the Transport Operator, as
described in the provisions of the PSC (if in place) and take into account the implications in the financial analysis, the sustainability analysis,
the assessment of State aid implications and wherever relevant.
140 At the time of writing, the relevant reference is to Regulation (EC) No 1370/2007 on public passenger transport services by rail and by
road. The method and indicators to demonstrate the absence of overcompensations and undue State aid must be compliant with the
applicable legislation at the time of carrying out the analysis.
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include a maturity period of 15 years (including three years grace period during construction and 15
years for principal repayment, which starts in the first year of operation) and an interest rate of 3.5 %
in real terms. The cash flows related to the debt service are used in the calculation of the financial
return on national capital (FNPV(K)).
V Financial and Economic Analyses
The financial and economic CBA is done in conformity with European and national guidelines for the
preparation of the cost-benefit analysis of major investment projects.
The following key assumptions have been used in the analysis:
the CBA is based on an incremental approach;
the analysis consolidates cash flows between the Transport Authority (owner of all project
assets and bearing replacement cost) and the Transport Operator (using project assets against
payment of a lease and bearing O&M costs);
contingencies are excluded from the financial and economic analyses and only considered in
the assessment of the financial sustainability.
the reference period for the analysis has been set at 25 years based on the average life of
assets, including both implementation (three years) and operations (22 years);
the financial and economic analyses are carried out at constant prices. For cash flows in real
terms, a 4 % discount rate in real terms is used in the financial analysis and 5 % in the
economic analysis;
VAT is fully refundable under national legislation and therefore not eligible. Thus, the financial
analysis is carried out on cash flows net of VAT;
the residual value is calculated on the basis of the residual non-depreciated accounting value;
the most recent macroeconomic forecasts were adopted, based on national statistics;
the necessary expenditure on assets renewal has been properly recognised in the future
project cash flows as operating costs, also for the purposes of the calculation of the pro-rata
application of discounted net revenue..
Financial analysis
The assessment of the PSC and the financial impacts of the project highlight compliance with European
Commission Regulations on the provisions of services of general economic interest141 and that aid
provided in the form of compensation to the in-house Transport Operator will remain a compatible
State aid, thus not requiring notification to the European Commission’s DG Competition.
Even if the project generates revenues paid by users (in the form of user fares), the project’s net
revenue (difference between the incremental operating revenues and O&M costs) is negative, which is
why Article 61 of Regulation (EU) No 1303/2013 does not apply here.
141 At the time of writing, the relevant reference is to Regulation (EC) No 1370/2007 on public passenger transport services by rail and by
road.
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1 2 3 4 5 10 15 20 25
EU GRANT
Construction Operation
Calculation of Discounted Investment Cost (DIC) NPV 4%
Investment cost M EUR 139.8 48.8 48.3 48.3 0.0 0.0 0.0 0.0 0.0 0.0
DISCOUNTED INVESTMENT COST (DIC) M EUR 139.8 48.8 48.3 48.3 0.0 0.0 0.0 0.0 0.0 0.0
Calculation of Discounted Net Revenues (DNR) NPV 4%
Revenues M EUR 9.9 0.0 0.0 0.0 0.7 0.7 0.7 0.8 0.8 0.8
O&M costs M EUR -16.0 0.0 0.0 0.0 -1.2 -1.2 -1.2 -1.2 -1.2 -1.2
Replacements M EUR -38.6 0.0 0.0 0.0 0.0 0.0 -20.0 0.0 0.0 0.0
Residual value of investments M EUR 11.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 30.1
DISCOUNTED NET REVENUES (DNR) M EUR -33.0 0.0 0.0 0.0 -0.5 -0.5 -20.5 -0.4 -0.4 29.7
ELIGIBLE COST (EC): M EUR 159.9
CO-FINANCING RATE OF PRIORITY AXIS (CF): 85%
EU GRANT ( = EC x CF): M EUR 135.9
In this case, the EU contribution has been calculated by multiplying the eligible costs shown in section
IV above (EUR 159.9 million) by the co-financing rate of the relevant priority axis (85%), which results
in an EU grant of EUR 135.9 million. In addition to the EU grant, the beneficiary will contract a loan of
EUR 15 million and will contribute with own funds with EUR 45.7 million. The beneficiary will also
ensure the pre-financing of the VAT (EUR 36.8 million), which is however recoverable. The financing
structure of the project is described below:
Financing Sources m EUR % share
EU grant 135.9 69 %
IFI loan 15.0 8%
Project beneficiary’s contribution 45.7 23 %
of which VAT 36.8 19 %
Total 196.6 100 %
The financial profitability of the investment (as indicated by FNPV(C) and FNPV(K)) is negative, as
expected for a project where project operating revenues are lower than the operating expenditures
(including renewals and maintenance), which is typical in the urban public transport sector. The table
that follows shows the results of the financial analysis.
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1 2 3 4 5 10 15 20 25
FRR(C)
Construction Operation
Return on Investment NPV 4%
Investment cost M EUR -139.8 -48.8 -48.3 -48.3 0.0 0.0 0.0 0.0 0.0 0.0
Revenues M EUR 9.9 0.0 0.0 0.0 0.7 0.7 0.7 0.8 0.8 0.8
O&M costs (incl. replacements) M EUR -54.6 0.0 0.0 0.0 -1.2 -1.2 -21.2 -1.2 -1.2 -1.2
Residual value of investments M EUR 11.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 30.1
Project cash-flow M EUR -172.8 -48.8 -48.3 -48.3 -0.5 -0.5 -20.5 -0.4 -0.4 29.7
FRR/C (before EU grant) -12.26%
1 2 3 4 5 10 15 20 25
FRR(K)
Construction Operation
Loan Balance
Beginning balance M EUR 0.0 5.0 10.0 15.0 14.2 9.9 4.8 -0.0 -0.0
Loan disbursements M EUR 5.0 5.0 5.0 0.0 0.0 0.0 0.0 0.0 0.0
Interest payments M EUR 0.0 0.2 0.4 0.5 0.5 0.3 0.2 0.0 0.0
Principal repayments M EUR 0.0 0.0 0.0 0.8 0.8 1.0 1.1 0.0 0.0
Ending balance M EUR 5.0 10.0 15.0 14.2 13.4 9.0 3.6 -0.0 -0.0
National Financing Sources
Project beneficiary's contribution to investment costs M EUR 3.4 2.8 2.8 0.0 0.0 0.0 0.0 0.0 0.0
Return on National Capital NPV 4%
Project beneficiary's contribution to investment costs M EUR -8.7 -3.4 -2.8 -2.8 0.0 0.0 0.0 0.0 0.0 0.0
Loan interest payments M EUR -3.9 0.0 -0.2 -0.4 -0.5 -0.5 -0.3 -0.2 0.0 0.0
Loan principal repayments M EUR -10.0 0.0 0.0 0.0 -0.8 -0.8 -1.0 -1.1 0.0 0.0
O&M costs (incl. replacements) M EUR -54.6 0.0 0.0 0.0 -1.2 -1.2 -21.2 -1.2 -1.2 -1.2
Revenues M EUR 9.9 0.0 0.0 0.0 0.7 0.7 0.7 0.8 0.8 0.8
Residual value of investments M EUR 11.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 30.1
National cash-flow M EUR -55.5 -3.4 -3.0 -3.2 -1.8 -1.8 -21.8 -1.7 -0.4 29.7
FRR/K (after EU grant) -11.16%
The analysis of the financial sustainability at the project level aims to assess whether the project is
able to balance out its positive and negative cash flows during the reference period. The analysis
shows that the project implementation costs are covered by means of the EU grant, a loan and the
beneficiary’s own contribution. As can be expected for such projects, negative cash flows will be
generated during project operations. In order for the project to be sustainable, the balance between
inflows and outflows must be reached by means of increased compensation by the City within the
framework of the PSC. As can be seen below, in its financial plans the city committed to increase
compensation to the extent that it covers the expected operating losses of the transport operator, so
that there is robust evidence that the financial sustainability of the project can be ensured.
1 2 3 4 5 10 15 20 25
FINANCIAL SUSTAINABILITY - PROJECT
Construction Operation
Financial sustainability
Project beneficiary's contribution to investment costs M EUR 3.4 2.8 2.8 0.0 0.0 0.0 0.0 0.0 0.0
Project beneficiary's contribution to loan repayment M EUR 0.0 0.2 0.4 1.3 1.3 1.3 1.3 0.0 0.0
EU grant M EUR 45.3 45.3 45.3 0.0 0.0 0.0 0.0 0.0 0.0
Loan disbursement M EUR 5.0 5.0 5.0 0.0 0.0 0.0 0.0 0.0 0.0
Revenues M EUR 0.0 0.0 0.0 0.7 0.7 0.7 0.8 0.8 0.8
Incremental compensations under Public Service Contract M EUR 0.0 0.0 0.0 0.5 0.5 20.5 0.4 0.4 0.4
Total cash inflows M EUR 53.7 53.3 53.5 2.5 2.5 22.5 2.5 1.2 1.2
Investment cost M EUR -53.7 -53.1 -53.1 0.0 0.0 0.0 0.0 0.0 0.0
O&M costs (incl. replacements) M EUR 0.0 0.0 0.0 -1.2 -1.2 -21.2 -1.2 -1.2 -1.2
Loan interest payments M EUR 0.0 -0.2 -0.4 -0.5 -0.5 -0.3 -0.2 0.0 0.0
Loan principal repayments M EUR 0.0 0.0 0.0 -0.8 -0.8 -1.0 -1.1 0.0 0.0
Total cash outflows M EUR -53.7 -53.3 -53.5 -2.5 -2.5 -22.5 -2.5 -1.2 -1.2
Net cash-flow M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Cumulated net cash-flow M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
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The assessment of the financial sustainability of the project for the beneficiary aims to understand
whether the City will have sufficient funds for financing the own capital contribution to project costs,
the repayment of the loan and the planned amount of compensation in the framework of the PSC. The
City of X explicitly allocated in the multi-annual financial forecasts a sufficient amount of funds to
cover own contribution, including capital expenditures, the debt service for the project loan and the
pre-financing of the VAT142. In addition, the payment of yearly compensation under the PSC is
explicitly mentioned as a long-term financial commitment in the multi-annual financial forecasts, with
a specific yearly financial allocation. Under these conditions, the financial sustainability of the project
for the beneficiary is secured.
The assessment of the financial sustainability of the project for the Transport Operator aims to
understand whether the operator will have sufficient funds to operate the project asset, ensuring an
adequate level of service and standard of maintenance. Total inflows and outflows for the Transport
Operator after the implementation of the project have been compared and are shown in the table
below.
1 2 3 4 5 10 15 20 25
FINANCIAL SUSTAINABILITY - TRANSPORT OPERATOR
Construction Operation
Financial sustainability
Revenues M EUR 428.8 14.0 14.3 14.6 15.5 15.8 17.3 18.2 18.2 18.2
Compensations under Public Service Contract M EUR 317.6 14.8 14.5 14.2 14.5 14.2 12.7 11.8 11.8 11.8
Total cash inflows M EUR 746.4 28.8 28.8 28.8 30.0 30.0 30.0 30.0 30.0 30.0
O&M costs (excl. replacements) M EUR -746.4 -28.8 -28.8 -28.8 -30.0 -30.0 -30.0 -30.0 -30.0 -30.0
Total cash outflows M EUR -746.4 -28.8 -28.8 -28.8 -30.0 -30.0 -30.0 -30.0 -30.0 -30.0
Net cash-flow M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Cumulated net cash-flow M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Based on the assumptions made concerning the expected inflows and outflows, the table above clearly
shows that the project operations will be sustainable for the Transport Operator thanks to the
provision of compensation under the PSC. As described before, the inflow of operating compensation
is reasonably secured in the long-term financial forecasts of the City. Under these conditions, the
financial sustainability of the project for the Transport Operator is secured.
Socio-economic analysis
The socio-economic analysis includes the following impacts:
Costs (-) Benefits (+)
Investment costs Consumer surplus:
Replacements (paid by the City) - Travel time savings
Producer surplus (-): - Vehicle operating costs savings (road users)
- O&M (paid by the Transport Operator) - Fares
- Fares Externalities
- Operating costs (tram) - Accidents savings
- Air pollution reduction
- Reduction of impact on climate change
- Noise impacts reduction
Conversion factors were estimated based on national statistics on the average composition of project
costs and shadow wage (for labour costs) and share of taxation (for energy costs). The correction
factors are0.9 for investment costs and 0.85 for O&M.
142 The multi-annual financial forecasts of a municipality usually cover a period shorter than the reference period used in CBA. It is however
important to verify that, for at least the duration of the multi-annual financial forecasts, the City has made the necessary financial
commitment.
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As described in section III on demand analysis, the multi-modal traffic model provides information on
the generalised costs for users of public transport and individual cars, without and with the project. It
is therefore possible to calculate the consumer surplus as the difference in generalised costs of the trip
(including time savings and fares) for both existing traffic and traffic diverted from the origin mode
(private car, bus) to the destination mode (tram). Benefits to generated traffic are calculated via the
Rule of Half143. The main assumptions and parameters used for the calculation of the costs and benefits
are summarised below.
Investment costs and replacements.
Investment costs and replacements are included in the economic analysis at their economic value, i.e.
conversion factors are applied to net financial cash flows to correct for the opportunity cost of
labour144.
Producer surplus.
For the calculation of the producer surplus, the revenues accruing to the Operator have been
compared to the Operator’s O&M costs. In this case study, the producer surplus is negative and
therefore a cost to the project, since the incremental revenues are lower than the incremental costs.
Consumer surplus
Travel time
Impacts on travel time are calculated based on the information provided by the traffic model on door-
to-door travel time145.
The project results in an overall decrease in travel time in the transport system (reduction of
passenger/h), mainly due to time savings for bus users and car drivers diverting to the newly
introduced tram mode. In this project, existing car users remaining in the road mode will not
experience time savings, since it is expected that the project will not generate any significant increase
in road capacity (the possible reduction of road congestion and increase of car speed due to traffic
diversion to tram will be counterbalanced by the limitation of road capacity due to the implementation
of a new surface transport mode, such as the tramway, as well as the implementation of the Traffic
Management System, heavily oriented towards the public transport priority).
The table below summarises the impact on travel time, in million passenger/h.
Year 4 Year 10 Year 15 Year 20 Year 25
(first year of
operation)
Existing traffic -0.4 -0.4 -0.5 -0.5 -0.5
Bus -0.4 -0.4 -0.5 -0.5 -0.5
Private transport - - - - -
Diverted traffic -1.1 -1.2 -1.3 -1.3 -1.3
Bus to tram -1.1 -1.2 -1.2 -1.2 -1.2
Private transport to tram 0.0 -0.1 -0.1 -0.1 -0.1
Total -1.5 -1.7 -1.7 -1.7 -1.7
143 It must be noted that, in specific circumstances, the treatment of diverted traffic in the economic analysis can differ from this case study,
see e.g. the railways case study. Chapter 5 of the CBA Guide must be referred to for a more exhaustive description of the recommended
approach to the treatment of benefits to diverted traffic.
144 Conversion factors were estimated based on the share of labour costs on construction and operating costs and the conversion factors as
provided in Annex IV of the guide.
145 Ideally, the traffic model should enable assessment not only in-vehicle time, but rather door-to-door travel time, including waiting time
and interchanges. If appropriate research on value of time is available, the economic analysis could value waiting time/interchanges
differently from in-vehicle time.
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The following parameters have been adopted for the estimation of value of time:
Travel purpose Share of trips by travel purpose Value of time (EUR/h)
Public transport Private transport Public transport Private transport
Work 35 % 45 % 9 11
Non-work 65 % 55 % 3.6 4.4
The cost saving approach has been adopted to estimate the unit VOT for work trips. Labour costs have
been estimated based on national statistics. Unit VOT for non-work travel time has been calculated
applying ratios respectively of 0.4 to work VOT. The share of trips by travel purposes is based on the
most recent traffic surveys.
Unit values escalate over time with an elasticity of 0.7 to GDP growth per capita.
Vehicle operating costs savings (VOC)
The avoided VOC for the users switching from cars to public transport due to the project (diverted
users) are counted as a benefit.
The adopted unit VOC is EUR 0.3 /car veh-km, based on national statistics and taking into account fuel
costs (depending on road alignment and traffic conditions) and wear and tear of vehicles (oil, tyres,
vehicle maintenance and depreciation). The unit VOC is applied to the amount of cars (vehicle-km)
saved in the project option.
The VOC savings associated with the reorganisation of bus services (resulting in a reduction of the bus
supply in vehicle-km) are accounted for in the Operator’s O&M costs.
Benefits to generated traffic
The traffic model shows that 5 % of the incremental tram trips will be newly generated in the
transport system. This will represent an increase of 2 % of the total motorised mobility in the city
(including public and private transport).
The benefits to generated traffic have been estimated according to the Rule of Half146. The half of the
generalised costs for existing users has been taken (including VOT and fares) and multiplied by the
amount of generated users.
Externalities
Accidents
The traffic diversion from cars to public transport is expected to reduce the number of accidents on
the roads, via the reduction of distance travelled by road (reduction of vehicle-km).
The adopted probability of accidents, number of casualties, fatalities and injuries are taken from
national studies and statistics.
Based on national statistics, the Value of Statistical Life (VOSL) has been estimated at EUR 400 000 per
fatality and EUR 65 000 per injury. In addition, a value of EUR 13,500 per casualty has been estimated
to cover direct medical and administrative costs associated with accidents.
Unit values escalate with GDP growth per capita, with an elasticity of 0.7.
Noise
Noise costs associated with the project have been estimated, taking into account the difference in noise
146 See section 5.8 of the CBA Guide.
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levels due to transport activity related to tram, bus and individual cars. The number of people exposed
to noise and the level of exposure with and without the project were assessed based on the noise maps
produced during the environmental impact assessment. This estimation takes into account the type of
noise source, the morphology of the territory, building patterns and the expected transport activity
changes.
Based on the assessment, the project is expected to reduce overall noise levels. This, on the one hand,
is due to the fact that the newly introduced tram mode will adopt anti-noise construction techniques
on both the tram tracks and the trams, thus limiting noise emission and, on the other hand is due to
the reduced level of traffic on roads (reduction of cars and buses).
The unit cost (EUR/year/person exposed) is identified based on national stated preference surveys
and is related to the level of annoyance generated by a given level of sound emission and escalates
with GDP growth per capita, with an elasticity of 0.7.
The differential noise cost is estimated multiplying the amount of persons exposed in the without and
with-the-project scenario by the unit cost corresponding to the levels of noise in the without and with–
the-project scenario.
Air pollution
A reduction of the environmental burden is expected due to traffic diversion from road-based modes
(cars and buses) to trams, which generate a reduction of fuel consumption and hence lower air
pollutant emissions. Tram operations are not expected to generate air pollution at the point of use. The
indirect environmental impacts of the upstream process of energy production are taken into account
in the assessment of climate change (see below).
It is assumed that there are national guidelines, based on clear assumptions and methodology,
providing unit monetary costs of air pollution147 per vehicle-km, disaggregated by mode of transport
and speed. In this case, the calculation of the impact was made based on the following steps148:
quantification of the incremental transport production, in vehicle-km, by mode (tram, bus,
individual transport);
multiplication by a unit cost (EUR/vehicle-km).
The following monetary values per vehicle-km were taken into account for the calculation of air
pollution impacts (based on national studies):
for bus transport, EUR 0.37 /vehicle-km (for speed between 11 and 20 km/h, in urban area);
for road transport, EUR 0.03 /vehicle-km (for speed between 21 and 30 km/h, in urban area).
Unit values escalate with GDP growth per capita, with an elasticity of 0.7.
Climate change
The variation of CO2 emissions due to the project is calculated, as well as its economic value.
Emissions for tramways, which are electrically powered, are assessed in relation to the upstream
process of production of the required increase in electric energy. These emissions do not happen at the
point of use of the tramway, but at the point of production of energy and depend on the national
energy mix.
In summary, although a small increase of CO2 emissions is expected due to the increase of electricity
consumption for tram operations (emissions related to energy production), the project will lead to an
overall (incremental) reduction of CO2 emissions,
The calculation of the economic impact of CO2 emissions for road based modes was made based on the
147 The most important transport-related air pollutants are: particulate matter (PM 10, PM2.5); nitrogen oxide (NOx); sulphur dioxide (SO2);
volatile organic compounds (VOC) and Ozone (O 3) as an indirect pollutant.
148 Please see section 3.8.6 of this guide for more extensive methodological guidance.
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following steps:
quantification of the incremental transport production, in vehicle-km, by mode;
multiplication of the incremental vehicle-km by an emission factor (gCO2/v-km) to calculate
the incremental emission of CO2;
multiplication of the total amount of CO2 emitted by a unit cost (EUR/tonne);
The calculation of the economic impact of CO2 emissions for tramways was made based on the
following steps:
quantification of the marginal energy consumption (KWh/train-km);
multiplication of the total incremental energy consumption (in KWh) by a national average
emission factor (gCO2/KWh) to calculate the incremental emission of CO2;
multiplication of the total amount of CO2 emitted by a unit cost (EUR/tonne).
The following emission factors were taken into account for the calculation of the economic impacts of
CO2 emissions for road based modes and tramways (respectively, based on national studies and on
international research):
for bus transport, 1,133.2 gCO2/v-km (corresponding to a Euro III bus);
for road transport, 347.4 gCO2/v-km (corresponding to Euro III 1.4 cc gasoline unleaded);
for tram transport, 5 KWh/train-km and 496 gCO2/KWh (energy consumption per train-km
and CO2 emissions per KWh depend on, respectively, project specific and country data).
The adopted unit costs per tonne of CO2 are in line with the ‘central’ values suggested in the general
part of this guide. Following the recommendations made in section 2.9.9, the 2010 value and the
annual adders are first converted to constant 2013 prices and for the years beyond 2030, the adders
are continued at the 2011 to 2030 rate.
The results of the economic analysis are described below:
1 2 3 4 5 10 15 20 25
ERR
Construction Operation
Socio-economic costs NPV 5.0%
C1. Project investment cost M EUR -110.3 -43.4 -43.4 -43.4 0.0 0.0 0.0 0.0 0.0 27.1
C2. Replacements (City) M EUR -27.6 0.0 0.0 0.0 0.0 0.0 -17.0 0.0 0.0 0.0
C3. Producer surplus (Transport Operator) M EUR -3.2 0.0 0.0 0.0 -0.4 -0.3 -0.3 -0.2 -0.2 -0.2
C3a. Fares M EUR 8.4 0.0 0.0 0.0 0.7 0.7 0.7 0.8 0.8 0.8
C3b. O&M costs M EUR -11.6 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
Total economic costs (C1+C2+C3) M EUR -141.1 -43.4 -43.4 -43.4 -0.4 -0.3 -17.3 -0.2 -0.2 26.8
Socio-economic benefits NPV 5.0%
Consumer surplus
B1. Value of time M EUR 115.2 0.0 0.0 0.0 8.3 8.5 9.8 10.9 11.4 12.1
B2. Vehicle Operating Costs (individual transport) M EUR 40.7 0.0 0.0 0.0 3.2 3.3 3.6 3.8 3.8 3.8
B3. Fares M EUR -8.4 0.0 0.0 0.0 -0.7 -0.7 -0.7 -0.8 -0.8 -0.8
B4. Benefits to generated traffic M EUR 23.0 0.0 0.0 0.0 1.7 1.7 2.0 2.2 2.3 2.4
Externalities
B5. Accidents M EUR 2.8 0.0 0.0 0.0 0.2 0.2 0.2 0.3 0.3 0.3
B6. Environment M EUR 12.9 0.0 0.0 0.0 1.0 1.0 1.1 1.2 1.3 1.3
B6a. Air pollution M EUR 11.2 0.0 0.0 0.0 0.9 0.9 1.0 1.0 1.1 1.1
B6b. Climate change M EUR 1.6 0.0 0.0 0.0 0.1 0.1 0.1 0.2 0.2 0.2
B7. Noise M EUR 3.6 0.0 0.0 0.0 0.3 0.3 0.3 0.3 0.3 0.4
Total economic benefits (B1+B2+B3+B4+B5+B6+B7) M EUR 189.8 0.0 0.0 0.0 13.9 14.3 16.2 17.8 18.6 19.4
Net benefits (ENPV) M EUR 48.7 -43.4 -43.4 -43.4 13.5 14.0 -1.0 17.5 18.3 46.3
ERR 8.3%
B/C RATIO 1.35
\129
VII Risk Assessment
Sensitivity analysis
A sensitivity analysis of the economic and financial profitability was carried out in order to identify
under which circumstances the project becomes, respectively, economically unprofitable, if any, or
financially profitable, if any. The analysis is carried out using disaggregated variables (i.e. demand and
prices separately) to better identify possible critical variables.
The sensitivity analysis was carried out for the following variables:
Sensitivity of financial profitability Sensitivity of economic profitability
Investment costs Investment costs
O&M unit costs O&M unit costs
Traffic demand - incremental Traffic demand - incremental
Revenues (unit tariff) Value of Time (unit cost)
Vehicle operating costs (unit cost)
Air pollution (unit costs)
Climate change (CO2 emissions) (unit cost)
Accidents (unit costs)
Noise (unit cost)
Critical variables are defined as critical if a 1% change leads to a change of FNPV/ENPV equal to or
higher than 1% (elasticity higher than 1). The estimated elasticity of the ENPV and FNPV(C) with
respect to a 1% increase of the critical project variables is shown in the table below:
Variable ENPV elasticity FNPV(C) elasticity
Investment costs ±1% ±2.8% -1.0%
Traffic demand (incremental) ±1% ±3.1% -
Value of Time (unit cost) ±1% ±2.8% -
Based on the analysis, only investment costs were found to be critical for the sensitivity of financial
profitability. Regarding sensitivity testing of the economic profitability, the following variables were
found to be critical: incremental traffic demand, investment costs and unit Value of Time. Switching
values are calculated as follows:
Variables Switching value
(ENPV = 0)
Investment costs +35%
Traffic demand -32%
Value of Time -36%
Spider diagrams illustrating the elasticity (line gradients) and switching values (line intersection with
X axis) for the above mentioned variables are depicted below.
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Financial profitability sensitivity Economic profitability sensitivity
140.0
-90.0 40% 60% 80% 100% 120% 140% 160%
120.0
-110.0
100.0 Investment cost
-130.0 O&M unit costs
80.0
Traffic (incremental)
FNPV/C (Meur)
ENPV (mEUR)
-150.0 Investment cost
60.0 Unit value of time
O&M unit costs
-170.0 Unit VOC
Traffic (incremental) 40.0
Unit air pollution cost
-190.0 Unit fare 20.0
Unit climate change cost
-210.0 0.0 Unit accident cost
40% 60% 80% 100% 120% 140% 160% Unit noise cost
-230.0 -20.0
-250.0 -40.0
Change in the variable Change in the variable
None of the above switching values seem to realistically threaten the assessment of the project
financial and economic profitability. The risk analysis below analyses the main risk factors related to
traffic forecasts and to investment costs, identifying the risk prevention/mitigation measures
implemented (or to be implemented) by the beneficiary. Concerning VoT, a reduction of such an entity
as to make the NPV null (-36%) is considered not realistic, given the macro-economic forecasts
adopted for the project (it is here reminded that, in this case study, the VoT is calculated based on
resource costs, i.e. labour cost).
Risk analysis
A qualitative risk analysis has been carried out by the Beneficiary, with the aim to identify the main
risks related to project implementation as well as operations. In addition, the main risk prevention and
mitigation strategies are described.
Risk Probability Severity Risk level Risk prevention / mitigation measures Residual
description risk
(P) (S) (=P*S)
Administrative risks
Problems with The need for land purchase is reduced to a
land purchase minimum since the new line will mostly run
and acquisition B II Low on the existing road. The needed None
of rights of way expropriation procedures are completed.
Function in charge: Beneficiary.
Establishment of a Project Implementation
Delays due to Unit with adequate resources within the
administrative Beneficiary structure, in charge of timely
procedures B II Low liaising with the relevant Low
(permits, institutions/departments for timely
tenders, etc.) finalisation of the needed procedures.
Function in charge: Beneficiary.
Involve JASPERS technical assistance
Late availability early in the project cycle. Negotiation of a
st
of EU grant co- B II Low loan available as of 1 year of construction Low
financing Function in charge: managing authority and
Beneficiary.
Construction risks
Cost budget compared with relevant
benchmarking to correct possible optimism
bias. Publication of contract notices in the
Investment cost Official Journal of the EU to ensure wider
C III Moderate competition. Selection of a professional Low
overrun
external Construction Supervisor, with
adequate budget.
Function in charge: Beneficiary.
\131
Risk Probability Severity Risk level Risk prevention / mitigation measures Residual
description risk
(P) (S) (=P*S)
Delays due to Selection of contractors in line with
contractors procurement legislation, including quality in
(failure to meet the awarding criteria (not only lowest price).
contractual Close monitoring of contracts by PIU and
deadlines, by means of an external professional
withdrawal, Construction Supervisor, with adequate
bankruptcy, budget.
etc.). For rolling C III Moderate Low
stock and Function in charge: Beneficiary.
equipment, this
relates to both
construction and
provision.
Environmental and social risks
The environmental procedure has been
completed according to high quality
Impacts on air standards and can be reasonably
pollution, noise considered comprehensive and complete.
and climate Mitigation Measures have been identified in
B III Moderate Low
change the EIA, applying especially to the
exceeding construction phase, and will be
expectations. implemented by the Beneficiary.
Function in charge: Beneficiary.
The public has been duly involved during
the development of the EIA procedure and
Public opposition A II Low public notice has been given of all relevant Low
decisions.
Function in charge: Beneficiary
Operational risks
The operating costs forecasts have been
Increase of made based on the company historic costs
operating costs as well as reasonable benchmarks, in order
higher than to reduce optimism bias.
planned
The PSC provisions are based on these
compensations, B III Moderate Low
forecasts, and provide for mechanisms of
leading to
adjustment to changes of operating costs.
liquidity
problems for the Function in charge: Beneficiary and
operator Operator in charge of ensuring correct
functioning of PSC
Significant Adequate information and promotion
shortfall in measures to support modal shift.
expected Conservative demand forecasts, also
incremental factoring in the impacts of the current
public transport economic downturn.
B IV Moderate Low
demand (implies
lower benefits, Function in charge: Beneficiary.
lower revenues,
need for higher
compensations)
The Transport Authority and the Operator
have signed a Public Service Contract,
Transport supply providing a clear framework for the
not provided provision of transport services, including
B III Moderate Low
according to planned production, quality standards and
forecasted levels penalties for non-performance. In addition,
the Operator is implementing management
tools to monitor the quality of services and
\132
Risk Probability Severity Risk level Risk prevention / mitigation measures Residual
description risk
(P) (S) (=P*S)
the level of user satisfaction (e.g. via user
satisfaction surveys).
Function in charge: Beneficiary (Transport
Authority)
Evaluation scale: Probability: A. Very Unlikely; B. Unlikely; C. About as likely as not; D. Likely; E. Very likely.
Severity: I. No effect; II. Minor; III. Moderate; IV. Critical; V. Catastrophic.
Risk level: Low; Moderate; High; Unacceptable.
The results of the sensitivity and risk analyses indicate that the project overall risk level is low to
moderate. The planned strategies to prevent the occurrence of the identified risks and/or mitigate
their adverse impact are expected to bring project risk to a lower level. The residual project risks can
be considered acceptable.
\133
4. Environment
The flagship initiative for a resource-efficient Europe establishes the importance of using all types of
natural resources efficiently and provides a general framework for policy actions for the European
economy and environment for the next decade. Under the flagship initiative, a roadmap to a resource-
efficient Europe was published in September 2011 defining the milestones to be met by 2020149.
In addition to the flagship initiative, a new Environment Action Programme (EAP) 'Living well, within
the limits of our planet' was adopted in November 2013 and will guide EU policy action on
environment and climate policy for the next seven years. The aim is to guide Europe towards a
resource-efficient, low-carbon and environmentally friendly economy in which natural capital is
protected and enhanced, and citizens' health and well-being are safeguarded.
The implementation of this programme, however, will require the continued commitment of the
Member States. In this respect, major projects supported by the ERDF and the Cohesion Fund can play
a pivotal role in ‘protecting the environment and promoting resource efficiency’ (thematic objective 6),
as well as in ‘promoting adaptation to climate change, risk prevention and management’ (thematic
objective 5). The main expected areas of intervention for major projects are:
water supply and sanitation;
waste management;
environment remediation, protection and risk prevention.
While being closely interrelated in many aspects, each sub-sector is characterised by different logics of
intervention so that the Chapter is structured along these typologies of intervention, which are
presented separately.
4.1 Water supply and sanitation
The EU water policy is largely based on the Water Framework Directive150 that sets up ambitious
objectives for the quality and protection of all waters bodies (ecological status, quantitative status,
chemical status and protected area objectives) and includes the key element of the River Basin
Management Plans. The RBMPs provide the overall context for water management in a certain
territory (the River Basin District, RBD) of the Union, including gaps, measures and objectives. In this
respect the Cohesion Policy investments should take place within the context of the relevant RBMPs,
including the preparation of programmes of measures at basin level, as well as within relevant
implementation plans for the provision of particular services linked to other relevant EU water
legislation (see box below).
In line with the results orientation of the new legislative framework of the cohesion policy, the
principles for investments in the water sector are as follows:
integrating the management of water resources on a river district scale. The 'river basin
district' is the territorial unit basis for the management of water from all points of view and is
defined as a set of terrestrial and marine areas, which include one or more neighbouring
basins. In addition, water investments can be financed if River Basin Management Plans are
adopted and are meeting minimum requirements set up in WFD (cf. thematic ex-ante
conditionality 6.1, criterion 2);
integrating economics into water management and water policy decision-making. To
achieve its environmental objectives and promote integrated river basin management, the
149These include strategic goals on key aspects for resource efficiency such as the economy, the natural capital and ecosystem services, and
specific issues in important sectors such as food, mobility and buildings.
150 Directive 2000/60/EC (see also: http://ec.europa.eu/environment/water/water-framework/)
\134
Water Framework Directive calls for the application of economic principles and requires an
economic analysis of the different uses of resources and water services;
polluter-pays principle151. The tariff policies for attaining the goal of economically and
environmentally sustainable use of water resources must recover the cost of water services,
including financial costs, environmental costs and resource costs, while taking into account
social, economic and environmental effects of the recovery, as well as geographic and climatic
conditions. In this regard, Member States are encouraged to define their pricing policy
frameworks at national/regional level;
water efficiency152. Reducing water usage helps to preserve the available resources and
prevent future droughts and also contributes to improving the competitiveness of an economy.
It encompasses in particular water pricing providing incentives for users to use water
resources efficiently, leakage reduction in distribution networks and, in areas where water
deficit is structural, water reuse systems.
The following investment typologies are discussed in the rest of the section:
renovation/development of infrastructure for water supply;
renovation/development of infrastructure for wastewater collection and treatment.
Natural capital enhancing projects (e.g. green infrastructure) are not specifically treated in this section
because usually associated to objectives of environment protection and ecosystem preservation (see
section 4.3). However, in some cases, these projects can also achieve some of the water- (but also
waste-) related benefits that are typical of the traditional engineering solutions. For example,
preserving the Natura 2000 network is likely to have benefits ranging from regulating services, such as
water resource savings, to cultural services, such as recreation. Vice-versa, development of
infrastructure in the Integrated Water Supply service can also achieve benefits of environment
preservation. That considered, both project typologies (i.e. infrastructure and natural capital
investments) share the same methods for benefit evaluation. For this reason, the methodology
presented below can be understood as a flexible framework for project appraisal, where a given
benefit can be achieved through different investment types.
A selective list of policy and regulatory documents for the water sector is provided in the box below.
THE EU POLICY FRAMEWORK
Blueprint to Safeguard Europe's Water Resources
The Water Framework Directive (or Directive 2000/60/EC)
The Drinking Water Directive (or Directive 98/83/EC)
The Urban Waste Water Treatment Directive (or Directive 91/271/EEC)
The Bathing Water Directive (or Directive 2006/7/EC)
The Nitrates Directive (or Directive 91/676/EEC)
Directive 2008/105/EC on environmental quality standards in the field of water policy
Directive 2009/54/EC on the exploitation and marketing of natural mineral waters
Directive 2006/118/EC on the protection of groundwater against pollution and deterioration
Directive 2001/83/EC on the Community code relating to medicinal products for human use
Commission Staff Working Document 'Climate Change and Water, Coasts and Marine Issues'
151 The requirement of cost recovery of water services is required under thematic ex-ante conditionality 6.1, criterion 1.
152 The requirement of water pricing policy which provides adequate incentives for users to use water resources efficiently is set up in the
thematic ex-ante conditionality 6.1, criterion 1.
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4.1.1 Description of the context
For water projects, besides the traditional information in the socio-economic context, there are
specific baseline features that should be analysed more carefully when performing the context
analysis:
territorial planning framework. The project promoter should describe the existing national
and regional sector policies (mainly for the use of water for human purposes, the treatment of
sewage and the protection of water bodies elements) to ascertain the project’s relevance. Also,
clear and explicit links needs to be made between the water-related priorities in the
operational programme and the relevant RMBPs;
institutional context. Reference should be given to the institutional organisation of the water
and sanitation services, including information on the capacity of the service provider (utility),
the level of service integration, the role of the planning and/or control authority bodies, etc.;
coverage and quality of the services in the area concerned by the project. The context
analysis should describe: the current extension and population coverage of the water and
wastewater systems153; levels of water consumption for civil, industrial, public and/or
irrigation uses; level of physical and administrative water losses, both at production and in the
distribution systems; reliability of the water supply and continuity of service; scarcity
/abundance of the water sources; polluting loads on surface water bodies, including rivers,
lakes, transition waters, estuaries and coastal seawaters;
pricing policy. The project promoter should present the current pricing policy and level of
charges paid by the users, as well as analysing the scope and implications of tariff increases or
change in the pricing system following project implementation, taking into account
considerations of equity linked to the relative prosperity of the Member State, or the region
concerned.
Table 4.1 Presentation of the context. Water sector
Main information
- Population dynamics
Socio-economic - National and regional GDP growth
trend
- Disposable income by population groups
- Reference to relevant river basin district
- Current status of water bodies affected by the project, both as sources of water and as
receptors of wastewater discharges
Environmental - Planned qualitative and quantitative objectives on the status of the affected water bodies
conditions - Current amount of water drawn from natural sources and targets for future (increasing or
decreasing)
- Other uses, existing and planned, of the concerned water bodies: bathing, other recreational,
productive uses, etc.
General political, - Reference to EU directives and sector policy documents (see above)
institutional and - Reference to national and regional strategies, including the River Basin Management Plans,
regulatory any national implementation plan and accompanying programmes of measures
framework - Reference to the priority axis and the interventions areas of the OP
- Reference to the institutional organisation of the service: the level of the service integration,
Water service planning and/or control authority bodies, planning documents, etc.
institutional, - Reference to the service control system
regulatory and
- Reference to the operational organisation of the service and to the modes of supply
operational
framework - Service provider (utility): who will take over the operation and maintenance of the project
infrastructure, and its capacity to implement (where relevant) and manage the infrastructure
153 E.g. with the use of maps of wastewater agglomerations. In particular an integrated approach focusing on the entire water cycle (natural
and artificial) must be adopted.
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- Service categories: drinking water, irrigation, industrial uses, sewers, wastewater treatment
- Service catchment area (or areas) and population served
- Specific water consumption and historic demand development by category of customers
(domestic, public, industrial and others)
Existing service - Connection rates, metering rate
conditions
- Water physical losses and administrative losses
- Infiltration to the sewerage network
- Frequency and duration of water supply interruptions
- Pricing policies and affordability ratios
Source: Authors
4.1.2 Definition of objectives
The main general objectives of water investments are to increase the coverage or to improve the
quality, effectiveness and efficiency of existing water supply and wastewater treatment services. Both
logics of intervention can be driven by the need of the Member States to comply with the EU
environmental acquis, as set out in the relative EU directives, but not exclusively.
The main motivations underlying the need for intervention are:
increasing the number of households connected to centralised drinking water supply and/or
wastewater networks154;
improving the quality of drinking water;
improving the quality of the surface water bodies and preserving ecosystems and biodiversity
dependent on these surface water bodies;
improving the reliability of the water sources and the water supply service;
increasing efficiency in water production and/or distribution, e.g. through detection,
measurement and reduction of water losses or management asset measures aimed at
operating costs reduction;
increasing efficiency in wastewater collection, removal, purification and elimination, e.g. with a
strategy for disposal of sludge from urban wastewater treatment;
replacing the use of water, preserving it from over-abstraction and/or providing for other
efficient uses.
4.1.3 Project identification
The scope is on investments in the Integrated Water Supply (IWS) service for civil, industrial and
agricultural uses. The IWS segments include the supply and delivery of water as well as the collection,
removal, purification and elimination of sewage. The re-utilisation of wastewater, while not strictly
part of the IWS, is also discussed.
The following table provides some examples of IWS investments.
Table 4.2 Typical IWS investments
Examples
- Construction of new infrastructures, e.g. aqueducts, intended to meet increasing needs
Renovation/development - Completion of water supply networks that have been partially realised
of infrastructure for - Modernisation and/or replacement of the existing water pipes and of other elements of
drinking water supply aqueduct (e.g. tanks, basins, spillways, pumping stations.)
- Pressure zoning management intended to improve the efficiency of the water asset
154 Note that according to EU legislation no wastewater investment shall be supported in agglomeration below 2 000 population equivalent
(unless clearly justified through technical evidence and sound option analysis).
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management
- Replacement/extension of the sewage network (either combined or separate)
Renovation/development - Construction /rehabilitation of wastewater treatment systems
of infrastructure for - Construction/rehabilitation of wastewater treatment plants with more stringent
wastewater treatment treatment for the reuse of water
- Infrastructure for rainwater drainage
Source: Authors
4.1.4 Demand analysis
4.1.4.1 Factors influencing water demand
When forecasting demand for water, different factors need to be taken into account and duly analysed,
including:
demographic dynamics: the total water demand is directly related to the size of population.
The project shall take into account the demographic forecasts and the migration flows for an
estimate of the users;
economic trend: even though in some cases there is relative or absolute decoupling between
resource use and economic growth, a fast growing economy still generally demands a higher
quantity of water than a flat or shrinking economy. In parallel, higher standards of living are
associated with higher demand for water. If, within a given catchment area, tourism or
production development is expected, it should be duly taken into account in forecasting the
water demand;
agricultural production trend: in the case of irrigation water, the demand depends upon the
surfaces that are expected to be irrigated and the types of crops;
industrial production trend: in the case of industrial use of the water or of industrial
wastewaters, demand forecasting usually requires a specific analysis of the hydro-needs of the
concerned production units, broken down by type of production;
climate: demand for water has a seasonal component and climate change impacts may affect
the availability of water in the long run;
tariff system: it is important to consider the elasticity of demand with respect to tariffs. In
some cases it will be necessary to estimate the elasticity for different income groups and also
for small and large users, because it may have quite different values and distributive impacts.
In any case, the elasticity of water demand with respect to service price should be estimated on
a local basis. In fact this parameter varies considerably in different geographical areas that are
otherwise similar.
4.1.4.2 Hypotheses, methods and input data
Demand is fundamentally made up of two elements:
the number of users (civil use), the surfaces that will be irrigated subdivided by different
kinds of crops (agricultural use) or the number and sectors of the production units which shall
be served (industrial use);
the quantity of water, that is being or will be supplied/treated for a given period of time.
The estimation of the demand curve may be based on data gained from the previous experience in the
area involved or on published forecasting methods often based on the concept of the consumer’s
willingness to pay155. In case of replacements and/or completions, it is also useful to make reference to
the data on historical consumption, provided that these data have been measured by reliable methods
155 Russell, Clifford S & Kindler, J. (Janusz) & International Institute for Applied Systems Analysis (1984). Modeling water demands. Academic
Press, London ; Orlando.
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(for example from the readings of meter consumption).
The most important input data to be considered for forecasting the demand in water projects are:
historical and current annual total and average consumption by type of consumers. The
following categories of consumers are generally considered:
o household/commercial final consumers, residents and non-residents (i.e.: commuters,
tourists, visitors for other reasons, etc.)156;
o industrial users;
o agricultural users.
variability of seasonal and daily level of consumption (litres/day) to identify peak and off-peak
demand.
4.1.4.3 Output of demand forecasting
The project promoter should provide projections related to volumes of water and wastewater that will
be treated by the project and the polluting load that will be generated.
In general, a distinction between starting, potential and actual demand (or water resource and water
consumption, respectively) can be made. The starting demand is given by the actual consumption
before the intervention (see box below). The potential demand corresponds to the maximum
requirement, which will be taken into account for the investment.157 The actual demand is the demand
which is actually fulfilled by the investment in question and which corresponds to the expected
consumption.
A first obvious evaluation criterion of the investment depends on the extent to which the actual
demand may be close to the potential demand: the demand the investment can actually satisfy
corresponds to the supply, net of any technical resource loss and release. Whenever the project may
imply the use of water (surface or subsurface) resources, the actual availability of the resource flows
required will be clearly shown by appropriate hydrological studies.
If the project involves the treatment and discharge of sewage, it is necessary to analyse the polluting
load of the water that will be treated as well as the load capacity of the body intended to receive the
polluting and nourishing substances, in a way that is compatible with environmental protection
(Directive 2000/60/EC).
DEMAND ANALYSIS: BASIC FUNCTIONAL DATA
- Number of users served, broken down into main categories, and projections for future dynamics.
- Irrigated surface (hectares) by crop kinds.
- Number and type of production units served, as well as their water demand (including possible seasonal
peaks) and expected wastewater production (including expected polluting loads).
- Water availability and demand per capita (l/d*inhabitant) or per hectare (l/d*hectare) or per production
unit.
- Water quality data (laboratory analysis).
- Number of population equivalent, flow and peak rates, parameters of the polluting load of the water that
will be treated (laboratory analysis) and quality constraints of the water that will be drained (defined by the
law).
156A parameter of consumption often used is the daily specific consumption, expressed in litres / inhabitant x day.
157 For example, for civil purposes it may be evaluated on the basis of the water requirements for the same use (generally expressed on a
daily and seasonal basis) arising out of the comparison with any situation which will be as close as possible to the one facing the project and
have a good service level. For irrigation purposes, it may be estimated on the basis of specific agronomic studies or, even in this case, by
analogy.
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4.1.5 Option analysis
The implementation of any investment project should be justified against a set of feasible alternative
options that would achieve the same objective(s). The analysis of options should be carried out
separately for water and wastewater systems, plants and networks and shall be based on a
comparison of:
the possible strategic alternatives, for example: a dam or a system of crosspieces instead of a
wells field or the agricultural re-utilisation of properly treated sewage; a central depurator
instead of several local depurators; rehabilitation/extension of existing treatment plants vs.
new construction; re-lining against replacement, etc.;158
the possible technical alternatives within the same infrastructure, for example: different
location of wells, alternative routes for aqueducts or trunk lines; different building techniques
for dams; different positioning and/or process technology for plants; utilisation of different
energy sources for desalination plants, etc.
In selecting the options, the design alternatives must meet the requirements of the legislative
framework (EU acquis) and, in particular, the European water policy (see above) and of the water
sector programmes of the Member State. Options that respect both design alternatives and the policy
constraints, will then be ranked and selected according to the methodology illustrated in section 2.7.2.
In particular, to select the optimal option, a life-cycle cost approach must be adopted to assess all
relevant costs over the lifetime of the project (investment costs, operational costs, maintenance costs,
decommissioning costs and external costs)159.
4.1.6 Financial analysis
4.1.6.1 Investment cost
In the case of IWS projects, the time horizon is typically 30 years (taking into account also the
construction period). As regards to the technical life of equipment, which has an impact on the level of
replacement costs that needs to be taken into consideration during the time horizon, it is
recommended to split the assets into main broad asset categories, for instance:
civil works (including operational buildings, reservoirs, access ways, etc.);
pipes (including transport and distribution pipes, connections);
electrical and mechanical equipment(including equipment built in wells, plants, pumping
stations).
Assumptions on the technical life of the categories above need to be duly justified and presented in the
CBA report.
4.1.6.2 Operation and Maintenance (O&M) costs
Typical operating costs items of water investments include energy, materials, services, technical and
administrative personnel, maintenance, and sludge management costs. Projections of O&M costs shall
be split into fixed and variable costs, and by category. In developing the O&M cost projections for both
with and without the project scenarios, clear assumptions shall be made. In particular, the definition of
the scenario without the project must be one of the operations based on a realistic estimate of the
continuation of the service, as illustrated in the box below.
158 As mentioned before, the possibility of investing in natural capital, rather than in physical investments, shall also be tested, where relevant
and able to contribute to the achievement of the intended objectives.
159 See European Union, 2013 'Green Public Procurement criteria on waste water infrastructure of waste water treatment'. Documents
available at: http://ec.europa.eu/regional_policy/sources/docgener/studies/pdf/green_public_procurement.pdf
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4.1.6.3 Revenues projections
The source of financial revenues in the IWS project comes from the application of charges to users for
the services rendered, e.g. revenues for drinking water supply, drainage water collection and
wastewater collection and treatment, sludge management, sale of purified water for industrial and
agricultural purposes, etc.
The public/private water agencies/companies/entities that run the water management should, in the
first instance, ensure the financial sustainability of the whole water management system, including
investments in maintenance of infrastructure. Thus, adequate tariffs have to bet set up with the goal of
ensuring an adequate level of recovery of the cost of providing the service, as well as financial
sustainability of operations once the project is implemented, while at the same time respecting
affordability constraints that might apply. When necessary, an affordability analysis must be carried
out in line with the provisions outlined in Annex V.
The following approach is recommended for the incremental tariff to be considered in financial
analysis:
without the project: current tariffs should be set at a level of cost recovery of the existing
system, therefore allowing for coverage of O&M, as well as depreciation of existing assets;
with the project: tariffs shall be set at least to cover all financial costs, i.e. to cover O&M costs
for the existing and new project assets, including depreciation and replacement of short-life all
assets, starting from the ones with the shortest economic life160.
Note that for the purpose of the calculations, a unit tariff is usually calculated and applied, although in
practice tariffs can be differentiated across user groups.
DEFINITION OF THE COUNTERFACTUAL SCENARIO
The counterfactual scenario is a realistic estimate of the continuation of the service as is, which could imply
higher O&M costs than in the scenario with the project, or even cover some minor necessary investments (do-
minimum), if estimated as needed.
Given the general rule, in the water and wastewater management sectors, the identification of an appropriate
counterfactual can be complex. In case of projects that are motivated by the need to comply with the EU
directives, business as usual would likely correspond to perpetuating a situation of infringement of EU and
national legislations and environmental risk. Thus, the project promoter should, in principle, dismiss this
scenario and adopt as counterfactual the 'do-minimum' solution.
In practice however, this approach is often not feasible. In fact, owing to technological constraints, it can be
difficult to identify a technically viable minimum solution capable of reaching the stated objective, other than the
project itself. In this case, the business-as-usual option should be considered an acceptable counterfactual, as the
only technically feasible basis for comparison of costs and benefits. However, penalties for non-compliance with
prevalent legislative requirements need to be projected, according to realistic and well-defined assumptions, and
included in the financial analysis provided that are paid by the project promoter (while in economic analysis
they are excluded to avoid benefits double counting).
4.1.7 Economic analysis
IWS projects can produce different social benefits and costs, depending on the specific typology of
project implemented as compared to the counterfactual scenario.
The main direct effects and externalities usually associated with the construction, modernisation and
quality improvement of water supply and wastewater networks and/or treatment plants are
summarised in the table below, together with the different valuation methods suggested.
160 For sustainability reasons, in justified cases, this could lead to temporarily raised tariffs above the affordability limit.
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Finally, a typical benefit that is not included below, because of a purely financial nature, are the O&M
costs savings of the integrated water service, which, for some projects, can be the only aim of an asset
management strategy.
Table 4.3 Typical benefits (costs) for water investments
Impacts Type Valuation method
Increased availability of drinking water supply Averting behaviour
Direct
and/or sewer services Stated preferences (choice experiments)
Improved reliability of water sources and water Averting behaviour
Direct
supply service Stated preferences (choice experiments)
Averting behaviour
Improved quality of drinking water Direct
Stated preferences (choice experiments)
Water bodies with a use value: market value, Averting
Improved quality of surface water bodies and behaviour, travel cost or benefit transfer
Direct
preservation of ecosystem services Water bodies with a non-use value: contingent valuation
or benefit transfer
Resource cost savings (water preserved for
Direct Long run marginal cost for water production
other uses)
Stated preferences
Health impacts Externality Revealed preferences (hedonic wage method)
Cost of illness
Congestion savings due to improved rainwater
Externality Time savings
drainage
Variation in GHG emissions Externality Shadow price of GHG emissions
Source: Authors
In what follows, the above-mentioned listed benefits and the relative methods for evaluation are more
extensively discussed.
4.1.7.1 Increased availability of drinking water supply and/or sewer services
Increased availability is typical direct effects of water and/or wastewater projects, which arises when
new users are connected to the centralised water supply or sewer networks.
Given that water is a classic case of natural monopoly, where market prices are generally distorted, the
preferred basis for benefit estimation is the users' willingness to pay (WTP) for the service. The WTP
for being connected to the water supply/sewerage service can be empirically estimated by applying
the market prices of the best alternative technique feasible for the water supply/discharge of
wastewater in the same catchment area (averting behaviour). In particular for the following projects:
Water supply projects, the avoided capital and maintenance costs of self-provision of
water, e.g. by means of tank trucks, small-scale desalination plants (only for coastal areas),
water wells or boreholes (especially for irrigation), can be applied. It is important to remark
that these WTP refers to drinkable water, i.e. the underlying hypothesis is that the
groundwater extracted with wells or borehole is drinkable. Otherwise, if purification is needed,
additional costs for the purification process must be added;
Sanitation projects, the avoided capital and maintenance costs of self-collection and discharge
of wastewater, e.g. by means of closed tanks, can be applied.
To quantify the benefit, the WTP values (expressed in Euro/household) should be multiplied by the
new households connected to the central network161.
Alternatively, stated preference methods (and in particular choice experiments – see Annex VI) can
also be used to calculate users' WTP for the service rendered by the project. This is particularly the
161Accordingly, if information on connection demand is available in terms of residents only, these have to be converted into number of unit
households by using the average household size of the country or region of reference.
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case of surveys being commissioned by water companies to provide evidence on what customers are
willing to pay for improvements in customer service and environmental performance. WTP estimates
are usually generated for attributes such as reduced frequency of service interruptions, improved
taste and odour, reduced discolouration, improved pressure, and so on. Thus, the stated preference
methods can be applied also to the benefits discussed below in sections 4.1.7.2 and 4.1.7.3.
4.1.7.2 Improved reliability of water sources and water supply service
This benefit arises when the methods for water abstraction, supply and distribution are improved so
that the pressure of the water is increased (within prescribed limits), accidental service interruptions
reduced and/or water supply shifts are eliminated.
As above, the WTP for improved reliability can be empirically estimated as the avoided cost of the
inhabitants for a reliable self-provision (averting behaviour). For example, the costs avoided to be
equipped with domestic tanks for collecting water and electric devices for pumping it into the house
water systems with an adequate pressure.
These costs could include the investment costs for purchasing the tank and/or the pump (renewal),
the costs of the electric power needed for its functioning, the maintenance costs and time spent by
users (this includes time to collect information about hours and days of water rationing as well as the
time spent to fill in the tanks and turning on/off the pumps).
4.1.7.3 Improved quality of drinking water
This benefit arises in case of interventions aimed at ensuring that the quality of drinking water
supplied to citizens meets the minimum EU standards (see Drinking Water Directive).
When underground or surface water sources contain too high concentrations of chemicals or
pollutants (e.g. iron, manganese, fluorine, etc.) water must be cleaned before supplying it to
distribution system. Thus, drinking water quality can be improved with the construction,
rehabilitation or upgrade of purification systems.
In the case of water quality being far from standards, purification treatments, can become more and
more costly, as well as ineffective or, when intensive chemical processes are necessary to treat the
highly polluted water, even health harming. In those cases, the quality of water can be improved
working on the purification systems or even changing the water source (e.g. with the construction of
aqueducts).
Again, the WTP for improved water quality can be empirically estimated as the avoided cost of the
users to purchase good quality water on the market.162 For example, the avoided cost of
purchasing water through tank lorries. Please note that this approach is pertinent to all users,
including those that are connected to a centralised system. In fact, the best alternative technique for
benefit estimation should consider a scenario where the existing supply is not compliant with the EU
standards and is therefore interrupted and replaced.
Alternatively, the WTP can be estimated as the avoided cost to the users for setting up and operating
domestic filtering systems that make water supply drinkable. The two approaches presented above
are mutually exclusive.
In addition, positive heath impacts can be generated, as illustrated below in section 4.1.6.7.
4.1.7.4 Improved quality of surface water bodies and preservation of ecosystem services
The improvement of the surface water bodies’ quality163 consists of reducing pollutant levels and/or
increasing dissolved oxygen levels. In turn, this has the positive effect of preserving ecosystems and
162 In case of projects aimed at providing bulk water only, the same approach applies, but the WTP should not be calculated against the final
user. It should be rather calculated as the avoided cost of the service provider for an alternative supply.
163 Water quality refers to the chemical, physical and biological characteristics of water.
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biodiversity dependent on these surface water bodies. Usually, this benefit originates from projects
involving the extension of the wastewater treatment or the construction/rehabilitation of wastewater
treatment plants (WWTPs) in compliance with EU requirements. Thanks to these projects, wastewater
is treated before being discharged into the surface water bodies. The benefit can also arise, however,
in case of projects dealing with removal of sludge and construction of wetland or projects concerning
storm-water management facilities164, such as bio-retention systems, infiltration or retention basins.
Depending on the type of project under assessment, different methods can be adopted to estimate
people’s WTP to have surface water bodies of a better water quality. Indeed, the estimation of the WTP
for a project aiming at improving the quality of a lake used for fishing differs from that of a lake used
for bathing and differs also from that for a project concerning a river without any use. In other words,
the use or non-use of the concerned surface water body must be known at first in order to choose the
best estimation method.
In case of water bodies (including seawaters) where prohibition to bathing, fishing or other
recreational and/or productive activities is removed thanks to the project, an operational
approach for benefit estimation is to use the market value of the concessions given for the
provision of the recreational activities (e.g. beach resorts) or productive activities (e.g. fishing,
shellfish) as proxy of WTP. In the absence of a market, the travel cost method to reach the
facility or benefit transfer (see Annex V) can be used.
In case of water bodies that are not used for bathing or other water related recreational and/or
productive activities, the WTP for the simple existence (non-use value) of a less polluted water
body (preserving or increasing the amenity of the place) must be estimated. A contingent
valuation would be the preferred choice. However, it is usually expensive and time consuming
(although nowadays, the progressive use of on-line panels of respondents is decreasing its
cost). As alternative, a benefit transfer approach, transferring and adjusting values calculated
somewhere else for similar projects, can be adopted.
Caution must be taken when defining the number of people to whom the concerned benefit must be
applied. In principle, the WTP for improving the quality of water bodies with a use value should be
multiplied by the number of persons who could potentially use the water body. Thus, a demand for the
good should be carefully estimated.
Instead, the WTP for improving the quality of water bodies with non-use value should be multiplied by
the total population of the catchment area, since the value reflects an existing or amenity value, i.e.
what people are willing to pay just to keep an environmental asset in good quality. That said, often
these values are space dependent, i.e. the non-use benefits received may decline with distance from
the good or service. For example, in the case of a river, people may have higher non-use benefits for
rivers closer to where they live than for similar rivers very far away. Hence, when aggregating non-use
values, consideration could be given to the use of a distance-decay function. This issue shall also be
discussed in sensitivity analysis.
4.1.7.5 Water preserved for other uses
The benefit of water preserved for other uses, current or future, arises first when interventions are
aimed at reducing the water leaks of the distribution network. In other words, this is a typical benefit
of water asset management projects: thanks to the reduced leaks, the volume of water needed to
supply the network decreases and, as a consequence, an amount of water is preserved for other uses.
Secondly, this benefit is generated when projects aim at avoiding the over-exploitation of a water
source. For instance, when groundwater is replaced with water produced from other sources such as
desalination or reuse of purified wastewater (more stringent treatment) for irrigation or industrial
164 Storm water is water that originates during precipitation events. Storm water that does not soak into the ground becomes surface runoff,
which either flows directly into surface water bodies or is channelled into sewers, which eventually discharge to surface waters. Storm water,
especially urban storm water, contains a high level of pollutants which if directly discharged in surface water bodies risks decreasing the
water quality.
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water supply. In contexts of water scarcity, this contributes to preserving the human environment and
the whole biodiversity of the area.
The opportunity cost of the preserved water should be estimated on the basis of the long run marginal
cost of production, reflecting the total social cost incurred to abstract an extra unit of water plus
transportation cost from the source where it is abstracted to where it is used.
When the water tariff is well built (i.e. it reflects the long run marginal cost of production– see Annex
III), the benefit is already captured by the operational cost savings of the operator which needs to use
less groundwater to guarantee the same level of supply. If the tariff does not reflect the long run
marginal cost, additional analysis is needed to measure the opportunity cost of the water preserved.
4.1.7.6 Health impacts
Positive impacts on health are mainly generated by two categories of projects:
projects that improve the quality of drinking water owing to pollutant reduction, as measured
by the difference between the contamination load carried by a unit volume of water, without
and with the new system;
projects that improve the effectiveness of the sewerage network and wastewater treatment,
e.g. owing to avoidance of any contamination of the local aquifer with sludge.
Positive impacts on health should be included in economic analysis by attributing an economic value
to the decreased morbidity rate for water-related diseases, taking care of possible benefit double
counting with the WTP (see box).
The preferred method for the estimation of economic cost is, as usual, stated or revealed preference
techniques based on the concept of willingness to pay/accept (i.e. either survey based techniques or
the hedonic wage method).
In absence of this, the cost of illness approach, which combines direct and indirect costs into an
overall societal estimate, can be adopted. Direct costs include the medical costs necessary for treating
a particular disease (e.g. hospitalisation, medical supplies, rehabilitation care, diagnostic tests, drug
prescriptions, etc.) and should be calculated on a case–by-case basis, depending on the type and
severity of disease. Indirect costs measure the value of lost production because of reduced working
time due to a particular illness. They are essentially calculated by multiplying the total period of
absence (number of days) by the daily gross wage rate of the absent worker. In the case of children,
disabled people and the elderly, the working days lost by their relatives (or to pay someone taking
care of them) could be used as a proxy off the economic value for reducing the risk or the duration of
illness.
WTP AND HEALTH IMPACTS: POSSIBLE DOUBLE COUNTING
In evaluating positive impacts in health, caution must be paid to avoid any benefit double counting with the WTP.
For instance, if the defensive behaviour for bad drinking water quality of all consumers is to buy bottled water, it
is unlikely that positive health impacts will be generated. Vice-versa, if consumers do not adopt a defensive
behaviour and would still drink tap water in absence of the project, a WTP based on the avoided cost of
purchasing water on the market is unrealistic, and the entire benefit will be the avoided cost of illness. 165
That said, most likely, there will be situations in between, where consumers would drink both bottled and tap
water and a combination of the two benefits apply. The project promoter should, however, consider realistic
estimates of the volumes of water to which one or the other benefit is calculated. Accordingly, apply the WTP
values only to a given share of the total water consumption and add the health benefit only for a realistic number
of avoided cases (to be possibly estimated on the basis of hospital records).
165 Please note that, in case of using stated preferences to estimate WTP for water quality improvements, the double-counting issue would
disappear as the WTP estimate would reflect health benefits as well as other benefits such as convenience of drinking tap water, etc.
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4.1.7.7 Reduced congestion
When existing rainwater collection in urban systems is not capable of coping with rain water during
hard rain, infrastructure to improve the drainage rate can be implemented, especially in light of the
new challenges posed by climate change concerns.
Time saving is the most significant benefit that can arise from the improvement of a rainwater
drainage system. Indeed, an improved rain water collection system leads to less congestion traffic and,
in turn to time savings. For the estimation of this benefit please refer to the transport chapter.
Obviously, this benefit is not related to interventions aimed at reducing the impact of hydrogeological
disasters (that are dealt with in section 4.3).
4.1.7.8 Variation in GHG emissions
When relevant to the technical solutions envisaged in the project, the economic analysis will have to
take into account the increase/decrease of GHG emissions as a result of:
increased activities triggered by the project, including:
o sludge digesters, based on a quantification of gas production and related CO 2 portion (to be
justified in the technical feasibility study);
o sludge transport to disposal sites, based on quantification of dehydrated sludge and other
waste from the WWTPs (screenings, grid) to be transported to a sanitary landfill and to
surrounding agricultural fields;
energy savings due to optimisation of the system.
Once quantified, the additional CO2 emissions generated or avoided should be monetised using the
shadow price of CO2, as illustrated in section 2.9.9.
4.1.8 Risk assessment
A sensitivity test of the results of both financial and economic analyses to changes in the value of the
considered variables is highly recommended. Sensitivity analysis of water projects is advisable for
both market-related variables and non-market goods. More specifically, the CBA results should be
tested for changes of at least the following variables (when relevant for the project):
assumptions on GDP trend
demographic trend
production trend, (when relevant)
trend of unit water consumption
number of years necessary for the realisation of the infrastructure
investment costs (as disaggregated as possible)
O&M costs (as disaggregated as possible)
unit tariff or estimated WTP for water consumption
WTP for increased coverage, increased reliability of supply, improved drinking water quality
and/or quality of surface water bodies
avoided cost of illness considered for the valuation of health benefits
quantities and unit values of GHG emissions.
On this basis, a fully-fledged risk assessment must be carried out, typically, by assessing the risks
presented in the following table.
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Table 4.4 Typical risks in water projects
Stage Risk
Regulatory - Unexpected political or regulatory factors affecting the water price
- Water consumption lower than predicted
Demand analysis
- Connection rate to public sewage system lower than predicted
- Inadequate surveys and investigation e.g. inaccurate hydrological predictions
Design
- Inadequate design cost estimates
Administrative - Building or other permits/ Utility approvals/ Legal proceedings
- Land costs higher than predicted
Land acquisition
- Procedural delays
Procurement - Procedural delays
- Project cost overruns and/or delay in construction schedule
Construction
- Contractor related (bankruptcy, lack of resources)
- Reliability of identified water sources (quantity/quality)
Operational - Maintenance and repair costs higher than predicted, accumulation of technical
breakdowns
- Tariff increases slower than predicted
Financial
- Tariff collection lower than predicted
Source: Adapted from Annex III to the Implementing Regulation on application form and CBA methodology.
4.2 Waste management
The EU legislation and policy on waste management are based on a series of principles which include
the obligation to handle waste in a way that does not have a negative impact on the environment or
human health, the encouragement to apply the priority order for waste management options in
accordance with the waste hierarchy, the recovery of costs of waste management in accordance with
the polluter pays principle and the principles of self-sufficiency and proximity. These principles
are central demands of the EU Waste Framework Directive166, which sets the basic concepts and
definitions related to waste management.
According to the waste hierarchy, waste management strategies must aim primarily to prevent the
generation of waste and to reduce its harmfulness. Where this is not possible, and waste is produced,
priority should be first given to its preparation for re-use, then to recycling, then to other forms of
recovery (e.g. in the form of energy in waste-to-energy facilities), and only as a final resort, waste
should be disposed of safely in authorised, legally compliant landfills. Exceptionally, the Waste
Framework Directive allows the departure from the hierarchy for specific waste streams where this is
justified 'by life-cycle thinking167 on the overall impacts of the generation and management of such
waste' or based on the consideration of 'general environmental protection principles of precaution
and sustainability, technical feasibility and economic viability, protection of resources as well as the
overall environmental, human health, economic and social impacts'.
The polluter-pays principle requires that the costs of waste management shall be borne by the original
waste producer or by the current or previous waste holders.
For the programming period 2014-2020, the most important new policy development in this waste
sector is the reinforced focus on resource efficiency, with the ultimate goal of making the most efficient
use of the limited available resources (such as energy, water and raw materials), leading to cost cuts.
168
Moving towards a more circular economy is essential to deliver the resource efficiency agenda
166 Directive 2008/98/EC.
167 For a description of the available tools
for conduction of life-cycle thinking see JCR-IES (2011), Supporting Environmentally Sound
Decisions for Waste Management. Available at:
http://publications.jrc.ec.europa.eu/repository/bitstream/111111111/22582/1/reqno_jrc65850_lb-na-24916-en-n%20_pdf_.pdf
168 COM(2014) 398 final
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established under the Europe 2020 Strategy for smart, sustainable and inclusive growth.169 Higher
and sustained improvements of resource efficiency performance are within reach and can bring major
economic benefits.
In addition, waste investments must be closely linked to the needs identified in the adopted waste
management plans and waste prevention programmes in compliance with the Waste Framework
Directive (cf. thematic ex-ante conditionality 6.2). A significant number of Member States still have
important needs in terms of ensuring adequate management of solid municipal waste in compliance
with EU standards, in particular to meet the 2020 target on preparation for re-use and recycling of
certain materials from household waste and construction and demolition170 and the targets for the
diversion of biodegradable waste from landfills171. In this respect, waste management will remain a
priority for investments with ERDF and the Cohesion Fund.
A selective list of policy and regulatory documents for the waste sector is provided in the box below.
THE EU POLICY FRAMEWORK
Waste framework
Waste Framework Directive (or Directive 2008/98/EC)
Regulation (EC) No 1013/2006 on shipments of waste
Commission Decision 2000/532/EC on establishing a list of wastes
Waste management operations
Council Directive 1999/31/EC on the landfill of waste
Directive 2000/76/EC on the incineration of waste
Specific waste streams
Directive 94/62/EC of 20 December 1994 on packaging and packaging waste
Directive 2012/19/EU on waste electrical and electronic equipment (WEEE)
Directive 2013/56/EC on batteries and accumulators
Directive 2000/53/EC on end-of-life vehicles
4.2.1 Description of the context
The baseline context elements recommended to be described for waste management projects are
shown in the following table.
Table 4.5 Presentation of the context. Waste management sector
Main information
- Population dynamics
Socio-economic - National and regional GDP and GDP per capita growth
trend
- Disposable household income by income groups
- EU directives and sector policy documents related to waste management (see above)
General policy, - National and regional strategies related to waste management, including the Waste
and regulatory Management Strategies and Plans and the waste prevention programmes
framework - Areas of intervention, objectives and specific targets of the operational programme and priority
axis relevant to waste management
169
COM(2010) 2020, COM(2011) 21.
170 EU Waste Framework Directive, Article 11, paragraph 2a) and b).
171 EU Landfill Directive, Article 5, paragraph 2.
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- Institutional set-up of services, legal responsibilities for the planning, provision and control of
waste management services, level of geographic integration, etc.
Specific legal, - Control system of the service, including waste flow control
institutional and - Operational organisation and forms of service provision and revenue collection, involvement of
operational
private sector in service provision, contractual arrangements including financial compensation
framework for
service provision - Level of taxes/fees/tariffs charged for services provided, level of cost recovery
- Service provider(s) (utilities) in charge of service provision, operation and maintenance of the
project infrastructure
- Service area and population served with service coverage rates
- Quantities and composition of waste produced and collected at the local/regional level by
source and type of waste (municipal waste from households, commerce, public parks and
gardens, street waste, etc.)
- Quantities and composition of waste imported from outside the local/regional level
Coverage and - Quantities of separately collected waste streams prepared for re-use or recycling (recyclable
quality of existing materials such as paper and cardboard, plastic, glass, metals), recovery or separate treatment
service provision or disposal (organics, bulky wastes, hazardous wastes, etc.)
- Quantities of mixed residual wastes produced and collected and type of waste management
methods implemented (for treatment and/or disposal)
- Physical condition of existing facilities for waste treatment and disposal, risks for the
environment from emissions of air, water and soil pollutants, extent of environmental damage to
soil and groundwater, if any
Source: Authors
4.2.2 Definition of objectives
The general objectives of waste management investments are usually the improvement of living
conditions of the population and of environmental management in the local and regional context. The
logic of intervention can be driven by the need of the Member States to comply with the EU
environmental standards, as set out in the relative EU waste legislation, but not exclusively. Specific
objectives involve:
the development of a modern local and regional waste management system, to replace an
inefficient and unsustainable waste management system based largely on landfills that are
either non-compliant and/or reaching the end of their useful lifetime;
increase of recovery of valuable materials and energy from waste, to reduce consumption of
raw materials and fossil fuels;
the reduction of health risks linked to an uncontrolled management and disposal of municipal
and industrial waste;
the curbing of raw material consumption and the planning of the final phases of material
production and consumption cycles;
the minimisation of GHG emissions and pollutants to air, water and soils from existing waste
management facilities;
replacement or technological overhaul of existing waste collection or treatment facilities, (e.g.
refuse collection vehicles, waste incinerators) due to technological obsolescence.
4.2.3 Project identification
The main types of waste management facilities are172:
investments in facilities for the collection, temporary storage and/or transfer of waste
(whether collected separately or not), such as municipal collection centres and waste transfer
stations;
172 See also Annex II A of the Directive 2006/12/EC.
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material recovery facilities for preparation of (usually separately) collected materials for
recycling;
treatment facilities for separately collected biowaste (e.g. composting and anaerobic digestion
plants);
treatment facilities for mixed residual wastes from residential and non-residential sources (e.g.
waste incinerators with energy recovery, mechanical-biological treatment plants, etc.);
engineered landfills.
A map and a description of the technical characteristics of the proposed facility should be presented
for a better comprehension of the local economic, social and environmental impacts of the project (see
box).
MAIN ENGINEERING FEATURES
- Basic data on waste to be treated: waste type (municipal waste, hazardous waste, packaging waste,
biowaste) and annual quantity (t/y);
- Treatment processes with description of technologies used and individual design parameters (average and
maximum throughput in t/d and t/h); specific consumption of energy, material and services consumed
- Mass balance of the treatment process with main inputs and outputs, including secondary raw materials
recovered, energy produced (MWh of heat and/or power), mass losses.
- Physical features: area occupied by the plant (in thousand m2), covered and uncovered storage areas (in
thousands m2), the distance from main agglomerations and discharge systems for effluent water and fumes.
- Information on procurement strategy and time-plan for construction
The implementation of any investment project should be justified against a set of feasible alternative
options that would achieve the same objective (see section 6.2.5).
4.2.4 Demand analysis
4.2.4.1 Factors influencing waste demand
When forecasting demand for waste management services, some key factors need to be taken into
account and duly analysed, including:
expected demographic growth and economic growth in relevant economic sectors;
present and expected changes in national and European norms in waste management;
evolution in the consumption habits and behaviour of waste producers, such as the increase in
consumption correlated with the standard of living, the change in public attitude towards re-
use and recycling activities or the adoption of clean products and clean technologies, with their
potential consequences on waste streams, including the variation in the type of waste
produced and the decrease or increase in waste production;
technological, product and business model innovations: development of the circular economy,
new business models (leasing, product service system, etc.) and product innovations are
bringing major changes in the concept of 'waste'/ 'end-of-waste'.
4.2.4.2 Hypotheses, methods and input data
The demand for waste management services in the project area will be estimated based on the
following input data: (i) current population and expected growth rate during the project horizon; (ii)
current waste generation per capita and expected changes during the project horizon; and (iii) current
waste composition and expected changes during the project horizon.
Other relevant aspects to be considered as part of the demand analysis (which will be also used for the
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identification and comparison of alternatives) are: (i) waste composition and calorific value; (ii) socio-
economic conditions and geographic distribution of the customer base; (iii) potential market for waste
sub-products (i.e.: recyclables and compost).
Demand is then forecasted from current waste generation levels taking into account demographic and
industrial growth predictions; as well as the potential changes in waste producer behaviour.
The estimation of the demand, both in terms of quantity and quality of waste is a key factor in the
identification of the project alternatives to define the type and capacity of the facilities that will be
necessary to achieve the desired objective (see box in section 4.3.3).
4.2.5 Option analysis
The options analysis shall be carried out at two levels.
First, the analysis of the strategic global alternatives (e.g. different methods for waste management,
different degrees of centralisation for waste treatment and disposal facilities) which shall be generally
compared based on an economic analysis including externalities, where these differ notably between
the individual options. In justified cases, other criteria related to technical, managerial and logistical
aspects may be incorporated into the analysis.
Second, the analysis of the possible sites and more specific technical alternatives for the project, which
shall be generally compared on the basis of costs and other criteria, including amongst others:
efficiency of material recovery and/or production of energy (electricity and/or heat);
actual market demand and off-take price for outputs (compost, recovered recyclable materials,
residue-derived fuels, electricity and heat, etc.);
public acceptance (i.e. chances of rejection by local communities and/or NGOs);
hydro-geology (i.e. type of soil, stability of slopes, risk of flooding, risk of seismic movements,
potential impact on water bodies and aquifers);
accessibility (i.e. proximity and quality of access roads);
ownership and zoning (i.e. land property and use);
other factors (i.e. negative impact on residential areas and economic activities in surrounding
areas).
In selecting the options, the design alternatives must meet the requirements of the legislative
framework and, in particular, the EU Waste Framework Directive (Directive 2008/98/EC). Options
that respect both design alternatives and the policy constraints, will then be ranked and selected
according to the methodology illustrated in section 2.7.2. The box below provides some examples of
options analysis at both strategic and technical levels.
OPTION ANALYSIS: EXAMPLES
Strategic alternatives
- options analysis for the comparison of centralised and decentralised systems for the treatment of separately
collected biowastes in a regional waste management system: one large centrally located plant vs. two or more
smaller plants located closer to the main collection zones
- options analysis for the comparison of technological alternatives for the treatment of residual mixed waste
collected (after separation of recyclables): mechanical-biological treatment with composting of the biological
fraction vs. thermal treatment in a waste-to-energy facility
- options analysis for the identification of the economic optimal solution to further reduce mixed residual waste
collected from an eminently rural area currently going to a landfill which is reaching the end of its useful lifetime
(after achievement of targets for material recycling and landfilling of biodegradable waste at the regional level)
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Technological alternatives
- options analysis for the comparison of different alternatives for transporting waste to a central treatment or
disposal facility from distant collection zones: transport with or without a waste transfer station for the
reloading of waste from small refuse collection vehicles to vehicles with larger payload and/or compaction
- options analysis for the comparison of different types of flue gas cleaning technologies in a waste-to-energy
facility
- options analysis for the inclusion of automatised separation of different recyclable materials from mixed waste
in the mechanical stage of mechanical-biological treatment plants and comparison of different systems available
on the market
4.2.6 Financial analysis
4.2.6.1 Investment cost
The time horizon for a project analysis is usually up to 30 years. In some cases, such as temporary
storage waste facilities, collection centres or landfills, shorter values may be however used.
Typical investment costs of waste management projects include:
civil works (including operational buildings, tanks, access ways, etc.)
plant and machinery
equipment and installations
trucks for collection, (re)loading and transport of waste
waste bins and containers
technical assistance cost elements for ensuring proper behaviour from the waste producers
(e.g. selection of waste, etc.)173
It is recommended to split the investment assets into main cost categories and assess their economic
life separately. The economic life of some project assets can be shorter or longer than the adopted time
horizon, in which case there will be a need for replacement or a residual value, respectively.
4.2.6.2 Operation and Maintenance costs
Projections of O&M costs shall be split into fixed and variable costs, with the latter in the form of
unitary cost per tonne of waste going through each stage of waste management. Typical operating cost
items of waste management investments are presented in Table 4.6.
Table 4.6 Typical O&M costs. Waste management sector
Main information
- energy (electricity, heat)
- fuels, materials and other consumables
- emission fees (for emissions to air and water)
Variable costs
- disposal of waste outputs produced in waste treatment facilities (only in case of projects dealing
with individual components of a larger waste management system)
- transportation costs
- technical and administrative personnel
Fixed costs - maintenance and repair
- insurance
173Note that these costs need to be maintained also after the completion of the project until a self-sustaining culture or environmentally
friendly behaviour is achieved.
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- services
Source: Authors
For certain facilities (such as landfills), closure costs and after-care costs following the closure of the
facility, should be considered as well as part of the residual value at the end of the reference period. In
developing the incremental O&M cost projections, clear assumptions shall be made for both with-
project scenario and the counterfactual without-project scenario (either do-nothing or do-minimum).
In particular, the choice of the counterfactual scenario follows the same logic as for IWS investments
(see box in section 4.2.5.2 above).
It is expected that the technical feasibility study will establish the incremental cost per unit of
produced waste on the basis of an analysis that takes into account the overall territorial integrated
waste management system.
4.2.6.3 Revenues projections
The identification of revenues in waste management projects depends on the typology of investment,
whether it addresses the entire waste cycle or just a segment of it. In the former case, typical sources
of revenues are:
the application of charges to users, either in the form of collection and disposal fees or taxes174;
the sale of sub-products such as compost, recycled materials, refuse-derived fuel or solid-
recovered fuel;
the sale of the energy recovered such as heat and electricity, including, as the case may be,
green certificates or bonuses for electricity produced from renewable waste fractions.
When the project concerns the entire waste management system, gate fees for individual waste
management facilities are considered transfer costs between the different service providers (i.e. for
waste collection, waste treatment, waste disposal in landfill) and therefore not included in the cash-
flows. That is, gate fees are ultimately paid by the users and included in the user fees paid for waste
management services.
On the contrary, if the project concerns only a segment of the waste management system (e.g. a waste-
to-energy plant or a selection for recycling plant), a price for the service provided will be charged to
the entities (municipalities, utilities, etc.) that ship the waste to be processed in the plant. Thus, gate
fees shall be considered as the project revenues. Similarly, in case of recycled materials, if the aim of
the project is to provide a service to third parties (e.g. to a consortium for the recycling of secondary
raw materials), the revenue is calculated based on the price paid for the waste processing service and
not on the sales price of the materials.175
Incremental fee/taxes charged to users shall be fixed at a level to recover the cost of providing the
service, including replacement costs for the equipment with shorter lifespan, so as to ensure the
overall financial sustainability of operations, while at the same time respecting affordability
constraints that might apply. The definition of fees or taxes that are affordable for all customers does
not imply that the same fee is applied to all. An affordability constraint for low income customers can
be overcome with a tariff structure with lower rates for low income customers, and higher rates for
the rest of the customers, including the non-residential ones (see Annex V).
4.2.7 Economic analysis
Waste management projects can produce different social benefits and costs, depending on the specific
typology of project implemented as compared to the counterfactual scenario. The main direct effects
174 In the waste management sector, taxes are considered as direct revenues, provided that the project promoters can demonstrate that they
are raised for the financing of the waste service and earmarked in that respect, with appropriate justification of the corresponding collection
mechanism.
175 Please note that even when the project concerns only a segment, it is however necessary to analyse the performance and investment
needs of the whole system with the aim of: i) ensuring technical adequacy of the solution; ii) measuring affordability for consumers.
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and externalities usually associated with the construction, modernisation and quality improvement of
the integrated waste management are summarised in the table below, together with the different
valuation methods suggested.
Table 4.7 Typical benefits (costs) for waste management investments
Impacts Type Valuation method
Resource savings: avoided waste to landfill Direct effect LRMC of landfill disposal
Resource savings: recovery of recyclable materials and
Direct effect Market values/border prices/ LRMC
production of compost
Resource savings: energy recovery Direct effect LRMC of the substituted energy
Hedonic price
Visual disamenities, noise and odours Externality
Stated preferences
Variation in GHG emissions Externality Shadow price of GHG emissions
Health and environmental hazards (variation in
Externality Shadow price of pollutants
contamination of air, water and soils)
Source: Authors
In what follows, the above-mentioned benefits and the relative methods for evaluation are more
extensively discussed.
4.2.7.1 Resource savings: avoided waste to landfill
For the purpose of the economic analysis of waste management projects, the reduction of the amount
of waste finally going to final disposal as a result of the project, which extends the economic life of the
landfills, should be credited with an economic value.
The data needed for benefit evaluation are:
quantification of the volume (tonnes) of waste that is not going to the landfill for final
disposal;
unit economic cost. The cost of landfill disposal per tonne of waste varies depending on the
size of the landfills, since there are significant economies of scale. Accordingly, the unit values
adopted by the project promoter should be specific to the project context and consistent with
the total annual waste generation in the project area that would otherwise go to the landfill. In
the absence of project-specific data, some reference values of total cost per year of landfill
disposal (taking into account both investment costs and operating and maintenance costs)
depending on plant’s capacity are provided in the study 'Costs for Municipal Waste
Management in the EU'176 (data should be updated to 2013 prices). 177
4.2.7.2 Resource savings: recovery of recyclable materials and production of compost
This benefit arises when the waste life-cycle closes, i.e. waste is used for making recycled products
(e.g. plastic, glass and metals) or for the production of compost. In this case the resource recovered
replaces the use of raw materials which, in turn, leads to cost savings from the societal point of view.
The economic value of the recovered recyclable materials and compost should be estimated at:
176 Prepared by Eunomia Research and Consulting in 2001 for the European Commission, DG Environment.
177 In those cases in which, in the absence of the project, a new landfill or the extension of an existing one would be needed, the avoided
capital and operating cost (including opportunity cost of land and costs for closure and after care) shall be used as project benefit.
Alternatively, and when feasible, the avoided cost of disposing of waste in a foreign country’s landfill can be taken as reference. See for
example “Research and Consulting in 2001 for the European Commission”, DG Environment.
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the corresponding market price for the service rendered, if prices are assumed to reflect the
opportunity cost of these products. Market prices should be justified along two dimensions:
o existence of an actual market for those products;
o consistency of the proposed prices with the existing market prices and comparable
qualities for the sub-products.
the corresponding border price for each sub-product, if market prices are assumed to be
distorted. The information required for the calculation of conversion factors (CF) could be
based on eco-industries data sets, or by national and international statistical offices or
Customs.178
4.2.7.3 Resource savings: energy recovered
This benefit arises when the waste is used for producing energy in the form of electricity or heat. In
other words, this benefit is associated with projects dealing with waste-to-energy plants, cogeneration
plants and biogas plants (with production of fuel gas, electricity and/or heat). In this case, the energy
recovered (using waste as source) replaces the use of energy from an alternative source/fuel (e.g.
coal) which, in turn, leads to cost savings.
For the estimation of the avoided cost thanks to the substitution of the energy source/fuel, please refer
to the methodology presented in section 5.7.4 of the energy chapter.
In the case of the substituted source being fossil fuel, an additional benefit related to displaced GHG
emissions through energy generation from clean sources is generated (see section 4.3.6.6 below).
4.2.7.4 Visual disamenities, noise and odours
The negative externalities usually associated with waste management installations consist of visual
disamenities, noise and odours. The negative impact of a landfill site, a waste incinerator or another
major waste facility in terms or disamenities is normally a fixed amount that does not vary
significantly with the amount of waste being disposed of or treated at the site but that depends on the
mere existence of the waste facility at the site.
Depending on the typology of investment, these negative externalities can be either reduced or
increased. Several methods are proposed in the literature to value in monetary terms these effects,
ranging from revealed preferences (hedonic price method based on the market values of real estates)
to stated preferences (WTP or WTA estimated via survey-based approaches).
The proposed approach of this guide for the estimation of the reduction/increase of visual
disamenities, noise and odours is the hedonic price method. The underlying concept is that the
proximity to a waste site causes a decrease in the value of the surrounding properties and, vice-versa,
the closing of an existing site has the opposite effect.
For benefit quantification, the following steps should be carried out:
first, it is necessary to fix the maximum territorial scope of the effect (or, in other words, to
define the 'affected area'). It is suggested to establish the maximum distance from the site
perimeter for the effects to unfold on a case-by-case basis, depending on the characteristics
and size of the waste facility and the urban structure around the site179;
second, the surface and market value of the existing real estates in the affected area shall be
estimated on the basis of land register;
178 As an alternative, for some specific materials such as metals, their opportunity cost can be estimated as the difference between their long-
run marginal cost and the cost of production from the virgin source.
179The economic literature suggests a distance up to 5 km as maximum limit for the affected area. See for example Brisson I.E and Pearce
(1998) 'Literature Survey on hedonic property prices studies of landfill disamenities'
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third, real estate price reduction (increase) should be calculated by looking at the land
register value of real estates in similar zones that are (not) affected by a dump site180;
finally, the following simplified formula181 can be applied in order to obtain the value of the
benefit:
B = ∑𝑖 𝑆𝑖 ∗ 𝑉𝑖 ∗ 𝛥%
where: i is the type of property; S is the total surface of properties i (in m2); V is the observed
value of properties (in Euro/m2); Δ% is the expected percentage increase/decrease in price
because of the project.
The result (B) is the estimated increase/decrease in property values as a result of a project.
4.2.7.5 GHG emissions
A reduction of GHG emissions is achieved when waste is: i) treated to reduce and stabilise the
biodegradable components before being properly disposed, ii) recovered in form or materials which
are sent to recycling, and/or iii) used for energy generation in substitution of fossil fuels182. In the first
case, the decrease of GHG emissions, mainly methane (CH4), originates from the diversion of untreated
biodegradable waste from landfills. In the second, materials recovered from waste enable savings in
GHG emissions that would have resulted from the extraction and processing of raw materials. In the
third, the waste-to-energy and co-generation (e.g. biogas) plants enable a reduction in GHG emissions
that would have been produced by the alternative energy source.
The method suggested to monetise the saved GHG emissions from waste management projects
consists of multiplying the amount of emissions avoided (expressed in CO 2-equivalents per year, see
below) by their unit economic costs.
The quantification of GHG emissions avoided due to treatment and proper disposal of waste should
be based on the following.
Specific emission factors for the waste management facilities (expressed in tonnes GHG/tonnes
of waste throughput), multiplied by the amount of waste treated (in tonnes of waste
throughput per year). By comparing the situations with the project and the counterfactual
scenario183, it is possible to estimate the emissions change attributable to the project. The
calculation of the specific emission factors will however require the knowledge or estimation
of the average composition of the waste treated184;
specific emission factors for the electricity and heat sources displaced by the project (in tonnes
of CO2 per MWh produced), multiplied by the amount of energy produced [in gigajoules (GJ) or
megawatts (MWh) produced per year];
180 Usually, the effect ranges between 1.5 % to 12.8 % of the property value (Brisson I.E and Pearce, 1998). In absence of data, an
averaged 5 % reduction (increase) can be adopted as proxy.
181 In line with the practical orientation of the Guide, the proposed formula is a shortcut for benefit estimation, especially useful when data
availability is low. When the data allows, analysts engaging in the hedonic price method should estimate a hedonic price function,
encompassing a wide range of variables including characteristics of the house or land affected, locational/accessibility characteristics,
neighbourhood characteristics and environmental characteristics, such as proximity to the waste facility and having a direct view of the
facility. The coefficients of these latter variables will give an estimate of the marginal impact of the waste facility on real estate prices,
controlling for all other variables.
182 Only carbon dioxide emissions that result from non-renewable resources ('fossil' fuels) should be included in the benefit estimation
because these increase the net amount of CO 2 in the atmosphere, whereas CO2 emissions from renewable sources can be considered as
neutral emissions and should be therefore omitted.
183 Note that the choice of the counterfactual (do-nothing or do-minimum) has implications with respect to the consideration of diffuse
emissions due to landfill, as the landfill of non-stabilised/untreated biomass is to be phased out according to the EU acquis.
184In this respect, it should be also noted that specific emission factors can vary throughout the project’s time horizon because of future
changes assumed in the composition of wastes to be treated or landfilled.
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specific emissions avoided through recycling of materials recovered by the project185 (in CO2
per tonne of material recycled) multiplied by the amount of material recovered from waste
sent to recycling (in tonnes per year).
In the absence of project-specific emission factors for the waste management facilities, average default
emission factors can be derived from literature. For example, the 'EMEP/EEA air pollutant emission
inventory guidebook' provides guidance for the estimation of emissions for all major waste
management practices.
In the case of avoidance of emissions due to energy recovery, the quantification of the volumes
avoided follows the same logic illustrated below, in section 5.7.6 of the energy chapter. Generally
speaking, CO2 emissions in the generation of electricity depends on the fuel and the efficiency of the
facility used for electricity generation and ranges from 0.40 kg CO2/kWh in the case of Combine Cycle
Turbines (CCGT) to 0.95 kg CO2/kWh in the case of coal. Similarly, CO2 emissions in the generation of
heat also depends on the fuel and the generation efficiency of the facility used for heat production and
ranges from 0.27 kg CO2/kWh in the case of gas boilers to 0.45 kg CO2/kWh in the case of electric
heating.
In order to evaluate the cost of CH4 emissions, the tonnes of CH4 emitted have to be converted into CO2-
equivalents and then monetised following the instructions provided in Chapter 2, section 2.9.9.
4.2.7.6 Health and environmental hazards
The treatment of municipal solid waste produces emissions of specific pollutants into the air, water
and soil.
For waste incineration, the main conventional pollutants emitted to the air are NOx, SO 2, ozone
precursors, particulates, heavy metals and dioxins. Such emissions are minimised through efficient
flue gas cleaning systems that remove particulates and pollutant gases before the remaining flue gas is
emitted to the air via the smokestack. Solid residues from waste incineration and flue gas treatment
(including slag and bottom ash, fly ash and air pollution control residues) are disposed of at proper
disposal sites, partially as hazardous waste. The flue gas cleaning processes may also give rise to
emissions to water through wastewaters produced. These emissions are controlled using various
physical-chemical wastewater treatment processes, which produce a filter cake which is disposed as
hazardous waste.
For waste landfills, in addition to volatile organic compounds and dioxins, leachate is generated and
emitted to the surrounding soil and water. Impacts related to the emission of leachate to the soil
include the migration of contaminants to groundwater and/or surface water, where they can affect
human health and the ecosystem. At compliant, engineered landfill sites, emissions to the soil are
minimised through effective leachate collection and treatment systems.
Following the same logic of the reduction of GHG emissions, a reduction of emission of pollutants to
the air, water and soil is achieved by implementing modern waste management systems. The recovery
of energy in the form of heat and/or electricity from waste also reduces emissions of air pollutants
from other energy sources that use fossil fuels.
To estimate the external cost of pollutant emissions, the usual approach consisting of quantifying the
emissions avoided thanks to the project (measured in kg per tonne of waste) and valuing them with a
unit economic cost (measured in euro per kg emission) applies.
Regarding the quantification stage, pollution pathways of emission are very project specific; they
depend on a large number of variables including the quality of the recipient body (soil or water), the
specific location of the plant, the technology used, the measures adopted for soil protection, etc. Thus,
they should be calculated case by case with default emission factors being hardly usable or even not
existing.
185 Data is available, for instance, in EC, (2001,) Waste management options and climate change. Available at:
(http://ec.europa.eu/environment/waste/studies/pdf/climate_change.pdf)
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Regarding the valuation stage, most of the available information in the economic literature is on the
marginal cost of air emissions and less information exists on the emissions cost to soil and water.
Focussing on air emissions, the same sources mentioned in the transport chapter can be taken as
reference (see section 3.7.6). As alternative, the Commission’s Impact Assessment on the review of the
National Emission Ceilings Directive186 can be used to value the external costs of health impacts, crop
yield loss and damage to buildings owing to air pollution.
4.2.8 Risk assessment
Sensitivity tests of the results of both financial and economic analyses to changes in the value of the
considered variables is mandatory. Sensitivity analysis of solid waste projects is advisable for both
market-related variables and the value of non-market goods. More specifically, the CBA results should
be tested for changes at least of the following variables (when relevant for the project):
assumptions on GDP trend
demographic trend
waste composition (e.g. possible reduction of the calorific value)
number of years necessary for the realisation of the infrastructure
investment costs (as disaggregated as possible)
O&M costs (as disaggregated as possible)
unit fee for waste collection and disposal or unit price for waste treatment service
(avoided) cost of landfill disposal
unit price of sub-products or of selection service
fuel and energy prices
quantities and shadow prices assumed for GHG emissions
quantities and shadow prices assumed for pollutant emissions.
On this basis, a risk assessment must be carried out, typically, by assessing the risks presented in the
following table.
Table 4.8 Typical risks in waste management projects
Stage Risk
- Changes of environmental requirements, economic and regulatory instruments (i.e.
Regulatory
introduction of landfill taxes, bans on landfilling)
- Waste generation lower than predicted
Demand
- Waste flow control/delivery insufficient
- Inadequate surveys and investigation
Design - Choice of unsuitable technology
- Inadequate design cost estimates
- Building or other permits
Administrative
- Utility approvals
- Land costs higher than predicted
Land acquisition
- Procedural delays
Procurement - Procedural delays
- Project cost overruns
Construction - Delay in construction schedule
- Contractor related (bankruptcy, lack of resources)
186 European Commission (2013), Commission Staff Working Document Impact Assessment. Brussels, 18 December 2013. Available at:
http://ec.europa.eu/smart-regulation/impact/ia_carried_out/docs/ia_2013/swd_2013_0531_en.pdf
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- Waste composition other than predicted or having unexpectedly large variations
- Maintenance and repair costs higher than predicted, accumulation of technical
Operational breakdowns
- Process outputs fail to meet quality targets
- Failure to meet limits of emissions produced by the facility (to air and/or water)
- Tariff increases slower than predicted
Financial
- Tariff collection lower than predicted
Other - Public opposition
Source: Adapted from Annex III to the Implementing Regulation on application form and CBA methodology.
4.3 Environment remediation, protection and risk prevention
4.3.1 Introduction
As specified in Article 9(5-6)(Thematic objectives) of Regulation (EU) No 1303/2013, environment
remediation, protection and disaster risk prevention and management are key objectives of the
cohesion policy within the broader policy framework for adaptation to climate change. The following
principles apply when defining the investment priorities under the ERDF and Cohesion Fund;
development of strategies and action plans for environmental management at national,
regional and local level for building up a knowledge base and data observation capacities, and
mechanisms for the exchange of information;
increased investments to preserve natural capital, e.g. avoiding damage and increasing
resilience to the built environment and other infrastructure, protecting human health,
investing in flood and coastal defences and decreasing the vulnerability of ecosystems;
development of tools and disaster management systems, to facilitate disaster resilience and
risk prevention and management for natural risks;
priority will be given to projects with demonstration and transferability potential including
green infrastructure and ecosystem-based approaches to adaptation, and projects aiming to
promote innovative adaptation technologies. This comprises both hard and soft technologies,
such as more resilient construction materials or early warning systems. New capital intensive
infrastructures, such as dams, dikes, etc. should be supported only where ecosystem-based
solutions are not available and/or insufficient.
A selective list of policy and regulatory documents is provided in the box below.
THE EU POLICY FRAMEWORK
Climate change
EU Strategy on Adaptation to Climate Change
White Paper 'Adapting to Climate Change – Towards a European Framework for Action'
Guidelines on Climate Change and Natura 2000
Protection of natural capital
EU Biodiversity Strategy
EU Green Infrastructure Strategy
Directive 2009/147/EC on the conservation of wild birds
Directive 92/43/EEC on the conservation of natural habitats and of wild fauna and flora
Directive 2008/50/EC on ambient air quality and cleaner air for Europe.
Marine Strategy Framework Directive
Strategy on the sustainable use of natural resources
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Natural risk prevention
Directive 2007/60/EC on the assessment and management of flood risks
Given the strategic orientation, the investments expected to be financed under the Major project
financing mechanism – which are the object of the section - include the following categories:
remediation of polluted sites (e.g. water bodies, hazardous waste or radioactive dump sites,
etc.);
preservation of natural assets (ecosystems and biodiversity e.g. protection, restoration or
nourishment of coastal zones, beaches, forests, natural parks, protected areas, etc.) with or
without a use value;
reduction of vulnerability and exposure to natural hazards (e.g. hydraulic rehabilitation of
rivers to reduce possible impacts of flooding). The main risks include both weather-related
(such as storms, extreme temperature events, forest fires, droughts, floods) and geophysical
risks (such as avalanches, landslides, earthquakes, volcanoes).187
4.3.2 Description of the context
These projects are largely a local/regional topic as it is the local/regional authorities that are first
confronted with the potential impacts of environment deterioration or natural disasters and have to
implement prevention measures. At the same time, cross-territorial and cross-sector impacts must be
kept in consideration188. For this reason, place-based approaches are fundamental for the effectiveness
of the projects.
The baseline context elements recommended to be described for the projects under assessment are
shown in the following table.
Table 4.9 Presentation of the context
Main information
- Data about the population living in the involved area
Socio-economic/
- Description of the existing economic activities and services
demographic - Data on agricultural sector
- Reference to EU directives and sector policy documents (see above)
Political, - Reference to the priority axis and the intervention areas of the OP
institutional and - National/regional strategies on adaptation to climate change
regulatory factors - National civil protection / risk management strategies or plans
- Reference to flood risk management policies
- Quality and environmental status of the affected area
189 190
Environmental - Parks, SCI , SPA , other protected areas established in the affected area and their
framework management systems
- Areas subject to high hydro-geological risks or other environmental risks
- Location of the intervention and extension of the involved area
- Morphological, geographical and geological features
Technical - Weather and climate conditions
- Existence of sites of natural or cultural interest
- Pollution and contamination in soil, groundwater, sediment and surface water bodies
Source: Authors
187 In some cases, this is also accompanied by the provision of adaptive infrastructures in case of a disaster, e.g. the implementation of an
emergency plan in case of forest fires.
188 For example, for flood risk prevention there could be issues that go eventually beyond national boundaries and therefore require
coordination at supra-national level.
189 Site of Community Importance, Directive 92/43/EEC, of 21 May 1992, Habitats Directive.
190 Special Protection Area, Directive 2009/147/EC of 30 November 2009, Birds Directive.
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4.3.3 Definition of objectives
In a broad perspective, environmental management aims at increasing the resilience and security of
the society as a whole and of human, natural and fixed capital. In particular, the following needs can be
addressed:
protecting human health;
protecting buildings and other assets, including the productive ones;
'climate proofing' the built environment and the existing infrastructures;
decreasing pressure on natural resources;
protecting coastal zones, forests and natural parks from deterioration;
increasing the ecosystem’s resilience.
In particular, the appraisal of this kind of projects can be used as an important tool to:
mainstream climate change, loss of biodiversity and natural risk prevention into integrated
spatial development planning;
evaluate risk management measures and make exposed infrastructure or other facilities more
hazard-resilient;
raise awareness and education on the importance of climate change, biodiversity and disaster
risk management.
Table 4.10 below reviews the main objectives per project typology.
Table 4.10 Main general objectives
Objectives
- To remove deep and surface pollution or contaminants from environmental assets
such as soil, groundwater, sediment, or surface water bodies for the general protection
Remediation of polluted of human health and the environment.
site areas
- To remove pollution or contaminants from a brownfield site intended for
redevelopment.
- To maintain Europe’s biodiversity, for instance by ensuring the ecological coherence
191
Preservation of natural and connectivity of the Natura 2000 network .
assets - To safeguard and restore valuable natural ecosystems and assets at a broader
landscape level so that they can continue to deliver valuable services to mankind.
- To boost natural disaster resilience of the disaster-prone areas more vulnerable to
extreme weather events and natural disasters, such as floods, landslides, avalanches,
Prevention of natural forest fires, storms, wave surge
disasters - To support local economies (e.g. in agriculture and forestry sectors) by reducing
vulnerability to natural risks, adapting to climate change, maintaining sustainable
livelihoods and fostering green growth.
Source: Authors
4.3.4 Project identification
The scope is on investments for the remediation of polluted site areas, the preservation of natural
assets and/or the reduction of the risk of natural disasters. Typical features regarding the project
identification stage are:
191Natura 2000 is an ecological network established under the Habitats and Birds Directives. It comprises more than 26 000 sites spread
across all the Member States and occupies 18 % of the EU’s land territory and around 4 % of marine waters within Member States’
jurisdiction. It was established mainly to conserve and protect key species and habitats across the EU, but it also delivers many ecosystem
services to human society.
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the integration of the physical interventions into a planning measure, e.g. a disaster risk
management plan, that is implemented at national or regional level;
linked with the above, these projects consist, in most cases, of both 'soft' components and
physical realisations. For instance, 'soft' solutions such as the ecological restoration of
floodplain forests (and other non-structural solution/green infrastructures) can be made in
combination with infrastructure for disaster reduction, such as river protection works. Or,
together with a dam construction, software management tools for weather forecasting can be
used to support the infrastructure operations;
interventions can be designed adopting a 'soil bioengineering approach' so as to pursue
technological, ecological, economic and design goals by making use of living materials (i.e.
seeds, plants, part of plants and plant communities) and employing them in near–natural
constructions while exploiting the manifold abilities inherent in plants.
Options analysis is particularly important and should consider global alternatives as well as solutions
closely linked to the local context.
4.3.5 Demand analysis
The projects that fall within this area of intervention are bound to result in a multitude of ecosystem
services that will benefit a wide range of users (and non-users). It is therefore important to define and
quantify who and what will benefit from the intervention, in terms of territorial areas, population,
buildings and various economic activities.
This is particularly important for natural risk prevention projects. The project promoter should
carefully analyse the key structural features of the areas for which the natural risk is reduced after the
implementation of the project. This includes, at least, a quantification of the surfaces affected and the
number of inhabitants and buildings (in other words, land use data, as far as possible detailed and
broken down by use: residential, commercial, industrial, touristic, etc.) that will be subject to the
identified risk (to a different extent) before and after the project is implemented.
A different situation arises when projects address natural assets that are a destination for tourism and
leisure activities or a land that, after reclamation, has become suitable for economic activities; in other
words, when projects address assets that have a use value. Examples include a protected area that is
visited for its naturalistic heritage; a restored beach or lake used for bathing or other water-related
recreational activities (e.g. fishing); a newly‐remediated land that is sold for agricultural purposes. In
these, and all other cases where a use value exists, a quantification of the number of users, as well as
an analysis of the potential market for economic activities, must be carried out for both with- and
without-the-project scenarios.
4.3.6 Financial analysis
4.3.6.1 Investment and operating costs
In the case of environmental management projects the time horizon is project specific, depending on
the typology of the environment asset and the relative intervention concerned. Thus, benchmark
values can hardly be proposed.
On the costs side, a distinguishing characteristic of these projects lies in the fact that, besides the
typical investment and operating costs associated with carrying out and operating the physical
realisations (infrastructure), other costs associated with the 'soft' components should be added. These
may refer to costs relating to institutional and capacity building of appropriate national, regional and
local institutions, or costs relating to flood management, climate-change mitigation and adaptation
measures, ICT tools, technical assistance and upgrade of the monitoring systems and means for
implementation of environmental controls.
Proper maintenance is critical to ensure the achievement of its objectives throughout the reference
period. To that extent, since O&M costs for this type of infrastructure are normally covered by public
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budgets, a clear commitment and identification of the resources allocated to cover O&M costs needs to
be provided by the promoter.
4.3.6.2 Revenue projections
Financial inflows hardly ever exist for projects aimed at natural risk prevention. On the contrary, in the
case of remediation of polluted site areas or preservation of natural assets that have a use value,
financial revenues can be generated by:
the rent of a restored natural asset for the provision of leisure-related services (e.g. bathing,
fishing, hunting);
the sale or rent of remediated land for residential zoning, industrial or agricultural purposes;
the tickets paid by the visitors of a natural park or a protected area, if any.
4.3.7 Economic analysis
Depending on the specific typology of project implemented, different benefits can be produced (Table
4.11) and different methods proposed for their evaluation (Table 4.12).
Table 4.11 Typical benefits
Ecosystem
Improved Increased Increase in
Productive and Reduction of
health recreational property
use of land biodiversity damages
conditions value values
preservation
Remediation of
polluted sites √ √ √ √
Preservation of
natural assets √ √ √
Natural risk
√ √ √* √ √
prevention
* In flood projects, especially when there is a proper adoption of green infrastructure solutions, the project can achieve
multiple objectives, including the restoration of ecosystems.
Source: Authors
Table 4.12 Typical benefits: valuation methods
Benefit Type Valuation method
- Stated preferences
- Revealed preferences (hedonic wage method)
Improved health conditions Direct
- Human capital approach
- Cost of illness
- Market value
Productive use of land Direct
- (Gross Value Added)
- Travel cost method
Increased recreational value Direct
- Benefit transfer
- Stated preferences (contingent valuation)
Ecosystem and biodiversity preservation Direct
- Benefit transfer
- Average avoided damage
Reduction of damages to properties Direct
- Risk premium insurance
- Stated preferences
Increase in property values Indirect
- Hedonic price
Source: Authors
In what follows, the above-listed benefits and the relative methods for evaluation are more extensively
discussed. Note that not all benefits will be necessarily relevant to all projects, and judgment is
required to identify which of them can justifiably be attributed to the project. On the other hand, the
list is not exhaustive: the project promoter could consider additional benefits, taking care however not
to double count the same benefit.
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4.3.7.1 Improved health conditions
Changes in human mortality and morbidity rates can be triggered by the projects aimed at:
remediating a polluted environment,
natural risk prevention.
In the former case, the project promoter should first estimate the avoided cases of human mortality
and morbidity based on dose‐response functions and on estimation of the dose received by members
of the polluted site(s). For example, in the case of remediation of a radioactive dump, estimates of
airborne transmission rates, measures of the radioactivity of the dust and exposure data can be taken
from scientific studies in order to estimate the dose received by the affected population. Based on this
dose, it would then be possible to estimate the risk of exposure‐induced death and/or illness, to which
unit economic costs shall be attached.
In the latter, quite obviously, it is not possible to predict when an actual disaster will occur and with
what intensity. Thus, the effectiveness of disaster prevention projects is estimated through risk and
vulnerability assessments that include a degree of uncertainty because they depend on a large number
of factors ranging from the deterministic socio-economic characteristics of the area to the probabilistic
nature of the event and its magnitude. Therefore, while costs are well defined, benefits derived from
avoided losses are not definitive, but are rather probabilistic, at best. Once the probabilistic
distributions of risks exposure are obtained, the project promoter should quantify the effect of the
project in terms of probability of avoided losses to people and the severity of the avoided impact.
As illustrated before, the preferred approach to value changes in health outcomes is to calculate
WTP/WTA. This can be done via stated preference methods (surveys) or revealed preference methods
(hedonic wage method). In practice, when this is not possible, one can use the human capital approach
(for mortality) or the cost of illness approach (for morbidity), in different sections. For the evaluation
of mortality, see section 3.8.4 in the transport chapter. For reduction of morbidity from pollution-
related diseases, see section 4.1.7.6.
4.3.7.2 Productive use of land
This benefit is related to the recovery of land, which, after the implementation of reclamation or
natural risk prevention measures, can be used for residential zoning, agricultural and/or industrial
purposes, e.g. thanks to the removal of restrictions on the use of land because of the health or human
hazard associated with it.
The rationale underlying this benefit is that a land value is created (or preserved) after the project
intervention:
if it is expected that the land will be actually rented or sold, the market value can be taken as
proxy of its opportunity cost, provided that no relevant market distortions exist, and the
relevant information will be derived from the financial analysis accounts;
if land is not actually sold or rented, its value can be estimated on the basis of real market
transactions for a comparable land in the vicinity to be used as benchmark. If this is not
possible, then other reference figures may be used e.g. based on national statistics. The benefit
will equal the recovered area multiplied by the value of the land per unit area.
Alternatively, when feasible, another possible method for benefit evaluation is to consider the gross
value added (GVA) of the agricultural, industrial or commercial activities that will be carried out on
the recovered land. The project promoter should however take care to avoid any benefit double
counting, by considering only the incremental GVA that is expected due to the project. That is, to make
sure the increase of GVA is attributable to the project only and not to other variables in the system,
such as a future services empowerment of the affected area.
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4.3.7.3 Increased recreational value
This is the main benefit associated with the recovery, or the preservation, of natural sites with a
recreational value (e.g. beaches, natural parks and protected areas) where leisure activities such as
trekking, picnicking, bathing, fishing, hunting, etc. can be carried out.
The estimation of this benefit implies pricing the recreational use of a specific natural area regardless
of whether the entry is free or not. Indeed, natural recreational sites often are free to enter.
The standard method for estimating the value of a natural recreational site is the travel cost method.
As explained in Annex V, it consists of collecting data on the travel costs for accessing the recreational
site or the natural amenity and estimating an incremental demand, which will be a function of: the
attributes of the site (e.g. its location); the travel cost to reach the site, and the characteristics of the
users. It is worth mentioning that the travel cost includes not only the actual monetary cost of travel,
but also the appropriate value of travel time as well as an estimation of other costs related to the visit
such as food, beverages and accommodation costs. As an alternative, the benefit transfer approach
can be used.
4.3.7.4 Ecosystem and biodiversity preservation
This category of benefit refers to the non-use value of ecosystem and biodiversity preservation
The WTP for the simple existence of the ecosystem and the biodiversity in good conditions must be
estimated following the same logic depicted in section 4.1.7.4 'Improved quality of surface water
bodies and preservation of ecosystem services' (i.e. contingent valuation or benefit transfer).
Within the possible sources where to obtain unit costs, 'The Economic benefits of the Natura 2000
Network'192 provides a synthetic analysis of a range of benefits flowing from the network, based on
secondary data from a number of studies of values delivered by different habitats. The available
estimates give a range of values ranging from EUR 50 per hectare per year to almost EUR 20 000 per
hectare per year. This depends on the service provided, location of the site and its conditions. For
these reasons, values should be adjusted to reflect the specificities of the context under analysis. Also,
the possibility of undertaking primary studies at EU or national level for the complex category of
ecosystem and biodiversity preservation benefits estimation is encouraged.193
4.3.7.5 Reduction of damages to properties
This benefit is related to the implementation of interventions aimed at preventing and reducing the
impact of natural disasters (that can also be the consequence of the changing climate), such as the
development of tools and systems for risk mapping, assessment and detection (e.g. early warning, alert
systems) and of infrastructure realisations for risk prevention and mitigation. In addition to the
improvement of health conditions, already discussed in section 4.3.7.1, natural risk prevention is also
associated with the reduction of damages to properties.
The estimation of avoided damages to capital (infrastructures, buildings and machineries) and natural
(forests, biodiversity) stocks incurred by both the public and the private sectors to repair or replace
the damaged assets, and to manage the emergency, should be based on the average avoided damage
methodology. The information and data needed to implement this method should come from properly
developed flood risk and hazard maps, in combination with flood modelling, as required by the Floods
Directive. Alternatively, a practical approach consists of adopting the market insurance premiums
available for these typologies of risks proxy to the value of the avoided property damages. For those
(public) assets where an insurance market does not exist, averaged calculations based on the avoided
costs of the public administrations for civil protection activities, compensation paid to citizens,
relocations of buildings, etc. should be carried out and added to the economic analysis.
192 Available at: http://ec.europa.eu/environment/nature/natura2000/financing/docs/ENV-12-018_LR_Final1.pdf.
193 As stated in the Natura 2000 report, ‘There is a clear need for further site based studies which are more geographically spread across the
EU, that cover a wider range of ecosystem services and are done in a comparable manner which would help create an improved evidence
base for future assessments’ (p.21).
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4.3.7.6 Increase in property values
This benefit, which is the increase of real estate values after project realisation, can be generated by all
the typologies of intervention treated in this section. For example, due to the disamenities and health
hazards linked with living in a polluted environment, people generally prefer to avoid living in or close
to these sites/areas. Similarly, if an area is at risk of natural disaster, this leads to a measurable
decrease in the value of the residential properties. On the other hand, the restoration and opening of a
natural amenity such as a natural park can lead to properties appreciating in value in the surrounding
areas.
The methodology for the estimation of the increase in property values is based on the hedonic price
approach (or, alternatively, stated preferences) and follows the same logic illustrated in section 4.2.7.4
about the evaluation of visual disamenities, noise and odours from waste management. What is worth
remembering here is that the magnitude of the effect can be very different. For instance, radioactive
contamination represents a much more serious disamenity than the impacts associated with a sanitary
landfill. As a consequence, the positive impact of a remediation intervention is likely to be greater. The
same can be said in the case of prevention of disasters, e.g. flooding. If, after project implementation,
the affected areas will become eligible for residential zoning, the values of the already existing
properties will be significantly appreciated.
4.3.8 Risk assessment
The main risks that should be assessed in the risk analysis are illustrated in the table below.
Table 4.13 Main categories of risk
Risks
- Unexpected political or regulatory factors affecting the project
- Inadequate surveys and investigation
- Procedural delays
- Delays in construction
Remediation of - Contractor bankruptcy/ lack of resources
polluted site areas
- Cost overrun
- Surface of the land devoted to economic activities lower than expected
- Sale or rent prices lower than expected
- Legal constraints
- Unexpected political or regulatory factors affecting the project
- Inadequate surveys and investigation
- Forecasting errors
- Procedural delays
Preservation of - Delay in construction schedule
natural assets and/or - Contractor related (bankruptcy, lack of resources)
biodiversity - Investment costs overrun
- O&M costs higher than expect
- No of visitors lower than expected
- Unexpected natural events damaging the asset
- Unexpected lower resilience of the natural assets
- Unexpected political or regulatory factors affecting the project
- Inadequate surveys and investigation with consequent inadequate technical design
- Inadequate information regarding historical disaster occurrences
- Underestimation of natural risk frequency or probability of disaster occurrences
Prevention of natural - Underestimation of the effects of climate change (e.g. about the correlation 'magnitude
disasters
versus frequency' of weather events)
- Procedural delays / Delay in construction
- Contractor bankruptcy, lack of resources
- Investment and maintenance costs
Source: Authors
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Case Study – Water and Waste Water
Infrastructure
I Project description
The project consists of two components: a) the construction of a new wastewater treatment plant to
achieve compliance with the requirements of Directive 91/271/EEC194 in a medium-sized city
(population 375 000), as well as associated investments in wastewater collection infrastructure to
reduce infiltration, increase collection rates and ensure the collected wastewater is transported to the
new wastewater treatment plant; b) the extension of the water supply network to increase the number
of people connected to the public water supply system.
Currently there is no wastewater treatment facility in the city, which was defined as an agglomeration
according to Directive 91/271/EEC. Although wastewater is collected from a large part of the
population (about 95 %) in an existing network, the outflow is discharged untreated into the river
running through the city. The current status of the river is declared as 'moderate' in the river basin
management plan. The existing network is a separate system, with separate collection of rainwater,
and it has been established that it is generally in good condition and fit for purpose to deliver
wastewater of adequate concentration for treatment. However, some targeted investments on
wastewater network rehabilitation will also be undertaken where high levels of repairs have been
reported. The city is located in a new Member State with an assumed derogation from compliance with
the Urban Wastewater Treatment Directive (EC/97/271) (agglomerations above 100 000) to 2020.
The current service operator is responsible for water supply as well as wastewater collection and is
100 % owned by the municipality. It will also take ownership and be responsible for operation and
maintenance of the new assets constructed under the project
II Project objectives
The main objective of the project is to ensure increased environmental integrity and compliance with
the Urban Waste Water Treatment Directive and with the National Programme of Water Supply and
Wastewater Treatment through incremental collection and compliant treatment of wastewater load,
and extension of water supply coverage. Collection rates are expected to increase to 99 % by extending
the sewage network to a further 15 000 people and ensuring that the connection rate (i.e. transfer to a
compliant WWTP rather than untreated discharge directly to the recipient water body) is 100 %. An
estimated 7 500 people will also be connected to the public water supply network, thereby increasing
overall water supply coverage to 99.5 %.
Sludge will be dried and composted to allow final disposal to agricultural land. Finally, the chemical
status of the river running through the city will be improved from 'moderate' to 'good' in accordance
with the definitions of the Water Framework Directive.
The project objectives are well aligned with the main goals of the priority axis 1 - 'Water and Sewerage
Management' of the operational programme 'Environment & Infrastructure'. In particular, the
investment will contribute to the achievement of the following operational programme targets at
national level:
194
Council Directive 91/271/EEC of 21 May 1991 concerning urban wastewater treatment
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1 OP Project
Indicator
2023 target (% of target)
Additional population newly connected to public
120 000 7 500 (6.25 %)
water supply system network
Additional population newly connected to the
300 000 15 000 (5 %)
sanitary sewage system network
Increase in the number of agglomerations meeting the
requirements of Directive 91/271/EEC (numbers)
10 1 (10 %)
including: agglomerations
over 100 000 p.e (population equivalent)
1The OP does not explicitly state objectives for improvements in water bodies, as wastewater treatment significantly affects
mostly chemical status. Wherever possible, such as this case study, impacts on water body chemical status will be defined.
III Demand analysis
The demand analysis was carried out based on available statistics and forecasts for the main macro-
economic and social indicators, on current measured consumption rates for water and production of
wastewater in the agglomeration, as well as on the implementation schedule of the works proposed
under the project.
The population forecast was based on previous figures from the past census and the estimated future
growth of the population realised by the National Statistics Institute, which anticipate a general
decline in population at a rate of about 0.25 % per annum.
Domestic consumption in the agglomeration currently accounts for about 70 % of total and is
relatively low at around 120 l/c/d as a result of a phased increase to full cost recovery tariffs over the
last decade. At this level of consumption, there is a relatively low elasticity of demand to further price
increases195, whereas the current tariff represents about 2.7 % of household income. However, further
tariff increases associated with the project are expected to trigger a stable decrease in consumption to
115 l/c/d, while tariffs rise to 3 % of household income, and are maintained at that level to comply
with the chosen tariff strategy.
Towards the end of the forecasting period, from around year 22, real growth in household income
(estimated at about 0.3 % per annum) results in tariffs falling below the 3 % threshold and in a
moderate increase in consumption rates associated with income elasticity. Wastewater is produced at
a rate of 0.8 to 0.85 of water production, but the practice of the operator is to bill wastewater at the
rate of water consumption (for simplicity of billing).
Commercial and institutional production accounts for about 20 % of total and is forecasted to develop
in direct proportion to domestic consumption. This amount includes consumption from commuters
and occasional visitors (the city is not a major tourist destination). Industrial consumption comprises
the remaining 10 % and, after falling during the transition to a free market economy, it has recently
shown signs of recovery and is forecasted to grow by 2.5 % per annum over the next 10 years (and
thereafter remain constant). Total WWTP capacity is designed for 525 000 p.e., allowing for 375 000
population, as well as further estimated 100 000 and 50 000 p.e. from commercial/institutional and
industrial production respectively.
A summary of forecasted demand is shown in Table 1 below.
195
Elasticity factors have been derived by the analysis of consumption patterns over the last years in several water
operators in the country.
\168
Table 1: Demand Analysis
1 2 3 4 5 6 7 8 9 10 11 12 13 14 29 30
DEMAND
Construction Operation
Calculation of Forecast Demand
Population 000s 375.0 374.1 373.1 372.2 371.3 370.3 369.4 368.5 367.6 366.6 365.7 364.8 363.9 363.0 349.6 348.7
Per Capital Consumption l/c/d 120.0 120.0 120.0 115.0 115.0 115.0 115.0 115.0 115.0 115.0 115.0 115.0 115.0 115.0 123.0 124.0
Water
Population Connected % 97.5% 98.0% 98.5% 99.5% 99.5% 99.5% 99.5% 99.5% 99.5% 99.5% 99.5% 99.5% 99.5% 99.5% 99.5% 99.5%
Domestic Consumption m m2 16.0 16.1 16.1 15.5 15.5 15.5 15.4 15.4 15.4 15.3 15.3 15.2 15.2 15.2 15.6 15.7
Commercial & Institutional m m3 4.6 4.6 4.6 4.4 4.4 4.4 4.4 4.4 4.4 4.4 4.4 4.4 4.3 4.3 4.5 4.5
Industrial m m3 2.3 2.3 2.4 2.5 2.5 2.6 2.7 2.7 2.8 2.9 2.9 2.9 2.9 2.9 2.9 2.9
Total m m3 22.9 23.0 23.1 22.4 22.5 22.5 22.5 22.5 22.5 22.5 22.5 22.4 22.4 22.3 22.9 23.0
Waste Water
Population Connected % 95.0% 96.0% 97.5% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99% 99% 99.0%
Domestic Consumption m m3 15.6 15.7 15.9 15.5 15.4 15.4 15.4 15.3 15.3 15.2 15.2 15.2 15.1 15.1 15.5 15.6
Commercial & Institutional m m3 4.6 4.6 4.6 4.4 4.4 4.4 4.4 4.4 4.4 4.4 4.4 4.4 4.3 4.3 4.5 4.5
Industrial m m3 2.3 2.3 2.4 2.5 2.5 2.6 2.7 2.7 2.8 2.9 2.9 2.9 2.9 2.9 2.9 2.9
Total m m3 22.5 22.7 22.9 22.4 22.4 22.4 22.4 22.4 22.4 22.5 22.4 22.4 22.3 22.3 22.9 23.0
Incremental Demand due to extension of network (included in
the above)
Water m m3 0.0 0.1 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
Waste Water m m3 0.0 0.2 0.4 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6
IV Option analysis
The analysis and evaluation of different options were carried out taking the following criteria into
account:
comparison of centralised and de-centralised solutions;
financial evaluation of different options where appropriate;
comparison of technical solutions concerning treatment processes.
In particular, alternatives in the following dimensions have been considered:
wastewater treatment strategy;
WWTP location;
sludge management;
wastewater network rehabilitation.
Wastewater treatment strategy
Consideration was given to building a single WWTP or two local plants serving separate sides of the
river. Based on a discounted cash flow analysis of capital and operating cost, the former was seen as
more cost efficient, despite the need to pump water from the left bank of the river to the location of the
treatment plant on the more populous right bank.
Table 2 Option Analysis: WWTP Strategy
NPV WWTP NPV Network NPV Operating NPV Total Ranking
Alternative Investment Investment Cost Cost
Cost
EUR EUR EUR EUR
WWTP Strategy 1: Two
smaller plants and
networks serving 45 000 000 8 000 000 37 000 000 90 000 000 2°
different sides of the
river
\169
WWTP Strategy 2:
Single plant and
network covering
38 000 000 10 000 000 32 000 000 80 000 000 1°
whole city with tunnel
under the river to link
the two networks
WWTP location
The number of suitable sites was restricted, but six possibilities were isolated and examined.
Ownership and spatial planning restrictions reduced the options to two, which were subject to
discounted cash flow analysis (including forecast of related operating costs). The chosen option is
downstream the agglomeration and slightly elevated above the river bank, requiring a small amount of
pumping, but was still shown as least costly compared to the alternative at a lower elevation in the
flood plain, which would have required construction of an expensive collector through a narrow and
environmentally sensitive river gorge.
Table 3 Option Analysis: WWTP Location
NPV WWTP NPV Network NPV Operating NPV Total Ranking
Alternative Investment Investment Cost Cost
Cost
EUR EUR EUR EUR
WWTP Location 1:
Lower elevation, but
38 000 000 12 000 000 31 000 000 81 000 000 2°
requiring high cost of
main collector
WWTP Location 2:
Higher elevation,
requiring some 38 000 000 10 000 000 32 000 000 80 000 000 1°
additional pumping
cost.
Sludge Management
The alternatives for final handling and use of sludge are shown below and are based on the following
assumptions:
sludge quality meets the criteria of the EC Sewage Sludge Directive 86/278/EEC and there is
adequate land available for re-use (Option 1);
the sludge is processed at the WWTP in a digester and dewatered to a total solid concentration
of 20 %;
the sludge is collected at an intermediate storage at the WWTP;
the WWTP receives a load corresponding to 525 000 p.e. and the sludge production is
estimated at some 50 000 m3/year (total solid at 20 %).
Table 4 Option Analysis: Sludge Management
NPV Investment NPV Operating Cost NPV Total
Alternative Cost Ranking
EUR EUR EUR
Option 1: Re-use in
agriculture and/or energy 0 13 000 000 13 000 000 1°
crops (after dewatering)
\170
Option 2 : Drying and use
as a fuel in cement or 5 000 000 21 100 000 26 100 000 2°
power plant
Option 3: Drying and
incineration of sludge and 22 000 000 33 500 000 55 500 000 3°
deposit of ash at landfill
Wastewater network rehabilitation
Justification for sewage network rehabilitation was made taking into account the financial benefits of
reduced operating costs, estimated at EUR 0.5 million per annum relative to an investment cost of
EUR 4.5 million. On a discounted cash flow basis, this results in a positive NPV of EUR 2.2 million.
However, reduction in infiltration also benefits the operation of the wastewater treatment plant. The
beneficiary has good data on historical breaks in the system and has demonstrated that the areas of
highest problems have been targeted.
V Project costs and revenues of selected option
The total project investment costs of the selected option are derived from technical feasibility studies,
and are in line with estimates received from contractors for similar projects in other agglomerations in
the region. The detailed cost breakdown is presented in Table 3 below.
Table 5 Project Cost Breakdown (in m EUR)
Ineligible
Project Investment Cost (m EUR) Total cost 196 Eligible cost
cost
Planning/design fees 4.0 - 4.0
Building and network assets (pipes) 44.0 - 44.0
Equipment and machinery 10.0 - 10.0
Technical assistance 2.5 - 2.5
Publicity 1.0 - 1.0
Supervision during implementation 3.0 - 3.0
Contingencies 5.5 - 5.5
Sub-TOTAL 70.0 - 70.0
VAT 14.0 14.0 -
TOTAL 84.0 14.0 70.0
All costs are eligible for EC grant funding apart from VAT (which is recoverable by the beneficiary).
Incremental operational cost resulting from the project amount to EUR 3.5 million per annum, being a
combination of costs and savings brought about by it as follows:
EUR 2.6 million associated with running the new wastewater treatment plant;
EUR 0.8 million associated with sludge handling;
EUR 0.4 million and EUR 0.2 million associated with maintenance of new waste water and
water network respectively;
EUR 0.5 million of savings associated with reduced costs from wastewater network
rehabilitation.
Of the EUR 3.5 million incremental cost, EUR 2.5 million is estimated as variable with respect to
volume, with the remainder fixed. In practice, changes in volumes at the level forecasted will not have
Ineligible investment cost includes cost incurred before the beginning of the programming period (for planning/design and land purchase)
196
and VAT
\171
a large impact on operating costs. Further, a small profit margin at 3 % is allowed, which is subject to
income tax at 50 %.
The replacement of short-life assets (plant equipment and machinery) needs to be undertaken every
10 years (although can be phased over a two-year period), and the relevant amounts are included
within incremental operating cost when performing the calculation of the discounted net revenue
(Article 61(3)(b) of Regulation (EC) No 1303/2013). This implies a depreciation rate on such assets equal
to 10 % per annum, whereas for the civil works and other assets (mainly pipes) this rate is taken as
2 % per annum. This results in a total incremental depreciation charge of EUR 2.2 million per annum.
The national authority has a policy of charging full cost recovery tariffs, based on operating costs
including depreciation. However, a separate national guidance states that tariffs should not exceed 3 %
of average household income, to remain within affordability limits. The current tariff is about EUR 1.44
per m3 (water and wastewater combined) and is equal to about 2.7 % of household income.
According to the agreed tariff strategy, the tariff will be steadily increased to cover 100 % of
incremental operating cost and a rising proportion of depreciation, while remaining all the time within
the affordable level as required by national guidance. Thus, in the first year of project operations (year
4 of projections), about 13 % of incremental depreciation is covered, 17 % is covered in year 5 and so
on until 100 % is covered in year 22. The water utility is not compensated for this lost income, which is
temporary and reduces from year to year. It can still be shown as sustainable, with cumulative cash
flows remaining always positive (see Table 7 below), but as a consequence the utility has limited
capacity to contract debt (due to the impact on yearly generated cash flows) and it looks to the
municipality to co-finance part of the investment197.
As previously stated, the national authority has a policy of charging full cost recovery tariffs, subject to
affordability constraints. Thus the tariff is set to cover all operating costs and depreciation, including
that proportion of the investment financed by grant funds. This follows the requirements of Article
9(1) of the Water Framework Directive to ensure that the tariff represents the full cost of the use of a
scarce resource and also that the utility is allowed to accumulate sufficient funds for long-term
replacement without having again to rely on grant subsidy. However, this full cost recovery tariff is a
target level which can only be achieved (in this case) after 20 to 25 years due to affordability
constraints.
Table 6 Affordability and Tariff
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 29 30
Affordability and Tariff
Construction Operation
Calculation of Affordability Constrained Tariff
Actual Monthly Per Capita Household Income Euro 194 195 195 196 196 197 197 198 199 199 200 200 201 202 202 211 212
Forecast Growth in Household Income (Real Terms) Euro/m3 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3%
Without Project Revenue M EUR 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.6 32.6 32.6 32.4 32.4
Without Project Tariff Euro/m3 1.44 1.44 1.44 1.44 1.44 1.44 1.44 1.44 1.44 1.44 1.44 1.44 1.45 1.45 1.45 1.47 1.47
% of Household Income % 2.71% 2.70% 2.69% 2.69% 2.68% 2.67% 2.66% 2.65% 2.65% 2.64% 2.63% 2.62% 2.62% 2.61% 2.60% 2.50% 2.49%
Project Incremental Operating Costs M EUR 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.6 3.6
Project Incremental Depreciation M EUR 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2
Project Incremental Profit Margin M EUR 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
With Project Revenue (for FCR) M EUR 32.7 32.7 32.7 38.5 38.6 38.6 38.6 38.6 38.6 38.6 38.6 38.5 38.5 38.5 38.5 38.3 38.3
With Project Tariff (for FCR) Euro/m3 1.71 1.71 1.70 1.70 1.70 1.70 1.70 1.70 1.71 1.71 1.71 1.71 1.73 1.73
% of Household Income % 3.17% 3.16% 3.16% 3.15% 3.14% 3.13% 3.12% 3.11% 3.10% 3.09% 3.08% 3.07% 2.94% 2.93%
% of Incremental Opex Covered by Incremental Tariff % 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%
% of Incremental Depn Covered by Incremental Tariff % 13% 17% 22% 27% 32% 37% 42% 47% 52% 57% 62% 67% 100% 100%
Actual With Project Revenue M EUR 32.7 32.7 32.7 36.5 36.6 36.7 36.8 36.9 37.0 37.2 37.2 37.3 37.4 37.5 37.6 38.3 38.3
Actual With Project Tariff Euro/m3 1.44 1.44 1.44 1.61 1.62 1.62 1.62 1.63 1.63 1.64 1.64 1.65 1.66 1.67 1.67 1.73 1.73
% of Household Income % 2.71% 2.70% 2.69% 3.00% 3.00% 3.00% 3.00% 3.00% 3.00% 3.00% 3.00% 3.00% 3.00% 3.00% 3.00% 2.94% 2.93%
197 An alternative model would be for the municipality to compensate the lost revenue, thereby allowing the utility to contract debt, but this
leaves the municipality with an on-going commitment and is less commonly used.
\172
VI Financial and economic analysis
The financial and economic analysis of the project is based on the incremental approach and the
following assumptions:
all amounts stated in constant EUR;
real discount rate of 4 % in financial analysis and 5 % in economic analysis;
reference period of 30 years;
residual value of EUR 14.8 million for FRR and EUR 70.5 million for ERR.
The residual value is estimated as the net present value of the project net cash flow (or net economic
benefits for the economic analysis) over the 14 years after the end of the projections, being an
estimate of the residual economic life of the assets198. Built into this estimate is provision for an
additional replacement of plant and machinery (estimated life of 10 years) as well as a
decommissioning cost, which is relatively low due to the expected continued use of the site for similar
activities.
The reference period of 30 years was applied in accordance with the indicative value suggested by the
delegated act on revenue generating operations and it is in line with common international practice
for this type of project.
Financial analysis
The project is a revenue generating operation in the meaning of Article 61 of Regulation (EU)
1303/2013. The authorities have elected to do a calculation of the discounted net revenue (rather than
adopting a flat rate)199. In this case, the EU contribution is determined by multiplying the eligible cost
as shown in section V above (EUR 70 million) with the pro-rata application of discounted net revenue
(76.2 %) and the co-financing rate of 85 % for the relevant priority axis, which results in EUR 45.3
million. The remaining EUR 24.7 million is to be financed from the municipal budget. The municipality
has confirmed that is willing to co-finance the project and can afford this contribution (over a three-
year period) without breaching its statutory debt constraints.
Table 7 Calculation of EU Grant
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 29 30
EU GRANT
Construction Operation
Calculation of Discounted Investment Cost (DIC) NPV 4%
Total investment (w/o contingencies)1 M EUR -60.2 -18.7 -22.8 -23.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
DISCOUNTED INVESTMENT COST (DIC) M EUR -60.2 -18.7 -22.8 -23.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Calculation of Discounted Net Revenues (DNR) NPV 4%
Incremental Revenues M EUR 70.7 0.0 0.0 0.0 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.8 4.9 5.0 5.9 5.9
M EUR 0.0
O&M costs - WWTP (Variable) M EUR -23.2 0.0 0.0 0.0 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6
O&M costs - WWTP (Fixed) M EUR -14.5 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
O&M costs - WW Extension (Variable) M EUR -5.8 0.0 0.0 0.0 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4
O&M costs - WW Rehabilitation (Variable) M EUR 7.2 0.0 0.0 0.0 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5
O&M costs - Sludge (Variable) M EUR -11.6 0.0 0.0 0.0 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8 -0.8
O&M costs - Water Extension (Variable) M EUR -2.9 0.0 0.0 0.0 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2
M EUR 0.0
Replacement Costs M EUR -10.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -5.0 -5.0 0.0 0.0 0.0 0.0
Residual value of investments M EUR 4.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 14.8
DISCOUNTED NET REVENUES (DNR) M EUR 14.2 0.0 0.0 0.0 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 -3.9 -3.7 1.4 1.5 2.4 17.2
ELIGIBLE COST M EUR 70.7
Pro-rata Application of DNR = (DIC - DNR) / DIC: 76.4%
MAX CO-FINANCING RATE IN PRIORITY AXIS: 85.0%
EU GRANT ( = EC x PRO-RATA x CF): M EUR 45.9
1
Contingencies comprise Eur 4.5m and are excluded from investment cost for the purposes of the Pro-rata calculation (as also is VAT which is recoverable)
198 Based on a weighted average of the physical lifetime of the different asset categories, the overall economic life of the project is estimated
at 41 years after implementation.
199 As set out in Article 61(3)(b) of Regulation (EU) 1303/2013
\173
The financing plan for the project is presented in the following table in million EUR:
Financing Sources m EUR % share
EU grant 45.3 53.9 %
Public contribution (Municipality) 24.7 29.4 %
Project beneficiary’s contribution (ineligible investment cost - VAT) 14.0 16.7 %
Total funding 84.0 100.0 %
Ineligible cost due to VAT payments will be covered by the operator using a special facility set up in
the national ministry of finance for the implementation of EU funded projects, which allow VAT costs
to be progressively repaid through normal billing operations over several years, thereby not adversely
affecting cash flow or financial sustainability.
The financial profitability indicators of the project are calculated as follows:
Table 8 Calculation of FRR/(C) and FRR/(K)
FRR/(C)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 29 30
Construction Operation
FRR/(C) before Community assistance NPV 4%
Total investment (w/o contingencies) M EUR -59.6 -18.5 -22.5 -23.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Revenues M EUR 70.7 0.0 0.0 0.0 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.8 4.9 5.0 5.9 5.9
O&M costs M EUR -61.0 0.0 0.0 0.0 -3.5 -3.5 -3.5 -3.5 -3.5 -3.5 -3.5 -3.5 -8.5 -8.5 -3.5 -3.5 -3.6 -3.6
Residual value of investments M EUR 4.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 14.8
Project cash-flow before Community assistance M EUR -45.4 -18.5 -22.5 -23.5 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 -3.9 -3.7 1.4 1.5 2.4 17.2
FRR/(C) before Community assistance -2.2%
FRR/(K)
FRR/(K) with Community assistance NPV 4%
National Grant M EUR -22.8 -7.0 -8.7 -9.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Interest payments M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Principal repayments M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M costs M EUR -61.0 0.0 0.0 0.0 -3.5 -3.5 -3.5 -3.5 -3.5 -3.5 -3.5 -3.5 -8.5 -8.5 -3.5 -3.5 -3.6 -3.6
Revenues M EUR 70.7 0.0 0.0 0.0 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.8 4.9 5.0 5.9 5.9
Residual value of investments M EUR 4.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 14.8
Promoter cash-flow after Community assistance M EUR -8.6 -7.0 -8.7 -9.0 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 -3.9 -3.7 1.4 1.5 2.4 17.2
FRR/(K) with Community assistance 1.8%
Thus FRR/(C) at -2.2 % is well below the discount rate of 4.0 % showing that the project needs grant
financing support, whereas FRR/(K) at 1.8 % shows that the envisaged level of support remains within
a reasonable range and does not provide for an excessive return to national capital.
With respect to the long-term financial sustainability of the project, the project itself generates
incremental revenue with a cumulative cash surplus over its life. However, the sustainability of the
utility as a whole (i.e. 'with project scenario') will need to be monitored, taking account of the current
(i.e. 'without project') level of tariff and operating cost, as well as the incremental costs and servicing
on any current or future debt that may be required. This is especially important given that the tariffs
are set below full cost recovery in the short term in order to meet affordability constraints. For the
current project, the cash flow can be summarised in the table below which shows that the project is
financially sustainable (cumulative cash flows always positive over the reference period).
Table 9 Sustainability
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 29 30
Sustainability
Construction Operation
Project Cash Flow
Without Project Revenue M EUR 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.7 32.6 32.6 32.6 32.4 32.4
Project Incremental Revenue M EUR 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.8 4.9 5.0 5.9 5.9
Total Revenue M EUR 32.7 32.7 32.7 36.5 36.6 36.7 36.8 36.9 37.0 37.2 37.2 37.3 37.4 37.5 37.6 38.3 38.3
Without Project Operating Costs (including Tax) M EUR 22.9 22.9 22.9 22.9 22.9 22.9 22.9 22.9 22.9 22.9 22.9 22.9 22.9 22.8 22.8 22.7 22.7
Project Incremental Operating Costs M EUR 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.6 3.6
Project Incremental Income Tax M EUR 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
Without Project Maintenance & Replacement M EUR 7.0 7.0 7.0 14.0 14.0 7.0 7.0 7.0 14.0 14.0 7.0 7.0 7.0 14.0 14.0 14.0 14.0
Project Incremental Maintenance & Replacement M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.0 5.0 0.0 0.0 0.0 0.0
Total Costs M EUR 29.9 29.9 29.9 40.4 40.4 33.4 33.5 33.5 40.5 40.5 33.5 38.4 38.4 40.4 40.4 40.3 40.3
Cash B/F M EUR 0.5 3.3 6.1 9.0 5.0 1.1 4.3 7.7 11.1 7.7 4.3 8.1 7.0 6.0 3.1 24.4 22.4
Cash Generated M EUR 2.8 2.8 2.8 -4.0 -3.9 3.2 3.3 3.5 -3.4 -3.3 3.8 -1.1 -1.0 -2.9 -2.8 -2.0 -2.0
Cash C/F M EUR 3.3 6.1 9.0 5.0 1.1 4.3 7.7 11.1 7.7 4.3 8.1 7.0 6.0 3.1 0.2 22.4 20.4
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Economic analysis
The economic analysis was carried out using an incremental approach, comparing economic cost and
benefits of the project over a 30-year period of analysis, which is the same as used in the financial
analysis. It was carried out in constant prices and used a social discount rate of 5 %.
The financial costs of the project were used as a basis to estimate its economic costs, by correcting the
non-skilled labour component in the investment and operating costs with a shadow wage that takes
into account the current unemployment level in the project area (with a Conversion Factor equal to
0.8).
No other conversions from financial to economic prices were deemed necessary (i.e. all remaining CFs
were set to 1), as the project components would be procured through an open, competitive
international tender, and local services and goods are considered adequately priced in the local market
(given its high degree of openness with the EU internal market).
The project-generated incremental tariff revenues were excluded from the economic analysis on the
grounds that they were not considered as a good proxy to monetise the project’s direct benefits and its
positive externalities. Instead the main expected socio-economic benefits of the project were taken
into account, as shown in the following table:
Value
Monetisation of project benefits
Total EUR 145.1 m
Benefit for improved environmental quality of the water bodies (WTP)
The implementation of the project will considerably improve the environmental quality of the river
crossing the city, which currently receives untreated wastewater discharge. This is expected to
increase the use of the river and its surrounding for recreational activities (use value).
As this use value is difficult to monetise and no specific study exists in the concerned Member State,
the benefit was valued using a benefit transfer method (see Annex VI for further details on this
methodology).
Based on a careful assessment of willingness-to-pay (WTP) studies performed for evaluating EUR 118.5 m
environmental externalities linked to wastewater treatment in comparable socio-economic and
environmental conditions, this benefit was valued at EUR 25/person/year starting from the first year of
operation, and for the total population living in the agglomeration (i.e. 375 000)
Since WTP measures generally depend on income levels, annual values would have to be projected
by increasing them following real per capita GDP growth over the project reference period. However, in
light of the uncertainties related to the estimation of the benefit value, it was decided to take a
conservative assumption, and keep the monetary value of the benefit fixed at its initial level throughout
the reference period.
Resource cost savings attributed to users newly connected to the wastewater network, who
now no longer need to maintain and operate closed tanks
Users newly connected to the sewage collection system as part of the project would not need to
continue incurring the costs of installing and maintaining closed tanks, which involve annual capital and EUR 19.0 m
O&M expenditures. Based on a benchmarking of average costs for an adequate individual treatment
system in the agglomeration, the benefit related to these cost savings was valued at an estimated EUR
100/person/year, for the population newly connected to the wastewater network (i.e. 15 000).
Resource cost savings attributed to users newly connected to the water supply network, who
now no longer need to maintain and operate water wells, as well as purchase drinking water
from other sources
Users newly connected to the water supply system as part of the project would not need to continue
incurring the costs of constructing and maintaining private water wells, which involve annual capital
EUR 7.6 m
and O&M expenditures, nor to continue purchasing drinking water from other providers. Based on a
survey conducted by the operator with these potential clients on the average costs for private wells and
alternative drinking water sources in the agglomeration, the benefit related to these cost savings was
valued at an estimated EUR 80/person/year, for the population newly connected to the water supply
network (i.e. 7 500).
The project is expected to deliver other benefits, such as direct health benefits. However, these
benefits are difficult to quantify and to clearly attribute to the project, not to mention the risk of
double counting benefits already captured by the values used in the analysis. As such they are
considered in qualitative terms, as further supporting the economic analysis.
\175
Based on these assumptions, the project showed satisfactory economic indicators with economic
benefits exceeding economic cost:
Economic indicators Values
Economic Rate of Return (ERR) 11.1 %
Economic Net Present Value (ENPV) EUR 54.9 m
Benefit - Cost Ratio 1.61
Table 10 Calculation of ERR and economic cost-benefit ratio
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 29 30
ERR
Construction Operation
TOTAL
Project investment cost (w/o contingencies) M EUR 64.6 18.5 22.5 23.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
of which:
Traded goods and skilled labour 51.7 14.8 18.0 18.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Non-traded goods 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Unskilled labour 12.9 3.7 4.5 4.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Land purchase 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Taxes 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Conversion Factors
Traded Goods and Skilled Labout Coef. 1.0
Non-traded goods Coef. 1.0
Unskilled Labour Coef. 0.8
Taxes Coef. 0.0
ERR NPV 5%
M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Benefit for improved environmental quality (WTP) M EUR 118.6 0.0 0.0 0.0 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.4
Direct savings to users no longer needing closed tanks M EUR 19.0 0.0 0.0 0.0 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5
Direct savings to users no longer needing wells M EUR 7.6 0.0 0.0 0.0 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6
Total investment (w/o contingencies) M EUR -56.1 -17.8 -21.6 -22.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M costs M EUR -53.0 0.0 0.0 0.0 -3.5 -3.5 -3.5 -3.5 -3.5 -3.5 -3.5 -3.5 -8.5 -8.5 -3.5 -3.5 -3.6 -3.6
Adjust O&M (unskilled labour) M EUR 2.5 0.0 0.0 0.0 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
Residual value of investments M EUR 16.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 70.5
ERR M EUR 54.9 -17.8 -21.6 -22.6 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2 3.2 3.2 8.2 8.2 8.1 78.6
ERR 11.1%
B/C RATIO 1.61
Based on the positive economic indicators resulting from the analysis, the implementation of the
project is expected to increase social welfare and it is therefore worth supporting with a grant from
the EU. It will also contribute to meeting the agreed national targets in compliance with the Urban
Waste Water Treatment Directive (and thus also avoid possible financial penalties).
VII Risk assessment
Sensitivity analysis
The sensitivity analysis assesses the effects of possible changes in the key project variables on the
project’s financial and economic performance indicators. In both the financial and economic analysis,
the analysis is carried out using aggregated and selected disaggregated variables (i.e. demand and
prices separately) to better identify possible critical variables.
The elasticity calculated for the ENPV and FNPV/(C) with respect to the different input variables 200, as
well as their switching values201, are shown in the table below.
ENPV Switching FNPV/(C) Switching
Variable
elasticity value elasticity value
Increase in investment cost 1.1 % 90 % 1.4 % 70 %
Reduction in valuation of economic benefits 3.1 % 32 % - -
Reduction in tariff (and therefore revenue) - - 14.8 % -7 %
Reduction in volumes of water i.e. demand - - 2.0 % -50 %
The elasticity is defined as the percentage change in the NPV indicator for a +1 % change in the variable.
200
The switching value is the percentage change required in an input variable to make the NPV indicator turn 0.
201
\176
(both with and without scenario)
increase in incremental operating costs as a
1.0 % 105 % 1.4 % -73 %
result of the project
The sensitivity analysis shows that, in the economic analysis, increase in investment cost, increase in
operating cost and reduction in the valuation of economic benefits are the most critical variables. The
relevant switching values to reduce ENPV to zero are shown as an increase of investment cost by 90 %,
an increase in operating cost by 105 % and a reduction in the valuation of benefits by 32 %. Note that,
as already stated, economic benefits are valued on a per capita basis, assuming full implementation of
the project, and are not a function of the incremental tariff revenue or volume of water billed.
In respect of the financial analysis, increase in investment cost, or increase in operating cost, as well as
reduction in tariff or volume, are seen as the most critical. A 70 % reduction in investment cost, 73 %
reduction in operating cost, 76 % increase in tariff or 50 % increase in volumes billed (the latter
assuming an impact on both with and without scenario), would result in a project FNPV of zero.
However, the key observation point is that the impact of tariffs on financial viability, and therefore also
sustainability, is very critical, as is to be expected. As can be seen in table 7 above, the cash flow
generated breaks even over about a 15-year period (after which it goes into permanent surplus).
Significant reductions in revenue would result in sustainability issues.
Risk analysis
Based on the results of the sensitivity analysis and taking into account uncertainties related to aspects
not directly reflected in the CBA calculations, a risk matrix was prepared in order to identify possible
risk prevention and mitigation measures.
The risk analysis shows that the residual risks for the project are low as a result of the measures
envisaged to prevent the occurrence of the identified risks and/or to mitigate their adverse impact in
case these should materialise.
All in all, the overall level of residual risk is deemed to be acceptable. It can be therefore concluded
that the probability of the project failing to attain its targeted objectives is marginal, provided that the
mitigation measures listed above are duly implemented.
Residual
Proba Sever Risk risk after
Risk description bility* -ity level* Risk prevention / mitigation measures prevention
(P) (S) (=P*S) /mitigation
measures
Demand side risks
Household demand (at 120 l/c/d) is already at the low
end of expectations and is expected to decrease a
further small amount to 115 l/c/d as a result of price
elasticity. There is more uncertainty in the context of
industrial demand, but this is only about 10 % of the
Volumes of water
total. A large part of the beneficiary’s cost structure is
consumed and
fixed (rather than variable with respect to volume).
wastewater B III Low Low
Thus changes in consumption can (and will have to
produced fall below
be) compensated through adjustment to the tariff,
level forecast
which can be done with limited impact on affordability
(see also next point below).
Function in charge: Municipal government in
coordination with project beneficiary (municipally
owned operating company)
Financial risks
As shown in the sensitivity analysis above, this is the
most critical issue for sustainability.
Tariffs will not be
approved at the Moder The municipal government approves the tariff, but
B IV subject the national law on tariff, which requires full Low
level required for ate
sustainability cost recovery, sets out the cost items which should
be included and requires a re-evaluation every year
to account for any changes in volumes consumed.
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Residual
Proba Sever Risk risk after
Risk description bility* -ity level* Risk prevention / mitigation measures prevention
(P) (S) (=P*S) /mitigation
measures
This system has been shown to work over recent
years with tariffs already reaching an appropriate
level with respect to the existing services.
Further tariffs are allowed to be restricted to keep
within 3 % of household income, following national
guidance on affordability, provided that this can be
shown not to compromise short-term sustainability.
Thus, the immediate tariff rise required is only around
12 % (on top of inflation) and should not result in
political opposition when the project benefits are
taken into account.
Function in charge: Municipal government in
coordination with project beneficiary
Current revenue collection levels exceed 99 % and
revenue collection discipline among the population is
good. As tariffs are not allowed to exceed 3 % of
Users will not pay
B III Low household income, further rises of only around 12 % Low
the tariffs required
(plus inflation) are required, which is not expected to
raise issues
Function in charge: Project beneficiary.
This was also identified as a critical risk in the
sensitivity analysis above.
Investment cost estimates compare well with costs
experienced with similar projects implemented in the
region and contain an element of contingency (10 %)
Investment cost Moder
C III to meet the first tranche of over-run (if any). Low
overrun ate
Nevertheless close monitoring of cost relative to
budget should be undertaken (at least quarterly) to
allow management and mitigation of any over-runs
should such occur.
Function in charge: Project beneficiary.
Existing cost structure is well established and forms a
good basis for projections. Incremental cost
Operating cost associated with new investments (especially WWTP)
B II Low Low
overrun has more uncertainty, but compromises a relatively
small part of overall operating cost.
Function in charge: Project beneficiary
Local public grants comprise the residual element of
the financing plan on top of EU finance.
Problems with The municipality has shown it can afford its
Moder
availability of local B IV contribution by reference to line items in its future Low
ate
co-financing budget, which also shows it can stay within its legal
debt limits.
Function in charge: Municipal government
Implementation risks
Land for both new WWTP and new pipeline
Problems with land extensions is either publically owned or (in a few
B II Low Low
purchase cases) relevant permissions have been obtained.
Function in charge: Project beneficiary.
Promoter’s procurement division to be supported by
Delays related to specialised technical assistance. Procurement and
Moder
extension of tender C III build schedule appears feasible and has adequate Low
ate
procedures contingency to fit within the eligibility period.
Function in charge: Project beneficiary.
Operational risks
Flow of wastewater Project has been designed to include the necessary
to WWTP (i.e. collectors to link outflows to the WWTP – under a
B III Low Low
connection) will not single financing plan.
be achieved Function in charge: Project beneficiary.
\178
Residual
Proba Sever Risk risk after
Risk description bility* -ity level* Risk prevention / mitigation measures prevention
(P) (S) (=P*S) /mitigation
measures
Failure of WWTP
technology to Selection of proven, best-available technologies
A IV Low Low
achieve project Function in charge: Project beneficiary.
objectives
Legislation in force requires users to connect within
Failure of
12 months or in any case pay for wastewater
customers to
B III Low discharge. Additionally, the utility will streamline the Low
connect to the
approval process for making connections.
network
Function in charge: Project beneficiary.
* Evaluation scale: Probability: A. Very Unlikely; B. Unlikely; C. About as likely as not; D. Likely; E. Very Likely.
Severity: I. No effect; II. Minor; III. Moderate; IV. Critical; V. Catastrophic.
Risk level: Low; Moderate; High; Very High
\179
Case Study – Waste Incinerator with
Energy Recovery
I Project description
The project foresees the construction of a new waste-to-energy (WtE) plant with a nominal capacity
for incineration of 200 000 tonnes of mixed municipal solid wastes per year (25 tonnes per hour, 62.5
MW thermal input capacity202), which will co-generate heat and power with nominal capacities of 40
MWth and 13 MWel. The design of the plant incorporates best available technology (BAT) fully in line
with the requirements of Directive 2010/75/EU203.
The project is located in a region of a new Member State eligible for the Cohesion Fund with around
1.3 million inhabitants and total municipal waste generation of currently 585 000 tonnes per year. A
large part of this waste is currently sent to landfills without treatment, which is considered an
unsustainable practice in the long term and does not comply with legal provisions and targets
provided by the EU Waste Framework Directive, Landfill Directive and the Waste Management Plans
adopted at national and regional level. This precarious situation and the recent decision of the central
government to gradually introduce a landfill tax as a way to make landfilling a less attractive waste
management option and to promote the construction of waste treatment facilities that give priority to
material and energy recovery are currently the promoter's main incentives for the development of the
project.
The project will be part of the region’s integrated waste management system, which is divided into
two catchment areas, one in the north, strongly rural in character, and one in the south, which
accounts for a large part of the region’s urban population as well as most of its commercial and
industrial activity. The system currently includes two engineered landfills serving each of the two
catchment areas, a mechanical-biological treatment (MBT) plant with a total throughput capacity of 50
ktpa conveniently located on the landfill site in the northern area and two composting facilities for
green waste from private and public gardens and parks also located at the landfill sites.
The WtE plant has been designed to treat residual mixed wastes produced in the three largest towns in
the south of the region (representing together around 50 % of the region’s total population and
around 60 % of total municipal waste generation). With the proposed capacity of 200 ktpa it will allow
the region to meet future targets on landfilling of biodegradable waste without interfering with
current efforts to increase separate collection rates for selected recyclables.
The project promoter and beneficiary of the WtE plant is a new company established to implement
and later operate the new plant. The company is co-owned by the regional government and the local
governments of the region’s three largest towns. The construction of the plant will be tendered out in
the second half of 2013 based on a design-build contract (FIDIC (International Federation of
Consulting Engineers) yellow book contract) and begin in Q1 2014. Upon termination of the
construction phase (Q3 2016), the contractor will support and prepare the new staff during the start-
up phase of the plant for commercial operations to start in January 2017.
The site chosen for the plant is a formal industrial complex in the outskirts of the largest of the three
towns with good connections to the road system and to all relevant utilities. The land is owned by the
municipality and will be sold to the project at market price. The heat produced in the WtE plant will be
fed into the district heating system of the municipality and will cover around one half of the system’s
summer baseload (40 MW), which is currently provided by a coal-fired heat boiler. The electricity will
202
Based on an annual availability of 8 000 hours and average energy content of the waste of 9 MJ/kg
203
Directive 2010/75/EU of the European Parliament and of the Council of 24 November 2010 on industrial emissions (integrated pollution
prevention and control)
\180
be fed into the national electricity grid and benefit from a premium paid under a national support
scheme for electricity produced in high-efficiency co-generation204.
II Project objectives
The general project objective was formulated as follows:
The project shall improve waste management practices in the region with the aim of reducing the
negative impacts on human health and the risks of environmental pollution in accordance with
relevant national and EU legislation in the sector of municipal solid waste management.
In addition, the following specific objectives were formulated for the project:
to reduce the amount of total waste and biodegradable waste currently disposed of in landfills
in the region;
to recover materials and energy contained in the waste in line with the EU’s waste
management hierarchy.
Although not a main project objective, the project will also contribute to the increase of the quantity of
energy generated from renewable sources partially replacing energy generated from fossil fuels.
After project implementation, the following quantifiable benefits are expected to materialise:
reduction of landfill space used for the disposal of untreated municipal waste, resulting in an
extension of the service life of the existing landfills and thus also of landfill costs;
recovery of ferrous metals and energy contained in the waste which can be sold on the market;
reduction of greenhouse gas emissions due to the diversion of biodegradable waste from
landfill and partial replacement of fossil fuels used for the generation of heat and electricity205.
The project objectives are well aligned with the main goals of priority axis 2 – 'Sustainable waste
management' of the national operational programme 'Quality of the Environment'. In particular, the
investment will contribute to the following OP output and result indicators:
OP target Project
2023 (% of target)
Output Indicator
New capacity for treatment and stabilisation of mixed residual municipal wastes 1 400 200 (14 %)
(in ktpa)
Result Indicators
Annual amount of biodegradable waste diverted from landfill 670 96 (14 %)
(in ktpa)
Annual amount of energy recovered from waste 10 700 1 530 (14 %)
(in TJ/y)
The project is also in line with the requirements of the EU Landfill Directive206 in so far as it
contributes towards the fulfilment of the targets for diversion of biodegradable waste going to landfill,
which are also incorporated in the national and regional waste management plans for the period
2014-2020. Through the reduction of emissions of GHGs, the project will also contribute to the climate
change target and the objectives of the sustainable growth dimension of the Europe 2020 strategy.
204
The electricity production qualifies as high-efficiency co-generation in line with Directive 2012/27/EU (Energy Efficiency Directive) and
hence the plant also meets the R1 energy efficiency formula as defined in Directive 2008/98/EC (Waste Framework Directive). The financial
support is further described in section V below (project costs and revenues).
205
There will be a net reduction of GHG emissions even though the plant will release the fossil CO2 contained in the waste (mainly in plastics
and rubber materials). For more details see section on the quantification of economic benefits.
206
Directive 99/31/EC of 26 April 1999 on the landfill of waste.
\181
III Demand analysis
The following table shows the forecast of municipal waste generation, collection and treatment for the
region which is coherent with the base case scenario outlined in the Regional Waste Management Plan
(RWMP). The forecast is based on:
a detailed analysis of historic waste generation and waste composition for different sources in
the region (years 2008-2012);
a long-term demographic forecast for the region which projects an average population growth
of -0.2 % p.a. during the period of analysis (item 1);
a long-term forecast of macro-economic growth at national and regional level;
a forecast of waste generation for different types of waste which envisages a diminishing
growth of per capita waste generation from +1.5 % p.a. in 2013 to +0.5 % p.a. in 2020 and to -
0.5 % p.a. on average in the ten years thereafter (item 2). This is taking into account the
gradual effects of the waste prevention measures to be carried out in the next years in
accordance with the National Waste Prevention Programme;
a progressive change in waste composition (increase of shares of packaging waste, decrease of
organic kitchen and food wastes) as a consequence of changes in consumption habits of the
population.
With regards to the separate collection of recyclable materials and other waste streams and the
treatment of residual waste, the following future developments have been envisaged until 2020, all of
which contribute to reducing the amount of waste going to landfills:
increase in the rate of separate collection of recyclables (paper, plastics, metals and glass) from
households and commerce from average 33 % in 2013 to 56 % in 2020, thus ensuring the
fulfilment of the 50 % recycling target required by Article 11(2) of the Waste Framework
Directive (item 2.1.1);
improvement of source separation of green wastes from private/public gardens and parks sent
to home-composting and centralised composting facilities (up to 90 % of green waste from
private gardens, and 100 % of green waste from public gardens/parks, included in item 3.2);
start of operations of MBT plant with capacity for 50 ktpa residual wastes produced in the
northern part of the region in the second half of 2013 (item 5);
introduction of separate collection system for biowaste from supermarkets, restaurants, large
kitchens for treatment in a biogas facility with energy recovery starting 2020 (10 % of total
kitchen/food waste produced, included in item 3.2).
The forecast shows that all these envisaged developments alone would be insufficient to meet the
region’s 2013 and 2020 targets for the diversion of biodegradable waste from landfills (155 kt and 109
kt respectively, see items 6 and 7 in the table above). A further analysis also showed that:
it is neither technically nor economically feasible to reach these targets based solely on an
increase in separate waste collection (of biowastes and/or recyclables);
there are currently no opportunities to send the residual mixed municipal waste to other
existing waste treatment facilities within the country;
transporting the residual mixed waste for treatment outside of the country would not be
feasible because of high transport costs.
\182
Item Parameter Unit 2013 2015 2017 2020 2030
1 Population Inhabitants 1,300,000 1,294,800 1,289,600 1,281,900 1,256,500
kg/capita/day 450 464 473 480 457
2 Total municipal waste (MW) generation
tonnes/year 585,000 600,271 609,877 615,375 573,692
Municipal waste (MW) from households and kg/capita/day 383 394 402 410 390
2.1 similar waste from commerce (excl. bulky
wastes, special wastes, hazardous waste) tonnes/year 497,250 510,230 518,396 525,684 490,076
tonnes/year 297,356 304,097 303,780 297,537 271,502
Biodegradable waste (BDW) content in 2.1
% 60% 60% 59% 57% 55%
thereof separate collection of recyclables at
2.1.1 tonnes/year 70,361 98,219 113,010 140,883 138,202
source (paper, plastic, metal, glass)
average separation rate of recyclables (paper,
% of total 33% 43% 47% 56% 55%
pastic, metal, glass)
thereof total separate collection of organics at
2.1.2 tonnes/year 12,431 15,307 18,144 37,586 36,511
source (kitchen, food, garden waste)
average separation rate of organics (kitchen,
% of total 7% 8% 10% 21% 23%
food, garden waste)
Biodegradable waste (BDW) content in 2.1.1
tonnes/year 52,709 68,626 77,241 107,502 105,121
and 2.1.2
2.1.3 thereof residual mixed wastes collected tonnes/year 414,458 396,704 387,242 347,214 315,364
Biodegradable waste (BDW) content in 2.1.3 tonnes/year 244,647 235,471 226,539 190,035 166,381
Other municipal wastes (i.e. bulky waste, street,
2.2 tonnes/year 87,750 90,041 91,482 89,691 83,616
market and green garden/park waste)
thereof separation collection at source (mainly
2.2.1 tonnes/year 17,550 18,008 18,296 17,938 16,723
green waste to centralized composting)
Biodegradable waste (BDW) content in 2.2.1 tonnes/year 15,795 16,207 16,467 16,144 15,051
2.2.2 thereof residual mixed wastes tonnes/year 70,200 72,033 73,185 71,753 66,892
Biodegradable waste (BDW) content in 2.2.2 tonnes/year 17,550 18,008 18,296 17,938 16,723
Total recyclable material separated at source and
3.1 tonnes/year 67,911 96,227 111,307 138,821 134,925
sent to recycling
Total kitchen/food/green waste separated at
3.2 tonnes/year 32,431 35,307 38,144 57,586 56,511
source to (home)composting/biogas plants
Biodegradable waste (BDW) content in 3.1
tonnes/year 68,504 84,833 93,708 123,647 120,172
and 3.2 (diverted from landfills)
Total residual mixed waste after separation at
4 tonnes/year 484,658 468,737 460,427 418,967 382,257
source
Biodegradable waste (BDW) content in 4 tonnes/year 262,197 253,479 244,835 207,973 183,104
Residual mixed waste to mechanical-biological
5 tonnes/year 25,000 50,000 50,000 50,000 50,000
treatment (2013)
Biodegradable waste (BDW) content in 5
tonnes/year 13,525 27,039 26,588 24,820 23,950
(diverted from landfills)
Maximum BDW to landfill according to targets in
6 tonnes/year 155,000 155,000 155,000 108,500 108,500
RWMP (BDW landfilled in 1995: 310 kt)
Check of compliance with target for BDW
7 tonnes/year - 93,672 - 71,441 - 63,247 - 74,653 - 50,654
diversion without the project (6-BDW in 4 and 5)
Residual mixed waste to waste-to-energy
8 tonnes/year - - 200,000 200,000 200,000
(project)
Biodegradable waste (BDW) content in 8
tonnes/year - - 106,351 99,279 95,802
(diverted from landfills)
Check of compliance with target for BDW
9 tonnes/year - 93,672 - 71,441 43,104 24,626 45,148
diversion with the project (6-BDW in 4, 5 and 8)
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The implementation of the waste-to-energy (WtE) project with 200 ktpa capacity would allow the
region to clearly meet the regional targets for landfilling of biodegradable waste for the years 2013
and 2020 (see items 6 and 9 in the table above). The more stringent 2020 target would still be fulfilled
even if the foreseen planned introduction of a separate collection and treatment system for biowastes
in 2020 is delayed by some years.
It could also be shown through a separate demand analysis prepared for the three large towns in the
region which are the main users of the WtE plant, that even after fulfilment of recycling targets in
2020, there will be sufficient residual waste for the WtE plant to operate at the design capacity of 200
kt/a (see in the table below values for separate collection and residual wastes collected in the region
including the three largest towns in 2020). In other words, the project will complement and not
compete with the efforts to expand separate collection of recyclable materials in these towns. And
even if the separate collection rates of the three large towns should be notably higher than expected in
2020 and after that, the WtE plant would not need to operate below its full capacity, as it could still
resort to residual wastes produced in other towns in the region.
Total 3 Large Region
Item Parameter Unit
Region Towns Rest*
1 Total population Inhabitants 1,281,900 640,950 640,950
2 Municipal waste generation, total tonnes/year 615,375 369,225 246,150
per capita waste generation kg/capita/day 480 576 384
3 Separate collected materials, total tonnes/year 196,408 137,485 58,922
in % of item 2 (total waste generation) % 32% 37% 24%
Residual waste (after separate collection),
4 tonnes/year 418,967 231,739 187,228
total
* smaller towns and villages
A demand analysis for the main energy output of the WtE, heat, was also performed, which confirmed
the viability of supplying the heat to the district heating system of the largest town of the region.
IV Option analysis
First of all, an option without any intervention could be discarded for the reasons previously explained
in the demand analysis: without construction of additional treatment capacity for the residual waste
stream, the region would not be able to meet its self-defined targets for the diversion of biodegradable
waste from landfills.
Moreover, the option analysis included in the feasibility study assesses the following sets of options for
the project:
technological specifications of the WtE plant components;
location of the WtE plant;
general type of waste treatment technology.
General type of waste treatment technology
A simplified CBA was carried out to compare the economic performance of the WtE plant with that of
an MBT plant with the same throughput capacity mainly aimed at separating metals and a light
combustible waste fraction from the mixed residual waste (to be further processed and used as refuse-
derived fuel) and stabilising the remaining organic waste through aerobic treatment207. These two
207 The technical configuration of the MBT plant is assumed to include (i) an enclosed mechanical pre-treatment stage for the separation of
metals and light, highly combustible waste fractions, (ii) an enclosed biological stage for aerobic treatment of the largely organic waste
fraction in tunnels, (iii) final maturation stage with final mechanical treatment for the production of a compost like output from the
biologically stabilised waste (involving screening and sieving). The mass balance of the MBT is assumed as follows: a) 200 kt mixed residual
wastes on the input side, b) output side: 60 kt light highly combustible waste fraction (30 %), 5.5 kt metals (2.75 %), 6 kt rejects from
\184
options scored highest in a qualitative multi-criteria analysis (included technical, economic,
managerial and environmental criteria) carried out to pre-screen a larger number of options for
residual waste treatment. As can be seen in the table below, the comparison shows that although both
options are comparable in financial terms [they show similar net financial levelised unit costs (LUC) in
EUR/t of waste treated]208, the WtE option shows a clearly better performance in the economic
analysis (see table below) 209 210. This is because the WtE option:
gives a larger reduction of waste going to municipal waste landfills thus saving more landfill
space,
produces significantly more economic benefits from recovery, in particular energy from waste,
gives a larger overall reduction in GHG emissions even after taking into account the additional
release of fossil CO2 contained in the waste.
Parameter Unit MBT WTE
Financial Analysis
FNPV of total cost 1000 EUR - 176,422 - 307,998
FNPV of revenues from sale of recovered materials/energy 1000 EUR 12,015 142,896
Levelized unit cost (LUC), Total Gross EUR/t - 60 - 111
thereof for initial investment EUR/t - 17 - 55
thereof for reinvestment (asset replacements/decommissioning) EUR/t - 4 - 13
thereof for operation/maintenance EUR/t - 28 - 37
thereof for disposal of outputs EUR/t - 11 - 6
Revenue from sale of recovered materials/energy EUR/t 4 51
Levelized unit cost (LUC), Total Net EUR/t 56 59
Economic Analysis
ENPV of total cost 1000 EUR - 147,041 - 270,338
ENPV of total benefits 1000 EUR 171,530 371,633
thereof landfill space saved 1000 EUR 67,516 72,133
thereof materials recovered 1000 EUR 10,579 3,847
thereof energy recovered (heat/electricity) 1000 EUR - 188,308
thereof avoided GHG emissions (net) 1000 EUR 93,435 107,346
Total ENPV 1000 EUR 24,489 101,295
mechanical pre-treatment (3 %), 70 kt stabilised compost-like output (35 %), 40 kt mass loss (20 %), 18.5 kt rejects from the final
mechanical treatment (9.25 %). Assumptions on the final destination of MBT outputs (see assumptions on disposal costs/off-take prices
below): the compost-like output (CLO) is used as cover material in landfills or as a filling material in construction, remediation of
contaminated sites, closed mines; the light waste fraction is taken off as residue derived fuel (RDF) by cement kilns or companies specialised
in RDF conditioning and trading; the recovered metals, are sold on the market; the rejects from mechanical treatment stages are sent to
ordinary municipal landfills.
208 Calculated by dividing the net present value of the facility’s net cost flows over the reference period (including the investment and OM&A
cost, net of revenues from sale of by-products such as heat, electricity and scrap metals) by the discounted quantity of waste treated in that
same period, using a financial discount rate of 4 %.
209 Based on a social discount rate of 5 %, same as the one applied in the economic analysis of the WtE option, for more details see section VI
below.
210 The reference period assumed for the analysis is 30 years, of which in the MBT option 3 years are for tendering and construction and 27
years for operation (4 and 26 years respectively, in the case of the WtE option, see explanation in section VI). The unit investment cost for the
MBT is estimated at 249 EUR/t + 5 % contingencies (net of land purchase and VAT), the unit operating and maintenance cost at 28 EUR/t
plus costs for transport and disposal of outputs going to landfill of 9 EUR/t in 2017 increasing to 12 EUR/t in 2030. The costs of disposal for
landfilled outputs (excl. transport) are calculated based on a landfill gate fee of 15 EUR/t plus landfill tax starting at 12 EUR/t in 2015, and
increasing to 18 EUR/t in 2020, 27 EUR/t in 2025 and 36 EUR/t in 2030. The disposal cost of the CLO and the RDF includes only the
transport cost as the off-take is conservatively assumed to be at no cost to the plant operator. The metals recovered are assumed to be sold at
an average price of 150 EUR/t (weighted average market price paid for ferrous and non-ferrous metals). A reinvestment cost of around 20 M
EUR after half of the operation period was assumed to replace plant and equipment components at the end of their economic life as well as
EUR 1 million for the dismantling of the plant after its final decommission. The residual value of the plant at the end of the reference period is
zero. In the economic analysis, 30 EUR/t is assumed to be the total economic cost of landfill space in the country (for non-hazardous
municipal waste, excluding cost of GHG emissions, which are monetised separately). This value is used to calculate the economic cost of
landfilling the MBT residues (excluding the CLO), instead of the landfill gate fee and landfill tax used in the financial analysis. The same value
also applies for the monetisation the economic benefits of every tonne of waste diverted from landfill through the project (the same
assumption is made in the economic analysis of the WtE option. For details on the assumptions made for the WtE option, see sections V and
VI below.
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Besides the CBA, the WtE option also scores better than the MBT option from the point of view of the
quality and marketability of the main outputs and the security of disposal of the wastes produced in
the respective treatment processes. In the case of the WtE option, the project promoter is able to
secure a long-term off-take and a reliable flow of revenue from the sale of the heat and electricity
produced in the plant as well as to secure a sound and reasonably priced disposal for the hazardous
and non-hazardous wastes through certified disposal facilities located in relatively close distance to
the plant. In the case of the MBT plant, under the market conditions existing in the project region, the
promoter would only be able to secure short-term off-take agreements for the two main outputs: the
light, combustible waste fraction and the compost-like output. In the case of the former product,
potential off-takers include a nearby cement kiln and several companies specialised in RDF
conditioning and trading, which would be ready to take off the product at no cost for the producer but
make this dependent on several quality parameters to be ensured by the producer. The compost-like
output is a low-quality material most likely to fail the strict quality requirements for its use as compost
and hence would only be good as a cover and filling material in landfills or in construction and/or
remediation projects. The operators of nearby landfills and construction companies would be willing
to take off the product at zero cost but are not willing to agree to long-term off-take agreements.
Hence, in the MBT option, there is a considerable risk that the project promoter would finally need to
pay a price for the disposal of the two main MBT outputs.
Location of the WtE plant
Three different alternative locations were considered for the project. The analysis was carried out in
qualitative terms considering multiple criteria such as (i) geographical location in relation to the three
towns producing the waste to be treated in the plant, (ii) existence of district heating network or other
potential off-taker for heat produced, (iii) accessibility to other relevant utility networks (electricity,
gas, water, etc.), (iv) accessibility to road network, (v) cost and size of available land, (vi) distance to
closest residential areas, (vii) environmental considerations. The proposed location ensures the
following advantages: convenient geographical location in relation to the three main towns of the
region, allowing to transport the waste to the facility without the need to build new waste transfer
stations, all-year-long heat off-take by the local district heating system, good access to relevant utilities
(heat, electricity, gas, water networks) and road system, sufficient distance to closest residential and
Natura 2000 area, availability of sufficient space for the project and additional land for possible
capacity extensions in case this is considered in the future.
Technological specifications of the WtE plant components
The options analysis also delivered a justification for following solutions proposed for the
technological components of the plant, all of which constitute BAT in line with the Directive
2010/75/EU (Industrial Emission Directive):
1 x 200 ktpa incineration line based on grate furnace technology,
1 x steam boiler (400°C, 40 bar) with backpressure steam turbine with 40 MWth and 13 MWel
nominal output capacity 211,
1 x multistage wet flue-gas cleaning facility designed to meet EU requirements (including
electrostatic precipitators for boiler and fly ash removal, selective non-catalytic reduction
(SNCR) of NOx, catalytic filter for destruction of PCDD/F-type organic substances212).
In addition, the plant will include:
access road and connections to relevant utilities;
211
The ratio of heat to electricity in the total energy output is 3:1, i.e. 75 % heat (40 MWth) and 25 % electricity (13 MWel). Hence, based on
estimated 62.5 MW thermal input, the gross CHP efficiency assumed is 85 %, calculated as follows: (40 MWth + 13 MWel) / (200 000 t * 2.5
MWh/t / 8 000/h), with 2.5 MWh/t or 9 kJ/kg being the estimated average net calorific value of the mixed waste and 8 000 h the plant’s
operating hours per year.
212
Polychlorinated dibenzodioxins/-furans
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reception and storage facilities for incoming waste;
slag and bottom ash treatment facilities including maturation area and ferrous metal
separation;
separate boiler and fly ash storage and solidification facilities;
rubber-lined steel stack (120 m) for release of treated flue gases into the atmosphere;
wastewater treatment plant to process wastewaters from flue gas cleaning facility designed to
meet legal requirements for discharge into the pubic sewerage system;
automatised process control and monitoring systems.
Slag and bottom ashes are envisaged to be sent to an inert waste landfill while the conditioned boiler
and fly ashes will be sent to a hazardous waste landfill, both of which are located in adequate
proximity to the plant (up to 30 km distance).
A one-line configuration was selected for the WtE plant because of its lower investment and operating
cost. The choice is justified based on the following specific circumstances;
the municipal heating plant has a gas-fired boiler in reserve it can easily and rapidly resort to
in the case of planned interruptions of the WtE plant (or even in the unlikely event of an
unexpected shut-down)213;
in the case of short interruptions for planned inspections, the site allows for temporary storage
of waste, adequately bailed in special plastic foil, which can later be progressively added to the
normal plant throughput. In the unlikely case of an (unexpected) longer shut-down of the
plant, waste could still be diverted to landfills (however at an additional cost to the WtE plant),
as there is currently no absolute ban on landfilling of municipal waste.
V Project costs and revenues of selected option
A breakdown of the investment cost for the selected project configuration, in constant prices of 2013,
is presented in the following table. No price adjustments for inflation were assumed during the
implementation period of the project.
Ineligible
Total cost 214 Eligible cost
Project Investment Cost cost
(m EUR) (m EUR)
(m EUR)
Planning/design fees 5.20 5.20 -
Land purchase 2.00 2.00 -
Building and construction 46.20 - 46.20
Plant and machinery or equipment 92.40 - 92.40
Contingencies 6.93 - 6.93
Publicity 0.10 - 0.10
Supervision during construction implementation 5.55 - 5.55
Technical assistance 1.80 - 1.80
Sub-TOTAL 160.18 7.20 152.98
(VAT) 32.04 32.04 -
TOTAL 192.22 39.24 152.98
The overall unit investment cost of around 756 EUR/tonne per annum of waste treatment capacity215
(net of costs for land purchase, contingencies and VAT) was found to be acceptable for the specific
configuration of the plant. Also, unit investment costs budgeted for the individual construction and
213
Short interruptions for annual inspections of the WtE plant are envisaged in the heat off-take contract
214
Ineligible investment cost includes cost incurred before the beginning of the programming period (for planning/design and land
purchase) and VAT.
215
Equivalent to EUR 2.750 /MW thermal input capacity
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technological components (i.e. for incineration, energy recovery and flue gas cleaning) were
considered to be comparable with prices found on the market.
Total operation and maintenance (O&M) costs (excluding the cost for the transport and disposal of
wastes as well as for electricity consumption, which is from own generation216) are estimated at
around 37 EUR/t of waste treated (4.9 % of investment cost net of land purchase, contingencies and
VAT), including cost for staff (6 EUR/t), maintenance (23 EUR/t), insurance (3 EUR/t), and process
consumables (5 EUR/t)217. Transport and disposal costs for waste outputs from incineration and flue
gas cleaning increase the total O&M cost to 43 EUR/t218.
The plant components with a short lifetime (75 % of the total plant and equipment cost, equivalent to
EUR 70 million) will be replaced once during the reference period, at the end of their economic life (15
years)219. It is assumed that the replacement works will be completed in a year, during which the
operation of the plant will be temporarily halted220. A cost for the final decommissioning and
dismantling of the plant at the end of the reference period (around EUR 6 million221) is also considered
in the analysis.
The project revenues include the sale of materials and energy recovered from waste as well as the gate
fees charged to users for municipal waste delivered at the plant. These were calculated based on the
following unit price assumptions:
Annual
Revenue item Unit price Remark
input/output
Gate fees for 200 000 t 30 - 59 EUR/t Gate fee set at 30 EUR/t at start of operations in
waste 2017, and progressively increased to 59 EUR/t in
2037.
222
Electricity sold to 87 250 MWh 50 EUR/MWh Estimated long-term average wholesale market price
grid for the country.
223
Fixed premium 106 250 MWh 15 EUR/MWh Premium granted to waste-to-energy facilities
for electricity producing electricity in high-efficiency co-generation,
from high- which are eligible for support under an existing
efficiency co- national scheme. Given that the scheme is due to
generation expire at the latest in 2031, revenues from the
premium are computed only in the first 15 years of
224
operations .
216
The electricity cost can be estimated at the foregone revenue for the plant from the sale of electricity (50 EUR/MWh), which is equivalent
to around 6 EUR/t and would increase the total O&M cost for the plant from 37 EUR/t to 42 EUR/t (5.6 % of net asset value)
217
Assumptions for the calculation of the O&M cost: (i) staff costs: 18 000 EUR per year and employee increasing by 1 % per year in real
terms; (ii) maintenance cost: 3.1 % of net asset value per year: (iii) insurance cost: 0.5 % of net asset value per year.
218
Assumptions for the calculation of the disposal cost: 10 EUR/t for non-hazardous incineration ashes,100 EUR/t for hazardous waste, plus
transport cost at 4.8 EUR/t; mass balance for the WtE plant: slag and bottom ash (24 %), metals (2 %), hazardous waste (2.5 %), mass losses
(71.5 %).
219
This assumption is in accordance with technical data from literature. The large asset replacements primarily concern the furnace/boiler
package and the flue gas treatment plant, as well as other ancillary equipment exposed to high wear and tear. Smaller replacements of
equipment with very short life (< 5 years) are included in the regular maintenance cost (for example, the super-heaters of the boiler system,
roller grates in the combustion chamber, etc.).
220
During this period the plant produces no revenues and has no expenditure other than the fixed operating cost and the reinvestment cost
for asset replacements.
221
This cost estimate is based on the assumption that the site will continue to be used for the same or a similar purpose in the future.
222 This value corresponds to the actual amount of electricity sold to grid, i.e. gross generation minus own consumption
223 Unlike in the case of revenues from the sale of electricity on the market, which are calculated based on the actual amount of electricity sold
to the grid (see above footnote), the premium for high-efficiency co-generation applies to the gross electricity generation, i.e. including the
own electricity consumption.
224 Most EU countries have schemes in place that provide financial support to electricity produced through high-efficiency co-generation or
from renewable energy sources (RES). The financial support may have different forms, such as investment aid, special feed-in-tariffs, fixed
and variable premiums paid on top of electricity market prices, or green certificates. Where WtE facilities are eligible for support under such
schemes, any additional revenues achieved should be included in the financial analysis. In this case, a fixed premium for electricity produced
in high-efficiency co-generation has been assumed. Where the support scheme has a clearly defined validity period, a conservative approach
is to limit the cash-flows until the end of the established support period only. In the economic analysis, a possible double counting should be
discarded before including these premiums as economic benefits.
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Heat sold to 1 147 500 GJ 4.1 EUR/GJ The heat price corresponds to the total variable cost
district heating of heat production saved by the district heating
225
system operator in the existing central heat plant .
Metals sold to 4 000 tonnes 80 EUR/t Long-term average market price for scrap ferrous
226
market metal .
The gate fee charged at the WtE plant is initially set at 30 EUR/t and stepwise increased every two
years to reach 43 EUR/t in 2025 and 52 EUR/t in 2030, which is roughly the same as the landfill gate
fee including the new landfill tax227. Further gradual increases of the WtE gate fee finally leads to 59
EUR/t in 2037 (year 21 of operations), which is the total levelised unit cost (LUC) of the plant, an
estimate of the full-cost recovery level (see table shown in the section on the options analysis above).
Higher gate fees are not applicable for affordability reasons228.
The gate fee at the start of operations clearly exceeds the LUC component for O&M and asset
replacements and is equivalent to around 50 % of the total LUC. The levelised gate fee over the total
period analysed is around 45 EUR/t, which is equivalent to 75 % of the total LUC.
VI Financial and Economic Analysis
The analysis is performed using a 30-year reference period, in line with the recommendation made in
this guide for projects in the waste sector, which includes four years for implementation and 26 years
for operations. The operational period is prolonged beyond the economic life generally estimated for
the plant’s assets (15 years) by assuming substantial asset replacements in year 16 of operations. At
the end of the reference period, the plant is considered to have used up most of its service potential
rendering its market value insignificant. This is why the residual value is conservatively set at zero and
only the cost of decommissioning and dismantling of the plant is computed in the last year of the
reference period (see section V above).
The financial and economic analyses are both carried out in constant prices. The real discount rates
used are 4 % in the financial analysis and 5 % in the economic analysis, in line with the standard
benchmarks recommended in this guide. The incremental method is applied in both the financial and
economic analysis. In the specific case of the financial analysis however, the without-project scenario
is one of no operations, so the incremental cash-flows are those of the with-project scenario. This
assumption is justified based on the fact that the project beneficiary is a new entity created with the
specific responsibility of executing and later operating the project.
225 The displaced heat source assumed in this specific case is a coal-fired heat boiler. The variable cost of 4.1 EUR/GJ includes the cost of fuel
and fuel transport (imported coal), as well as other variable O&M costs of production. As a reference, the full cost of heat for a coal-fired
boiler including capital cost is in the order of 6.8 EUR/GJ and for a gas-fired boiler around 9.0 EUR/GJ. The reduced heat price (i.e. below the
full cost of heat from the displaced or the next best alternative source) is justified in this case as the WtE plant is assumed to take the place of
an existing boiler in the heat production system’s priority order and not to displace investments for its replacement or postpone investments
for the expansion of existing heat production capacity (the heat demand is assumed to remain without notable increase in the future).
District heating systems are common off-takers for the heat produced in WtE plants and situations like the one described above may exist in
reality but are not to be seen as a standard scenario. The heat price has an important impact on the financial viability of WtE projects and
should therefore be carefully assessed and verified for each particular case. Also, where a reduced heat price is assumed, it should be verified
that this is also reflected in the final heat price paid by the final users and does not lead to a subsidisation of the district heating system
operator.
226 Own estimate based on expert opinion, assuming conservative development of demand for scrap metal on the world market
227 For details, see footnote inserted in the section on the options analysis
228 To substantiate the setting of the WtE plant’s gate fee below its full-cost recovery level (i.e. the plant’s LUC), a household affordability
analysis was carried out which compared the maximum affordable level of household expenditure for waste management services, as defined
by the competent national authorities, and the total cost of the municipal waste management system, as designed to reach full compliance
with all legal requirements until 2020. The level of the fees paid for the waste management services, including the gate fee for the WtE plant,
are calculated so that these do not exceed the maximum affordable levels. The progressive increase of the waste fees follow the projected
improvement of real household incomes throughout the reference period of the project.
\189
Financial analysis
The project complied with the requirements of the Commission Decision of 20 December 2011 (on
State Aid and Services of General Economic Interest - SGEI)229 and therefore does not require
notification to the European Commission’s Directorate-General for Competition. In this case, the
‘funding gap method’ was used to demonstrate the financing needs and proportionality of the state aid
granted to the project230.
The ‘funding gap rate’ is 24.0 % (DIC = EUR 145.0 million, DNR = EUR 110.2 million, see calculations in
the table below), mainly due to the fact that the plant’s gate fee is capped for affordability reasons and
does not recover the full cost of the plant for most of the reference period.
1 2 3 4 5 6 7 8 9 10 15 20 25 30
EU GRANT
Construction Operation
4.0%
Calculation of Discounted Investment Cost (DIC) NPV 4 %
Investment cost (net of contingencies) M EUR 145.0 7.2 89.0 42.6 14.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
DISCOUNTED INVESTMENT COST (DIC) M EUR 145.0 7.2 89.0 42.6 14.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Calculation of Discounted Net Revenues (DNR) NPV 4 %
Waste input ktpa 0.0 0.0 0.0 0.0 200.0 200.0 200.0 200.0 200.0 200.0 200.0 0.0 200.0 200.0
Gate-fee EUR/t 0.0 0.0 0.0 0.0 30.0 30.0 33.0 33.0 36.1 36.1 47.4 54.0 59.4 59.4
Revenue from gate-fee M EUR 123.7 0.0 0.0 0.0 0.0 6.0 6.0 6.6 6.6 7.2 7.2 9.5 0.0 11.9 11.9
Revenue from sale of metals and energy M EUR 142.9 0.0 0.0 0.0 0.0 10.8 10.8 10.8 10.8 10.9 10.9 10.9 0.0 9.3 9.3
Revenue from sale of heat M EUR 64.9 0.0 0.0 0.0 0.0 4.7 4.7 4.7 4.7 4.7 4.7 4.7 0.0 4.7 4.7
Revenue from sale of electricity M EUR 73.6 0.0 0.0 0.0 0.0 5.8 5.8 5.8 5.8 5.8 5.8 5.8 0.0 4.2 4.2
Revenue from sale of metals M EUR 4.4 0.0 0.0 0.0 0.0 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.0 0.3 0.3
Total O&M cost including reinvestments M EUR -156.4 0.0 0.0 0.0 0.0 -8.6 -8.6 -8.6 -8.7 -8.7 -8.7 -8.7 -72.1 -8.9 -15.6
Fixed O&M cost M EUR -91.8 0.0 0.0 0.0 0.0 -6.5 -6.5 -6.5 -6.5 -6.5 -6.5 -6.6 -2.1 -6.7 -6.8
Variable O&M cost M EUR -29.3 0.0 0.0 0.0 0.0 -2.1 -2.1 -2.1 -2.1 -2.1 -2.1 -2.1 0.0 -2.1 -2.1
Reinvestment cost M EUR -35.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -70.0 0.0 -6.7
Residual value of investment M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
DISCOUNTED NET REVENUES (DNR) M EUR 110.2 0.0 0.0 0.0 0.0 8.2 8.2 8.8 8.7 9.4 9.4 11.6 -72.1 12.3 5.6
ELIGIBLE COST M EUR 153.0
FUNDING GAP RATE (FGR = (DIC - DNR) / DIC): 24.0%
CO-FINANCING RATE OF PRIORITY AXIS (CF): 80.0%
EU GRANT ( = EC x FGR x CF): M EUR 29.4
The EU’s project co-financing contribution (a non-reimbursable grant) results in EUR 29.4 million
from multiplying the eligible cost shown in section V above (EUR 153 million) by the ‘funding gap rate’
(24.0%) and by the co-financing rate of the relevant priority axis in the OP (80 %). The remainder of
the project investment is financed by national public funds (a non-reimbursable grant of EUR 7.3
million) and by funds provided by the project beneficiary, a mix of debt (EUR 80.0 million) and equity
(EUR 43.4 million), as shown in the following table.
Financing Sources m EUR % share
Eligible investment cost 153.0 95.5 %
EU contribution (grant) 29.4 18.3 %
National public contribution (grant) 7.3 4.6 %
Loan 80.0 49.9 %
Beneficiary contribution (equity) 36.2 22.6 %
Ineligible investment cost (excl. VAT) 7.2 4.5 %
Beneficiary contribution (equity) 7.2 4.5 %
231
Total investment cost (excl. VAT) 160.2 100.0 %
With regards to the project loan, the specific conditions agreed between the project beneficiary and
the IFI that provides the loan include a maturity of 18 years (including three years grace period during
construction and 15 years for principal repayment which start in the first year of operation) and an
229
Commission Decision of 20 December 2011 on the application of Article 106(2) of the Treaty on the Functioning of the European Union to
state aid in the form of public service compensation granted to certain undertakings entrusted with the operation of services of general
economic interest.
230
This was considered as an ‘individual verification of financing needs in accordance with the applicable State aid rules’ in the meaning of
Article 61(8)(c) of Regulation (EU) No. 1303/2013. Hence, Article 61 (1-6) does not apply in this case.
231
The VAT is not included in the financing plan as it is fully recoverable for the beneficiary. The beneficiary will pre-finance the total amount
of this indirect tax.
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average interest rate of 4 % in real terms. The interest during construction, totalling EUR 4.8 million,
will be provided by the beneficiary in addition to a working capital injection of EUR 3.0 million to
finance the start-up of operations232.
The foreseen re-investment for the replacement of assets in year 16 of operations (EUR 70 million) is
financed by the beneficiary in equal parts with equity and debt. The loan has an amortisation period of
10 years and an average interest rate of 4 % in real terms.
The calculations of the financial profitability indicators (before-tax, real) are shown in the table below
and are as follows:
Return on investment (before EU grant): FRR(C) = 1.8 %
FNPV(C) = EUR -34.8 million
Return on national capital (after EU grant): FRR(K) = 2.2 %
FNPV(K) = EUR -14.2 million
1 2 3 4 5 6 7 8 9 10 15 20 25 30
FRR(C)
Construction Operation
Return on Investment NPV 4 %
Investment cost (net of contingencies) M EUR -145.0 -7.2 -89.0 -42.6 -14.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Revenues M EUR 266.6 0.0 0.0 0.0 0.0 16.8 16.8 17.4 17.4 18.1 18.1 20.4 0.0 21.2 21.2
O&M costs including reinvestments M EUR -156.4 0.0 0.0 0.0 0.0 -8.6 -8.6 -8.6 -8.7 -8.7 -8.7 -8.7 -72.1 -8.9 -15.6
Residual value of investments M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Project cash-flow M EUR -34.8 -7.2 -89.0 -42.6 -14.5 8.2 8.2 8.8 8.7 9.4 9.4 11.6 -72.1 12.3 5.6
FRR(C) (before EU grant) 1.8%
1 2 3 4 5 6 7 8 9 10 15 20 25 30
FRR(K)
Construction Operation
National Financing Sources
National public contribution (grant) M EUR 0.0 4.5 2.1 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Project beneficiary contribution (equity) M EUR 7.2 22.1 10.6 3.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 35.0 0.0 0.0
Loan Balance (loan for the financing of initial investments)
Beginning balance M EUR 0.0 0.0 48.8 72.1 80.0 76.0 71.8 67.5 63.0 58.4 32.0 0.0 0.0 0.0
Loan disbursements M EUR 0.0 48.8 23.3 7.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Interest payments M EUR 0.0 0.0 2.0 2.9 3.2 3.0 2.9 2.7 2.5 2.3 1.3 0.0 0.0 0.0
Principal repayments M EUR 0.0 0.0 0.0 0.0 4.0 4.2 4.3 4.5 4.7 4.9 5.9 0.0 0.0 0.0
Ending balance M EUR 0.0 48.8 72.1 80.0 76.0 71.8 67.5 63.0 58.4 53.5 26.1 0.0 0.0 0.0
Loan Balance (loan for the financing of asset replacements)
Beginning balance M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 22.6 4.1
Loan disbursements M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 35.0 0.0 0.0
Interest payments M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9 0.2
Principal repayments M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.4 4.1
Ending balance M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 35.0 19.2 0.0
Other financial contributions
Working capital injection (Project beneficiary) M EUR 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Return on National Capital NPV 4 %
National public contribution (grant) M EUR -6.9 0.0 -4.5 -2.1 -0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Project beneficiary contribution (equity) M EUR -58.0 -7.2 -22.1 -10.6 -3.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -35.0 0.0 0.0
Working capital injection (Project beneficiary) M EUR -2.7 0.0 0.0 0.0 -3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Interest payments M EUR -27.6 0.0 0.0 -2.0 -2.9 -3.2 -3.0 -2.9 -2.7 -2.5 -2.3 -1.3 0.0 -0.9 -0.2
Principal repayments M EUR -64.5 0.0 0.0 0.0 0.0 -4.0 -4.2 -4.3 -4.5 -4.7 -4.9 -5.9 0.0 -3.4 -4.1
O&M cost M EUR -121.1 0.0 0.0 0.0 0.0 -8.6 -8.6 -8.6 -8.7 -8.7 -8.7 -8.7 -2.1 -8.9 -8.9
Revenues M EUR 266.6 0.0 0.0 0.0 0.0 16.8 16.8 17.4 17.4 18.1 18.1 20.4 0.0 21.2 21.2
Residual value of investments M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
National cash-flow M EUR -14.2 -7.2 -26.6 -14.7 -10.2 1.0 1.0 1.6 1.5 2.2 2.2 4.4 -37.1 8.0 7.9
FRR(K) (after EU grant) 2.2%
Under consideration of all cash-flows described above, both during project implementation and
operation, the project is expected to be financially sustainable, as the cumulated net cash-flow is never
negative during the reference period (see the following table).
This is capital paid in by the owners of the beneficiaries (i.e. the regional government and the local governments of the three participating
232
municipalities), in accordance with their shares in the new company.
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1 2 3 4 5 6 7 8 9 10 15 20 25 30
FINANCIAL SUSTAINABILITY
Construction Operation
Financial sustainability
EU contribution to project (grant) M EUR 0.0 17.9 8.6 2.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
National public contribution to project (grant) M EUR 0.0 4.5 2.1 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Project beneficiary contribution to project (equity) M EUR 7.2 22.1 10.6 3.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 35.0 0.0 0.0
Loan disbursements M EUR 0.0 48.8 23.3 7.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 35.0 0.0 0.0
Other beneficiary contributions during project implementation M EUR 0.0 0.0 2.0 5.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Revenues M EUR 0.0 0.0 0.0 0.0 16.8 16.8 17.4 17.4 18.1 18.1 20.4 0.0 21.2 21.2
Total cash inflows M EUR 7.2 93.3 46.6 21.0 16.8 16.8 17.4 17.4 18.1 18.1 20.4 70.0 21.2 21.2
Investment cost M EUR -7.2 -93.3 -44.6 -15.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M cost including reinvestments M EUR 0.0 0.0 0.0 0.0 -8.6 -8.6 -8.6 -8.7 -8.7 -8.7 -8.7 -72.1 -8.9 -15.6
Interest payments M EUR 0.0 0.0 -2.0 -2.9 -3.2 -3.0 -2.9 -2.7 -2.5 -2.3 -1.3 0.0 -0.9 -0.2
Principal repayments M EUR 0.0 0.0 0.0 0.0 -4.0 -4.2 -4.3 -4.5 -4.7 -4.9 -5.9 0.0 -3.4 -4.1
Corporate Income Tax M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.2 0.7 0.0 0.6 0.0
Total cash outflows M EUR -7.2 -93.3 -46.6 -18.0 -15.8 -15.8 -15.8 -15.8 -15.7 -15.7 -15.2 -72.1 -12.6 -19.9
Net cash-flow M EUR 0.0 0.0 0.0 3.0 1.0 1.0 1.6 1.6 2.4 2.4 5.2 -2.1 8.6 1.2
Cumulated net cash-flow M EUR 0.0 0.0 0.0 3.0 4.0 5.0 6.5 8.1 10.6 13.0 33.0 55.4 96.2 131.8
In addition, the debt service coverage ratio (ration of EBITDA (earnings before interest, tax,
depreciation and amortisation) and the debt service for contracted loans) is always above 1.1 during
the entire repayment period of the loans.
Economic analysis
The economic analysis investigates the impact on society of improving waste management practices
through the implementation of a waste incineration facility with energy and material recovery. The
counterfactual scenario used as a baseline is one with continued landfilling of untreated mixed
residual wastes collected in the project’s service area (business as usual).
The financial costs of the project are used as a basis to estimate its economic costs. The following
correction factors were applied:
Cost item Correction applied Remark
Technological equipment, CF = 1 Purchased through open, competitive, international
construction materials and tenders, adequately priced on the market. No
related services correction required.
Skilled labour as required for CF = 1 A competitive market is assumed for skilled labour
engineering services and which can be thus assumed to be adequately priced on
operations the market. No correction required.
Unskilled labour as required SWCF = 0.6 High regional unemployment, hence, correction
for construction works and required.
operations
Land cost CF = 1 Sales price is within the range of prices commonly
found for similar land on the local market.
Consumables in operations CF = 1 Mostly adequately priced on the market. Natural gas
used only in small quantities during start up. No
corrections applied.
Electricity cost N.A. Not included in O&M cost as the electricity consumed
by the plant is from own production and no additional
electricity is required from the grid.
Disposal costs CF = 1 The gate fees of the waste disposal facilities are
considered to adequately internalise all financial cost
and the externalities related to the disposal of the non-
hazardous and hazardous waste produced in the plant.
No correction required for the waste disposal costs.
Other operating costs (i.e. CF = 1 Spare parts and external services used for asset
asset maintenance and maintenance/repair are adequately priced on the
insurance cost) market. Insurance to be procured through open tender,
local prices comparable with prices in rest of Europe.
No corrections applied.
The following socio-economic benefits of the project were monetised in the economic analysis:
\192
resource cost savings through improved waste management, which can be subdivided in
the following sub-categories:
o saved cost of landfill space (i.e. leading to an extension of landfill lifetime) through
diversion of municipal waste to the new waste management facility, i.e. WtE plant;
o avoided cost for the alternative production of energy and metal recovered from waste
(i.e. heat, electricity, scrap metals);
avoided externalities from GHG emissions through the improved waste management,
divided into four subcategories:
o avoided GHG emissions from improved waste management (considering both the
avoided GHG emissions from landfills and additional fossil CO2 releases from the
incineration of materials contained in waste);
o avoided GHG emissions from existing heat production based on fossil fuel (through
heat generation from waste);
o avoided GHG emissions from next best alternative electricity production based on fossil
fuel (through electricity generation from waste);
o avoided GHG emissions from metal production based on raw materials (through
recovery of metals from waste).
Other positive externalities of the improved waste management achieved through the project are not
computed in this case because they were found to be insignificant in monetary terms as compared to
those from avoided GHG emissions, e.g. the avoided emissions of pollutants to air, such as NO x, SO2 and
fine particulate matter through the displacement of coal as fuel in energy generation, or the avoided
soil and groundwater contamination through municipal waste landfills. These two categories of
externalities can be considered to be largely internalised in the resource cost savings mentioned under
points 1 a) and b) mentioned above.
Negative externalities of the project computed in the economic analysis are the fossil CO 2 emissions
generated through the incineration of waste, which are subtracted from the benefits mentioned under
points 2 a) – d) above. Other negative externalities were considered to be insignificant and thus not
computed:
fossil CO2 emissions from project implementation (e.g. from fuel and electricity consumption
during construction);
other emissions from the WtE plant to air, water and soil: minimised through the inclusion of
BAT for the treatment of flue gases, incineration ashes and wastewater produced in the plant
as well as the safe disposal of ashes (all of which are internalised in the cost of the project);
visual or other disamenities (i.e. visual impact, noise, odours) caused by the WtE plant:
considered minimal in this case as the project will be implemented in an existing brownfield
site located in the outskirts of the town around 2 km away from the closest residential area233.
The monetisation of the project’s socio-economic benefits is elucidated in the following table (for 2017
and 2042, i.e. the first and last year of operations).
233 Negative externalities from visual and other disamenities (noise, odour) are common for large waste management projects such as
landfills or waste treatment plants but may be difficult or even impossible to quantify when such projects are implemented in or in close
vicinity to existing brownfield sites or large industrial areas. This is due to the difficulty to isolate the disamenities caused by the project from
those already caused by the existing site/infrastructure. However, when large waste management projects are implemented on greenfield
sites that are in close vicinity to residential areas such negative externalities should not be neglected in the economic analysis. The typical
method applied to monetise such externalities is the hedonic price method. In applying the hedonic price method, there are three important
variables to be estimated: (i) the project impact area and the affected property (in m2), (ii) the average property value or annual rent (in
EUR/m2) and (iii) the depreciation rate expected due to the project (in %). While the estimation of the first and second variables are strongly
dependent on site-specific factors, the third variable can be estimated based on experience from other comparable projects. Reference is
made to Chapter 4.2.7.4 and Annex VI, which provide more details and an example for its application.
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Value
Monetisation of project benefits
(2017 / 2042)
B1. Resource cost savings through improved waste management m EUR 22.0
B1a) Economic value of landfill space saved (excl. externalities from GHG emissions)
The monetisation of the economic benefit is based on the full (financial) cost of construction, operation,
closure and aftercare of an average landfill in the country in addition to the opportunity cost of the land
used and positive externalities from avoided emissions to soil and water. m EUR 6.0
Calculation of saved cost of landfill space is as follows:
Amount of waste diverted from landfill (200 000 ktpa) x estimated cost of landfill space in the country
234
including opportunity cost of land (30 EUR/t ) = EUR 6.0 million
B1b) Economic value of recovered energy in form of heat (excl. externalities from GHG
emissions)
The monetisation of the economic benefit is based on the avoided cost of the existing heat source
displaced in the system, which in this case is an existing coal-fired heat only boiler. In addition to the
long-term marginal cost of heat production, which includes the full capital and operating costs, an
235
economic penalty cost for (limited) security of supply of coal is included in the calculation .
The use of the long-term marginal cost of the displaced heat source as a basis for valuing the
economic benefit to society, instead of the short-term marginal cost used in the financial analysis, is m EUR 9.3
justified because the latter does not represent a competitive market outcome (the local heat market
has only one potential off-taker which dictates the price) and thus does not truly reflect the opportunity
cost of heat.
Calculation of avoided economic cost of heat production (excl. externalities):
Annual heat production at the WtE plant (1 147 500 GJ) x long-term marginal cost for existing heat
production based on coal plus a penalty cost for security of supply of coal (6.7 EUR/GJ + 1.4
236
EUR/GJ ) = EUR 9.3 million
B1c) Economic value of recovered energy in form of electricity (excl. externalities from GHG
emissions)
The monetisation of the economic benefit is based on the avoided cost of the next best alternative
plant for producing the electricity. In the long term in Europe, this would be a CCGT (combined cycle
237
gas turbine) .
The fixed premium for high-efficiency co-generation considered in the financial analysis on top of the
EUR 6.4 m
market price for electricity is left unconsidered in the economic analysis as this would otherwise
constitute double counting.
Calculation of avoided financial cost of electricity generation from alternative sources is as follows:
Annual electricity export at the WtE plant (84 250 MWh) x long-term marginal cost of electricity
generation in CCGT plus a penalty cost for security of supply of gas (65 EUR/MWh + 10 EUR/MWh) =
EUR 6.4 million
B1d) Economic value of recovered ferrous metal (excl. externalities from GHG emissions)
The monetisation of the economic benefit is based on the avoided cost of the alternative production of
the metal from raw materials.
Given that the trade market for scrap metals is well developed in the country, the financial price paid on
the local market is considered a good proxy for the avoided financial cost of alternative metal EUR 0.3 m
production from raw materials.
Calculation of avoided financial cost of metal production is as follows:
Amount of ferrous metal recovered annually (4 000 t) x estimated long-term average market price of
scrap ferrous metal (80 EUR/t) = EUR 0.3 million
B2. Avoided externalities from GHG emissions through improved waste management and EUR 7.5 m/
material/energy recovery EUR 11.8 m
B2a. Avoided GHG emissions through improved waste management (avoided GHG from
landfills minus additional fossil CO2 emissions from incineration of waste) EUR 1.5 m /
The specific GHG emissions per tonne of waste estimated for landfills was in this case 0.67 tCO 2eq/t in EUR 1.1m
the first year of operations, progressively decreasing to 0.62 tCO 2eq/t at the end of the reference
234
The value was taken from the national CBA guideline, which is an average estimated for the country recommended for use in case no
better estimate is available for the specific project region.
235
In this case study the coal is assumed to be imported. In cases where the coal is mainly from domestic production, the penalty for security
of supply can be removed or reduced.
236
The production cost is based on an average cost of fuel including transport of around 85 EUR/t. An expert estimate was used for the
penalty cost for security of supply of coal.
237
The use of the generation cost of the CCGT as a basis to monetise the economic benefit of electricity generation in the WtE plant is a
simplification. As in this case the counterfactual scenario is one in which no plant is built, a more realistic estimation of the economic benefit
would be to consider the average generation cost of two plants: the existing marginal plant (generation displaced in the short and medium
term) and a CCGT (generation displaced in the long term). It is to be noted that the definition of the marginal plant is specific for each
country.
\194
Value
Monetisation of project benefits
(2017 / 2042)
period. The estimated specific GHG emission factors for the WtE plant (excluding GHG emissions
avoided through displacement of fossil fuels in alternative energy production facilities, which are
calculated below) are 0.47 tCO2eq/t in the first year of operations, progressively increasing to 0.55
238, 239
tCO2eq/t at the end of the reference period .
Calculation of avoided cost of GHG emissions through improved waste management
Amount of waste treated in WtE plant (200 000 ktpa) x (GHG emission factor for landfills – GHG
emission factor for WtE plant: 0.21 tCO2eq/t to 0.08 tCO2eq/t) x shadow price for CO2 (from 36 EUR/t
240
in 2017 to 50 EUR/t in 2030 and 63 EUR in 2042) = EUR 1.5 million (2017) / EUR 1.1 million (2042)
B2b. Avoided GHG emissions through energy recovery in form of heat
The specific GHG emissions per MWh of heat produced from coal are 0.416 tCO 2eq/MWh (heat only
boiler with 85 % gross energy efficiency).
Calculation of avoided cost of GHG emissions through displacement of heat production from existing EUR 4.7 m /
source: EUR 8.4 m
Amount of heat produced per year (318 750 MWh) x specific GHG emission factor for the coal-fired
heat boiler (0.416 tCO2/MWh) x shadow price for CO2 (from 34 EUR/t in 2017 to 50 EUR/t in 2030 and
63 EUR in 2042) = EUR 4.7 million (2017) / EUR 8.4 million (2042)
B2c. Avoided GHG emissions through energy recovery in form of electricity
The specific GHG emission factor for electricity produced in a CCGT is applied in the calculation to be
in line with the assumption made to monetise benefit B1c) above: 0.36 tCO 2eq/MWh.
Calculation of avoided cost of GHG emissions through displacement of electricity production from EUR 1.1 m /
alternative source: EUR 1.9 m
Amount of electricity exported to grid per year (84 250 MWh) x specific GHG emission factor for
electricity produced in CCGT (0.36 tCO2eq/MWh) x shadow price for CO2 (from 36 EUR/t in 2017 to 50
241
EUR/t in 2030 and 63 EUR in 2042) = EUR 1.1 million (2017) / EUR 1.9 million (2042)
B2d. Avoided GHG emissions through ferrous metal recovery
The estimated specific GHG emissions avoided per tonne of ferrous metal recycled is 1.521 tCO2eq/t
Calculation of avoided cost of GHG emissions through recycling of ferrous metal: EUR 0.2 m/
Amount of metals recovered per year (4 000 t) x specific GHG emission factor for metal recycling EUR 0.4 m
(1.521 tCO2eq/t) x economic cost of CO2 (from 36 EUR/t in 2017 to 50 EUR/t in 2030 and 63 EUR in
2042) = EUR 0.2 million (2017) / EUR 0.4 million (2042)
Total economic benefit (B1+B2) EUR 29.5 m /
EUR 33.7 m
Based on these assumptions, the following results were obtained from the economic analysis of
the project.
238
Specific GHG emissions from landfill and the WtE plant are expressed in CO 2 equivalents (CO2eq) per tonne of waste input. Other GHG
considered besides CO2 are methane (CH4) and nitrous oxide (N2O), which are converted into CO2 equivalents by applying a factor that
expresses their climate change effect relative to the one of CO 2 (i.e. 21 for CH4 and 310 for N2O).
239
The specific emission factors for landfills and the WtE plant vary throughout the reference period because their calculation considers the
future changes assumed in the composition of mixed residual wastes to be treated in the WtE plant (i.e. decreased content of kitchen/food
waste and increased content of plastic). The specific emissions from landfills are calculated assuming well-managed engineered landfills as
the ones existing in the proximity of the project area. The model used for the calculation is one developed by JASPERS for waste management
facilities (http://www.jaspersnetwork.org/jaspersnetwork/display/for/Calculation+of+GHG+Emissions+in+Waste+and+Waste-to-
Energy+Projects).
240
The assumed shadow prices for CO2 are consistent with the values suggested in section 2.8.8 of this guide (EIB estimates), adjusted to
constant 2013 prices. The escalation by EUR 1.1 million per year in the period 2031 – 2042 is also consistent with the suggestion made in this
guide (also expressed in constant 2013 prices).
241
The total electricity production of the WtE facility is used in the calculation, including the own-process related electricity consumption, as
the latter is considered on the cost side as well, monetised with the same electricity price. Hence, the cash-flows corresponding to the own-
process related electricity consumption cancel each other out in the total project cash-flow.
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1 2 3 4 5 6 10 15 20 25 30
ERR
Construction Operation
5%
Socio-economic costs NPV 5 %
Investment cost M EUR -138.7 -7.2 -84.4 -42.6 -14.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M cost including reinvestments M EUR -131.7 0.0 0.0 0.0 0.0 -8.4 -8.4 -8.4 -8.5 -71.8 -8.6 -14.0
Fixed O&M cost M EUR -77.0 0.0 0.0 0.0 0.0 -6.2 -6.3 -6.3 -6.3 -1.8 -6.5 -6.5
Variable O&M cost M EUR -25.7 0.0 0.0 0.0 0.0 -2.1 -2.1 -2.1 -2.1 0.0 -2.1 -2.1
Reinvestment cost M EUR -29.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -70.0 0.0 -5.3
Residual value of investments M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Total economic costs M EUR -270.3 -7.2 -84.4 -42.6 -14.5 -8.4 -8.4 -8.4 -8.5 -71.8 -8.6 -14.0
Socio-economic benefits NPV 5 %
B1. Resource cost savings M EUR 264.3 0.0 0.0 0.0 0.0 22.0 22.0 22.0 22.0 0.0 22.0 22.0
B1a. Economic value of landfill space saved M EUR 72.1 0.0 0.0 0.0 0.0 6.0 6.0 6.0 6.0 0.0 6.0 6.0
B1b. Economic value of recovered energy in form of heat M EUR 111.8 0.0 0.0 0.0 0.0 9.3 9.3 9.3 9.3 0.0 9.3 9.3
B1c. Economic value of recovered energy in form of electr. M EUR 76.5 0.0 0.0 0.0 0.0 6.4 6.4 6.4 6.4 0.0 6.4 6.4
B1d. Economic value of recovered metal M EUR 3.8 0.0 0.0 0.0 0.0 0.3 0.3 0.3 0.3 0.0 0.3 0.3
B2. Avoided environmental externalities M EUR 107.3 0.0 0.0 0.0 0.0 7.5 7.6 8.1 8.9 0.0 10.7 11.8
B2a. Avoided GHG emissions through improved waste mgt. M EUR 13.4 0.0 0.0 0.0 0.0 1.5 1.4 1.2 1.0 0.0 1.0 1.1
B2b. Avoided GHG emissions through heat prod. from waste M EUR 73.9 0.0 0.0 0.0 0.0 4.7 4.9 5.5 6.2 0.0 7.7 8.4
B2c. Avoided GHG emissions through electr. prod fr. waste. M EUR 16.7 0.0 0.0 0.0 0.0 1.1 1.1 1.2 1.4 0.0 1.7 1.9
B2d. Avoided GHG emissions through metal recovery fr. waste M EUR 3.4 0.0 0.0 0.0 0.0 0.2 0.2 0.3 0.3 0.0 0.4 0.4
Total economic benefits (B1+B2) M EUR 371.6 0.0 0.0 0.0 0.0 29.5 29.6 30.1 30.9 0.0 32.7 33.7
Net benefits (ENPV) M EUR 101.3 -7.2 -84.4 -42.6 -14.5 21.1 21.2 21.7 22.4 -71.8 24.1 19.8
ERR 10.6%
B/C RATIO 1.37
With an estimated 10.6 % economic rate of return, a positive economic net present value of EUR 101.3
million and a benefit/cost ratio equal to 1.37, the construction of the WtE plant is expected to increase
social welfare. Therefore, it is worth supporting with a grant from the EU.
VII Risk Assessment
Sensitivity analysis
The sensitivity analysis assesses the effects of possible changes in the key project variables on the
project’s financial and economic performance indicators. In both the financial and economic analysis,
the analysis is carried out using aggregated and selected disaggregated variables (i.e. demand and
prices separately) to better identify possible critical variables.
The elasticity calculated for the ENPV and FNPV(C) with respect to the different input variables242, as
well as their switching values243, are shown in the table below.
FNPV(C) Switching ENPV Switching
Variable
elasticity value elasticity value
Econ./Fin. investment cost 4.2 % -24 % -1.4 % 73 %
Econ./Fin. O&M cost (incl. reinvestments) 4.5 % -22 % -1.3 % 77 %
Waste input -6.8 % 15 % 3.4 % -29 %
Gate fee (WtE) -3.6 % 28 % - -
Econ./Fin. heat price -1.9 % 54 % 1.1 % -91 %
Econ./Fin. electricity price -2.1 % 47 % 0.8 % (*)
Shadow price of CO2 - - 1.1 % -94 %
Shadow price of landfill space - - 0.7 % (*)
(*) No switching values were calculated in these cases as the ENPV would not become 0 even if the variable were 0
Spider diagrams illustrating the elasticities and switching values for the above mentioned variables
are depicted below.
242
The elasticity is defined as the percentage change in the NPV indicator for a +1 % change in the variable.
243
The switching value is the percentile change required in an input variable to make the NPV indicator turn 0.
\196
Sensitivity Analysis - ENPV Sensitivity Analysis - FNPV(C)
300 100.0
Econ./Fin. Investment cost
250
Econ./Fin. O&M costs 50.0
(excl. reinvestments)
200
Waste flow
FNPV(C) (M EUR)
0.0
ENPV (M EUR)
150 Econ./Fin. Electricity Price
100 Econ./Fin. Heat Price -50.0
Shadow price of CO2
50
-100.0
Shadow price of landfill
0 space
40% 60% 80% 100% 120% 140% 160%
-150.0
-50
-100 -200.0
Change in variable 40% 60% 80% 100% 120% 140% 160%
Change in variable
The sensitivity analysis shows that in the economic analysis, only the waste input, and to a lesser
extent the investment and operating cost as well as the economic cost of heat and the shadow price of
CO2, constitute critical variables. In the financial analysis, on the other hand, most of the tested
variables are critical for the FNPV(C)244. This can be explained by the fact that the FNPV(C) is not far
from 0 (in which case the project investment would be sufficiently profitable without any external
support).
With regards to the waste input, which appears as the most critical variable in both cases, it needs to
be noted that the demand analysis was carried out based on conservative assumptions on waste
generation both at regional level and in the three large towns that are promoting and co-financing the
project. Still, the demand analysis shows that the three towns alone can easily provide the required
amount of waste to ensure that the design capacity of the plant is used to the maximum extent over the
short, medium and long term. This would still hold true even if source separation of recyclables in the
three towns should develop better than expected. Hence, the probability of a decrease of the annual
waste throughput equal to the switching value for the ENPV is very low. A higher annual throughput
than the designed capacity is not possible, so the switching value for the FNPV(C) is purely theoretical.
With regards to the project costs, unit costs calculated for both construction and operation of the plant
compare very well with those of similar projects recently implemented and currently in operation in
the EU. The investment cost estimates have also been confirmed in consultations with manufacturers
of plants and equipment to cross check with current market conditions. With regards to the disposal
costs for waste produced in the WtE plant, it can be said that these were consulted with disposal
companies operating in the region. Environmental assessments confirm the legality and viability of the
proposed disposal methods. Consequently, there is no reason for serious doubt in the reliability of any
of the project’s cost estimates, so that the switching values for the investment and O&M cost can be
considered as highly unlikely to occur in reality.
With regards to the estimation of the economic benefit of replacing heat production from coal with
heat produced by the project, it is to be noted that the value assumed for the avoided cost of heat
production has been calculated based on conservative assumptions on the price of coal, as well as on
capital and operating cost for heat production. It is therefore quite unlikely that its switching value
(required for the ENPV to become 0), which is around -91 %, could somehow materialise. This would
not be the case even if the internalised penalty for security of supply of coal were removed or if the
long-term marginal cost of heat production were replaced with the short-term marginal cost (as in the
financial analysis).
On the assumed financial heat price received for heat supplied, it should be mentioned that the
conditions for the heat off-take (including the price) have been negotiated in advance with the local
district heating provider, with whom a basic agreement exists that is also supported by the local
government of the municipality in question. An important decrease of the heat price below the
assumed level appears thus highly unlikely.
244
A critical variable is defined as one whose variation by 1 % leads to a variation of the project’s FNPV or ENPV by more than 1 %.
\197
With regards to the assumed shadow price of CO2, it has been noted already that the assumed values
are estimates used by the EIB, which gives them a high degree of credibility.
With regards to the project facility’s gate fee, which is also very critical for the financial analysis, it
should be mentioned that the values assumed in the analysis have been discussed and approved by the
municipal governments of the three towns participating in the project which is why these are not
likely to change in the future.
All in all, the assumptions made for the critical variables of the project appear to be well founded
which makes the results of the CBA appear robust.
Risk analysis
Based on the results of the sensitivity analysis and taking into account uncertainties related to aspects
not directly reflected in the CBA calculations, a risk matrix was prepared in order to identify possible
risk prevention and mitigation measures.
Residual
Proba Sever Risk risk after
Risk description bility* -ity level* Risk prevention / mitigation measures prevention
(P) (S) (=P*S) /mitigation
measures
Demand side
risks
Demand analysis is carried out based on conservative
assumptions on waste generation in the project’s
catchment area which are comparable with
assumptions made in other regions in the country.
Available waste
Local governments of the three towns participating in
flow is much lower
Moder the project control the waste flow within their collection
than the design B III Low
ate zones and will produce more than sufficient residual
capacity of the
waste to ensure maximum use of the demand capacity
plant
in the short, medium and long term.
Function in charge: project beneficiary in coordination
with municipal governments of the three towns
participating in the project
Changes in composition of household waste and
separation rates of recyclables and other waste
fractions assumed in the demand forecast are plausible
Composition and and based on developments observed also in other
calorific value of countries. Calorific value assumed for the input waste is
the actual input in line with that of waste of other urban areas within the
Moder country and abroad.
waste are outside C III Low
ate
of the range used In case of seasonal fluctuations in waste composition,
to design the appropriate mixing with waste from different sources
incineration plant from within the same catchment areas is possible.
Function in charge: project beneficiary in coordination
with municipal governments of the three towns
participating in the project
Heat off-take agreement has been negotiated with local
Uncertainty with district heating provider and is reflected in a declaration
regards to off-take of intent signed by the two parties. Agreement is
C IV High Low
of heat produced supported by the local government of the relevant town.
in the plant Function in charge: project beneficiary, local
government of the relevant town
Financial risks
Investment cost estimates compare well with costs
experienced with similar projects implemented in the
EU in the last years. Consultations with plant and
Investment cost Moder equipment manufacturers were carried out to cross-
C III Low
overrun ate check estimates with current market conditions.
Publication of contract notices in the Official Journal of
the EU to ensure wider competition.
Function in charge: project beneficiary
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Residual
Proba Sever Risk risk after
Risk description bility* -ity level* Risk prevention / mitigation measures prevention
(P) (S) (=P*S) /mitigation
measures
Operating cost estimates compare well with costs
experienced with similar projects in operations.
Consultations with plant and equipment manufacturers
were also carried out to cross-check estimates.
Real increases in staff costs have been considered in
Operating cost Moder the operating cost forecasts.
B III Low
overrun ate
Electricity consumption, which makes up 13 % of total
O&M cost is largely covered by own production.
Waste disposal costs have been consulted with
disposal companies active in the region.
Function in charge: project beneficiary
National public grants confirmed through commitments
of the national government to co-finance the relevant
OP.
Regional Government and involved Municipalities have
all provided written commitments to (co-)finance the
project, interests during construction and initial working
Problems with
capital.
availability of local C IV High Moderate
Project beneficiary is seeking a loan from the EIB to co-
co-financing
finance the project, for which first negotiations have
started.
Function in charge: Ministry of Finance, managing
authority responsible for the OP, regional government,
municipal governments of the three towns participating
in the project, project beneficiary
Delays in project
preparation and Involve JASPERS technical assistance early in the
approval leading Moder project cycle to reduce time for project approval.
C III Low
to late availability ate Function in charge: Managing authority responsible for
of EU grant co- the OP, project beneficiary
financing
Proposed gate fees for the WtE have been agreed in
advance with the three towns participating in the
project.
The heat off-take price has been negotiated and agreed
in principle with local DH service provider and is
reflected in a declaration of intent signed by the two
Shortfall in parties. The agreement includes provisions for regular
revenues from price adjustments for inflation and for changes in the
gate fees and price of coal or the price paid by the district heating
Moder
sales of materials B IV operator for CO2 emissions. Low
ate
and energy
The off-take price for electricity is a long-term average
jeopardises debt
which has been assumed in accordance with current
service
forecasts of demand and supply.
The scrap metal price is set based on the current
market price which is considered a conservative
assumption for the future (demand growth is expected
to outpace supply so prices are not expected to fall).
Function in charge: project beneficiary
Implementation risks
Land is owned by one the municipalities promoting the
Problems with project. Conditions for land purchase have already
A II Low Low
land purchase been agreed in principle.
Function in charge: project beneficiary.
The public consultation process required as part of the
EIA is well advanced and concerns raised during public
Problems with
Very hearings do not represent any critical issue for the
public opposition D IV Moderate
high project. Recommendations made by environmental
to the project
NGOs have been partially incorporated into the project.
Publicity measures aimed at informing the public about
\199
Residual
Proba Sever Risk risk after
Risk description bility* -ity level* Risk prevention / mitigation measures prevention
(P) (S) (=P*S) /mitigation
measures
the project and its objectives are included in the project.
Function in charge: project beneficiary
Promoter’s procurement division to be supported by
Delays related to
Moder specialised technical assistance. Appropriate time
extension of C III Low
ate contingencies are factored into the project schedule.
tender procedures
Function in charge: project beneficiary
Operational risks
Limits for
emissions of Selection of proven, best-available technologies for flue
pollutants to A II Low gas treatment and wastewater treatment facilities Low
air/water are Function in charge: project beneficiary.
exceeded
* Evaluation scale: Probability: A. Very Unlikely; B. Unlikely; C. About as likely as not; D. Likely; E. Very Likely.
Severity: I. No effect; II. Minor; III. Moderate; IV. Critical; V. Catastrophic.
Risk level: Low; Moderate; High; Very High
The risk analysis convincingly shows that the residual risks for the project are either low or moderate
as a result of the measures already implemented to prevent the occurrence of the identified risks
and/or to mitigate their adverse impact in case these should unexpectedly materialise. All in all, the
overall level of residual risk is deemed to be fully acceptable, It can be therefore concluded that,
provided that the project is awarded with the EU funds as expected and recommended, the probability
of the project failing to attain its targeted objective at a reasonable cost is only marginal.
\200
5. Energy
5.1 Introduction
Investments in energy infrastructures in EU Member States are driven by specific challenges affecting
the national, regional and international energy markets. The main issues that are specific to the EU are
related to security and reliability of supply, and affordable energy prices for consumers. Also, global
concerns for climate change call for the need of progressively substituting fossil-based energy fuels
with more sustainable sources. Related to this, another important driver is derived from the
challenges posed by the growing penetration of power generation from intermittent renewable energy
sources, particularly wind and solar, to the entire electrical system, and to the power grid in particular.
The objectives of European energy policy are the construction of appropriate cross-border
interconnections, diversification of supply sources and routes, promotion of energy efficiency, and the
acceleration of the transformation to low-carbon energy. Their strategic importance is reaffirmed in
the overarching Europe 2020 strategy for smart, sustainable and inclusive growth in the EU and in its
flagship initiative entitled 'resource-efficient Europe'. In particular, this flagship aims to help decouple
economic growth from the use of resources, support the shift towards a low-carbon economy, increase
the use of renewable energy sources, modernise the transport sector, promote energy efficiency,
enhance competitiveness and promote greater energy security. Targets have been set by the EU to
achieve a 20 % reduction of GHG emissions below the 1990 level, a 20 % share of energy from
renewable energy sources and a 20 % reduction in the use of primary energy by the improvement of
energy efficiency by 2020. Further targets have been set by the EU for 2030 as part of its policy
framework for climate and energy in the period from 2020 to 2030245: a binding EU-wide target to
reduce GHG by at least 40 % below the 1990 level, a binding EU-wide target to increase the share of
renewable energy to at least 27 %, as well as an indicative target to increase energy savings through
the improvement of energy efficiency by 27%. The importance of diversifying oil import sources in
order to ensure not only financial savings, due to increased competitiveness, but also energy security,
and the need for upgrading Europe’s network, including Trans-European Energy Networks, are also
stressed in European strategic documents.
Roadmaps, action plans and regulatory documents have been developed by European authorities. EU
strategic goals have been translated by Member States into more concrete measures to be
implemented in the upcoming years, tailored to the specific national and regional investment
priorities.
During the 2014-2020 period, the ERDF and the Cohesion Fund will invest in supporting the shift
towards a low-carbon economy in all sectors (thematic objective 4), including investments in energy
efficiency, renewable energy246, smart distribution systems and high-efficiency co-generation of heat
and power based on useful heat demand. In addition, the ERDF could also invest in improving energy
efficiency and security of supply through the development of smart energy distribution, storage and
transmissions systems, and through the integration of distributed generation from renewable
sources247. In general, investments to achieve the reduction of greenhouse gas emissions from
activities falling under Annex I of Directive 2003/87/EC (the Emissions Trading System Directive)
245Adopted by the European Council on October 23rd, 2014 taking into account the recommendations of the European Commission’s
Communication COM(2014) 15.
246 Concerning hydropower any project that modifies the hydromorphological characteristics of a water body causing deterioration of the
status has to be assessed in line with Art. 4.7 WFD.
247 As regards smart gas infrastructure, it shall have at least one of the following characteristics:
- it supports integration of generation from non-conventional sources (such as renewable energy sources, RES, based on synthetic
methane and biomethane) in the gas grids, transport and storage of such gas;
- it allows the integration of gas power plants in the electrical grids as needed for compensating the peak loads in order to allow
further integration of RES (and thus increasing the overall share of RES in the system);
- it enhances the flexibility of the gas networks, in particular through the use of IT technologies, to support demand and supply
challenges, and offers customers new services and improved effectiveness while reducing overall climate and environmental
impact compared with the existing situation. It therefore promotes a win-win scenario from a climate perspective.
\201
cannot be supported by the ERDF or the Cohesion Fund. The rationale for this exclusion is that such
investments would just foster a reduction in the price of emission permits, without achieving
additional decreases in the volume of emissions (as the number of permits remains fixed, and thus the
volume of greenhouse gas emissions).
A selective list of policy and regulatory documents for the energy sector is provided in the box below.
THE EU POLICY FRAMEWORK
Strategies, roadmaps and action plans
Communication from the Commission, ‘A policy framework for climate and energy in the period from 2020 to
2030’, COM(2014) 15.
Green Paper, ‘A 2030 framework for climate and energy policies’, COM(2013) 169 final.
Regulation (EU) No 347/2013 on guidelines for trans-European energy infrastructure and Commission
Delegated Regulation (EU) No 1391/2013 amending Regulation (EU) No 347/2013 of the European Parliament
and of the Council on guidelines for trans-European energy infrastructure as regards the Union list of projects of
common interest.
Regulation (EU) No 1316/2013 establishing the Connecting Europe Facility.
Report from the Commission to the European Parliament and the Council, 'The state of the European carbon
market in 2012', COM(2012) 652 final.
European Commission Communication 'Making the internal energy market work', COM(2012) 663 final.
European Commission Communication 'Energy Roadmap 2050', COM(2011)885 final.
European Commission Communication 'A Roadmap for moving to a competitive low carbon economy in 2050',
COM(2011) 112 final.
European Commission Communication 'Roadmap to a Resource Efficient Europe', COM(2011) 571 final.
Commission Staff Working Paper 'Energy infrastructure investment needs and financing requirements',
SEC(2011) 755 final.
ENTSO-E – European Network of Transmission System Operators for electricity, 'Ten-year Network
Development Plan'.
ENTSOG – European Network of Transmission System Operators for Gas, 'Ten-Year Network Development Plan'.
Member States’ National Renewable Energy Action Plans.248
Member States’ National Energy Efficiency Action Plans. 249
Electricity and renewable sources
European Commission Communication, 'Delivering the internal electricity market and making the most of public
intervention', COM(2013) 7243 final.
European Commission Communication, 'Renewable Energy: a major player in the European energy market',
COM(2012) 271 final.
European Commission Communication, 'Smart Grids: from innovation to deployment', COM(2011) 202 final.
Directive 2009/72/EC concerning common rules for the internal market in electricity and repealing Directive
2003/54/EC and Regulation 714/2009.
Directive 2009/28/EC on the promotion of the use of energy from renewable sources and amending and
subsequently repealing Directives 2001/77/EC and 2003/30/EC.
Natural gas
248 Available at: http://ec.europa.eu/energy/renewables/action_plan_en.htm
249 Available at http://www.energy-community.org/portal/page/portal/ENC_HOME/AREAS_OF_WORK/ENERGY_EFFICIENCY/NEEAPs
\202
Regulation (EU) No 994/2010 concerning measures to safeguard security of gas supply and repealing Council
Directive 2004/67/EC.
Directive 2009/73/EC on common rules for the internal market in natural gas and repealing Directive
2003/55/EC and Regulation 715/2009.
Energy efficiency
Commission Staff Working Document, Guidance note on Directive 2012/27/EU on Energy Efficiency, amending
Directives 2009/125/EC and 2010/30/EC, and repealing Directives 2004/8/EC and 2006/32/EC.
Directive 2012/27/EU on Energy Efficiency.
Directive 2010/31/EU on the Energy Performance of Buildings.
5.2 Description of the context
Understanding the context in which the project is implemented is the first step of any project
appraisal. This is particularly important for energy projects, as they are usually part of a network that
extends at national or international level, thus making the project’s sustainability and performance
subject to a large number of external factors. The baseline context elements recommended to be
described for energy projects are shown in the following table.
Table 5.1 Presentation of the context: Energy sector
Information
- National and regional GDP growth
- Income disposal
Socio-economic- - Demographic change
political trend 250
- Energy intensity of the economy
- Fuel price trends
- Weather and climate conditions
Geographical - Type and quantity of energy sources and fuels available within the national territory (energy
factors balance)
- Degree of interconnection and integration with other countries
- Reference to EU directives and sector policy documents (see above)
- Reference with the priority axis and the interventions areas of the operational programme (OP)
Political, - Reference to the short, medium and long-term national, regional and local planning documents
institutional and and strategies, including for example the National Renewable Energy Action Plan
regulatory factors - Political factors influencing the energy market (such as conflicts or political tensions involving
the fuel exporter countries)
- Regulatory and controlling authority(ies) and its/their role
- Structure of the market: energy utilities, wholesalers, retailers, types and number of final
consumers
Existing service - Degree of vertical integration of the market and information about market liberalisation and
market conditions
competition in the sector
- Tariff and/or energy price system and consumer price trend
- Volumes of energy production, intermediate and final consumption, import and export by type
of energy (electricity, natural gas, oil, heat, secondary bio-fuels, etc.) and energy sources/fuels
for electricity generation
- Import dependency rate
Existing service - Load profile and load factor of technologies interested in the project
technical - Seasonal and daily trend of energy consumption
conditions - Information about historic and current energy production, consumption and trade patterns
- Degree of achievement of EU/national targets for the energy sector
- Planned and/or recently executed investments that may affect the project performance
- Technical characteristics of the service currently provided
- Service quality and reliability
250 Defined as the gross inland consumption of energy divided by gross domestic product.
\203
- Infrastructure production / transportation capacity and energy storage capacity
Source: Authors
5.3 Definition of objectives
The most direct objective of energy projects is to address one or more of the challenges that affect the
energy systems in Europe, which were briefly recalled in the introductory section. In more detail,
energy projects generally aim at:
developing new energy capacity to meet increasing energy demand;
developing new energy capacity to reduce energy import dependency;
extending the energy supply network to reach non-served areas;
diversifying energy sources and supply markets;
integrating the national energy market to other countries better, so as to ensure an alignment
of consumer energy prices throughout the EU;
improving technical reliability and security of energy supply, and avoiding energy
interruptions;
increasing energy efficiency in production facilities by reducing energy losses, modernising
existing plants for energy production and promoting co-generation;
increase the efficiency and quality of the energy system by technically and/or operationally
improving the transmission or distribution of energy;
increasing consumption energy efficiency, e.g. of residential and/or public buildings and/or
technical installations, to reduce their overall energy consumption;
reducing greenhouse gases and pollutant emissions produced by the energy sector by
substituting fossil fuels with more sustainable energy sources, such as renewable ones (wind,
solar, hydropower, biomass, etc.).
5.4 Project identification
Having defined the objective of the intervention, the next step is to present in detail the proposed
project to be implemented. The focus is on the following two categories of projects:
construction, modernisation and quality improvement of energy production plants, storage,
transport, transmission and distribution networks;
actions to improve the efficiency of energy consumption, i.e. energetic rehabilitation of public
and private buildings and industrial production systems.
Information and data about the project’s engineering features, technical characteristics, expected
effects, and types and numbers of consumers served are to be provided. See the typical categories of
investment costs in section 5.5. The implementation of any investment project should be justified
against a set of feasible alternative options that allow achieving the same objective (see section 5.6).
The following table provides examples of energy investments, together with the following typologies:
Table 5.2 Examples of energy investments
- Construction of a power plant that produces electricity from a
given renewable or non-renewable source/fuel
- Modernisation of an existing power plant to increase energy
Energy production, storage, production capacity and/or energy efficiency and/or substitute the
transport, transmission and Electricity
energy fuel/source
distribution
- Construction/modernisation of a power transmission line within the
country or to other countries
- Construction/modernisation of the electricity distribution system
\204
(electrical substations, dispatch system, electricity transmission
grid)
- Development of smart transmission and distribution systems
(smart grids)
- Development and expansion of electricity storage facilities
251
- Distributed (or decentralised) generation
- Construction/modernisation of liquefied natural gas (LNG)
regasification terminals, underground storage facilities, etc.
- Construction of a new or the expansion of an existing transport
Natural gas
gas pipeline within the country or linking the national network to
the foreign gas supply systems
- Modernisation of the already existing gas supply system
- Construction/modernisation of a boiler station or thermal power
Heat plant for heat generation or co-generation
- Construction/modernisation of a district heat distribution system
Second-
generation - Construction of plants for second-generation biofuels production
biofuels
- Refurbishment of public buildings (schools, hospitals, etc.) for
improving their energy characteristics
- Refurbishment of apartment blocks and other private buildings to
Consumption energy efficiency
improve their energy characteristics
- Measures for improving energy saving and efficiency in industrial
252
productive systems
Source: Authors
5.5 Forecasting energy demand and supply
Both demand and supply of energy in a given market need to be assessed and forecasted for any
energy project. This is particularly important for projects involving the production of electricity: due
to the limited technological possibilities of storing electricity, a balance between demand and
production should always be ensured in order to avoid service disruption. Matching demand and
supply forecast is also relevant to gas projects, even if line pack, storage in caverns, aquifers, depleted
fields or other facilities (like LNG) are, in principle, possible over long periods of time: actually, the
supply of gas from abroad often relies on long-term contracts, so as to stipulate which reliable demand
estimates are needed, particularly to ensure service reliability, even during peak demand periods.
Some indications on how energy demand and supply can be forecasted for the purpose of the financial
and economic analyses are provided below.
5.5.1 Factors influencing energy demand
Energy products (natural gas, electricity, heat and biofuels) can be demanded by final consumers, i.e.
households, commercial activities and industries or public bodies, and intermediate consumers that
transform an energy product into a different one (natural gas can be combusted to produce heat or
electricity). When forecasting energy demand of both categories of energy projects (i.e. energy
production, transport, transmission and distribution projects, and projects for energy-efficient
consumption), different factors need to be taken into account and duly analysed. The most important
ones253 are:
demographic dynamics: the total energy demand is directly related to the size of population;
251 Electricity generated by a consumer from an eligible on-site-generating facility and delivered to the local distribution facilities.
252 Measures for energy saving and efficiency improvements in both SMEs and large enterprises are eligible, although the latter are not an
investment priority for EU funds.
253 Not all of the factors hereby listed may be relevant to all specific typologies of energy projects.
\205
economic trend (e.g. gross domestic product, GDP, growth and per capita GDP): a fast-
growing economy generally demands a higher quantity of energy than a flat economy; in
parallel, higher standards of living are associated with a higher demand for energy;
weather and climatic conditions: they largely affect the demand for heating and cooling;
tariff system: it could affect the level of consumption, but also the timing, if discounted prices
are provided during off-peak hours;
particular energy efficiency developments in energy transportation/transmission and/or
energy consumption (i.e. through targeted investments): they can also notably affect total
gross energy demand.
5.5.2 Input data for demand analysis
The most important input data to be considered for forecasting energy demand are:
annual total and average consumption of energy products, e.g. in TWh/year (for electricity) or
bcm/year (for gas), by type of consumers. The following categories of consumers are generally
considered:
o household/commercial final consumers,
o industrial final consumers, and
o energy transformation sector;
the peak demand, generally expressed in GW for electricity and mcm/day for gas;
variability of seasonal and daily levels of consumption;
annual export demand.
5.5.3 Factors influencing energy supply
For energy production, transport, transmission and distribution projects, the project promoter should
provide projections related to the level of energy produced and/or
transported/transmitted/distributed by the project under assessment. The market shares of key
energy producers, wholesalers and retailers should also be analysed and projections of supply of
alternative energy products provided. A variation in the supply of alternative energy sources could
actually significantly affect the project performance and the energy mix to be considered in the
counterfactual scenario (see section 5.8.1).
The main factors affecting the level of energy supply associated with the project are:
national and international socio-economic and political factors influencing the fuel price
dynamics;
political decisions about the discontinuation of certain types of energy sources and fuels (e.g.
nuclear power);
system of incentives on certain types of energy sources and fuels (e.g. subsides on renewable
sources);
environmental requirements imposing additional costs to energy production;
structure, territorial size, degree of integration and performance quality of the energy
system (both production facilities and the transportation and transmission/distribution
networks);
market structure, particularly related to the number of competitors and the degree of market
openness and integration into other markets.
\206
5.5.4 Input data for supply analysis
The input data required to determine the present and future levels of energy production and which
need to be made explicit in the project appraisal includes:
structure of the electrical grid or of the transport/distribution networks;
type of plant and/or technology;
energy source or fuel used;
total installed capacity;
net capacity or utilisation rate of the infrastructure, defined as the ratio between the actual
output expected to be supplied and the maximum possible outputs;
annual volume of imported energy products;
efficiency, which varies by type of fuel and energy production technology;
estimated losses of energy produced and/or delivered;
storage capacity (for natural gas and electricity).
5.6 Option analysis
Alternative options of energy projects should be discussed and compared with each other on the basis
of the following information:254
the characteristics of the present and future energy demand and supply (see section 5.5);
the environmental conditions in the immediate project area, in particular with regards to air
pollution;
available technological alternatives: the same energy can be produced/transported/stored by
a variety of technologies, each one with different degrees of efficiency, capacity and
environmental impact;
available sources for electricity production: some areas might not be provided with particular
energy sources (e.g. water basins, sufficient solar exposure, etc.);
possible routes for energy transport, transmission/distribution network;
possible synergies with the deployment of NGA infrastructures (especially relevant for smart
grids);
applicable regulations limiting technological options (e.g. regulations forbidding energy
production from nuclear power);
notable negative public opinion / strong public opposition to certain technologies in the given
project area/country;
different peak-load arrangements.
5.7 Financial analysis
5.7.1 Investment cost
Apart from the general costs for planning and design, construction engineering and publicity,
investment costs for energy projects typically include:
land acquisition and purchase of rights of way;
254 Not all of them may be relevant to all typologies of energy projects.
\207
decommissioning/dismantling/demolition costs borne when rehabilitating old energy-
generation facilities;
technological plant installations and equipment;
mobile equipment required for operations;
connections to the relevant utility networks;
road access;
skilled and non-skilled labour costs;
information technologies, particularly relevant in case of smart grid projects;
mitigation measures for environmental protection255;
testing and training of operational staff before start of operations.
The investment cost of the project could also be presented per capacity installed (e.g. EUR/KW for
electricity generation, EUR/m3 for gas storage capacity) or length of power lines/pipelines (EUR/km),
in order to allow for comparisons and benchmarking to similar projects.
5.7.2 Operation and maintenance costs
Operating and maintenance (O&M) costs of energy projects can be differentiated between variable and
fixed costs, depending on whether they vary with the quantity of energy produced/distributed or not.
Fixed O&M costs, whose magnitude depends on the type of project, usually include:
cost for public concessions fees or other permits;
general overheads;
insurance costs;
labour costs;
periodic fixed maintenance and repairing costs.
The most relevant variable operating costs are:
energy fuel costs;
variable overheads;
utilities;
other goods and services for energy production or transportation/transmission/distribution;
waste disposal costs (including solid waste and waste water);
for projects involving the construction or modernisation of energy production plants, the cost
of greenhouse gas (GHG) emission allowances purchased within the European Emission
Trading System (ETS)256, or of similar permits and certificates issued by the different national
systems for energy projects producing GHG emissions, have also to be considered as part of the
255 For instance, installation of filters for pollution prevention or treatment systems for waste water and fumes or human safety (e.g.
emergency preparedness training programme).
256 The European Union Greenhouse Gas (GHG) Emission Trading Scheme (EU ETS) is one of the major pillars of EU climate policy. The
scheme was established by Directive 2003/87/EC and is meant to enable the EU and Member States to meet the commitments to reduce GHG
emissions, in compliance with the Kyoto Protocol. The scheme, that commenced operations in January 2005, requires that all installations
operating in any of the activities listed in Annex I of the Directive, including activities in the energy sector, and emitting GHGs must be in
possession of an appropriate permit issued by the competent authorities.
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project O&M costs, as far as they represent real cash flows257;
costs for dismantling and decontamination (if relevant) after decommissioning of large
facilities at the end of their economic life. These costs should be duly substantiated with
references to cost experiences with comparable facilities that were dismantled in the past.
5.7.3 Revenues
Revenues are generally associated with energy projects for production, transport, transmission and
distribution and not to projects for energy-efficient consumption. The main typologies of revenues
related to these can be classified under the following categories:
energy or fuel sales: a tariff or a unit price, which is paid by consumers of the energy supplied
by the project, usually made of a combination between a fixed and a variable component. Both
the tariff and the unit price may depend on a large number of factors, such as the level of
consumption, the timing of consumption (during peak or off-peak hours) and the type of user.
Also, the tariff could include an incentive component (e.g. feed-in tariff), usually aimed at
rewarding renewable energy producers with higher energy prices than the energy price
applying to other energy producers over the same market;
transport or other service sales: a tariff or a price, which is paid by users of the project
infrastructure for the service of transporting electric energy through a grid, or heat and gas
through a pipeline network. Similarly, a price can be paid for other types of network and
ancillary services (measurement, supply adjustments, balancing, capacity payments, etc.). Even
in this case, the tariff or price, which generally encompass fixed and variable components,
depends on several factors: among others, the amount of capacity reserved, energy
transported, the type of service, the timing of the required service, the duration of the contract,
etc.;
sale of energy allowances: for those specific types of projects falling under the ETS Directive
and which are eligible for the ERDF or Cohesion Fund, if ETS allowances or similar certificates
compensating for the reduced production of GHG emissions are sold on the national or
European market (and this gives rise to a real cash flow for the project operator), the resulting
revenues have to be included among the project inflows.
5.8 Economic analysis
Energy projects can produce different social benefits and costs, depending on the specific typology of
the project implemented as compared with the counterfactual scenario.
Sub-section 5.8.1 provides a presentation of the main effects usually associated with the construction,
modernisation and quality improvement of energy supply networks and/or energy production plants
and discusses the methodologies recommended for their evaluation.
Sub-section 5.8.2, instead, is focused on the benefits produced by energy efficiency projects for public
and private buildings and industrial productive systems.
5.8.1 Energy production, storage, transport, transmission and distribution
Various types of projects for energy production, storage or transport/transmission/distribution are
generally associated with benefits, such as:
increase and diversification of energy supply to meet increasing demand;
257 Investments to achieve the reduction of greenhouse gas emissions from activities falling under the ETS Directive cannot be supported by
the ERDF or the Cohesion Fund. However, in some very specific cases (e.g. fuel switched from fossil to biomass-based energy) certain
investments might be eligible. When an investment combines renewables and combustion installations with a rated thermal input exceeding
20 MW, the part of the operation relating to combustion installations will not be eligible.
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increase of security and reliability of energy supply, i.e. reduction in the frequency of
episodes of power or gas interruptions during the daytime or periods of the year or in
geographical areas;
reduction of energy costs for substitution of the energy source, because of the change of
the country from which the energy is imported, a substitution of self-production with import
or of import with self-production, and the displacement of the source or fuel for electricity
production;
market integration, i.e. the ability of a power system to reduce congestion so that energy
markets can trade power in an economically efficient manner and achieve higher
socioeconomic welfare;
improved energy efficiency leading to a reduction in the cost of production, storage or
transport/transmission/distribution per unit of energy.
Two environmental externalities are common to all these types of energy projects. These are the
variations of GHG emissions and air pollution (e.g. in particular, airborne pollutants such as SO 2, NOx,
particulate matter (PM), volatile organic compounds (VOCs), mercury and other heavy metals, etc.).
Table 5.3 Typical benefits of energy projects
Economic benefit Type of effect Examples of typical projects
Construction of a new energy production plant
Increase and Increase of production capacity of an energy facility
diversification of
Direct Construction/expansion of energy storage facilities
energy supply to meet
increasing demand Construction of an interconnector or LNG regasification facilities to expand
the volume of imported energy
Construction of a new energy production plant
Construction/modernisation of energy supply systems within the country
Increase of security Integration of electricity and natural gas networks into EU electricity and
and reliability of energy Direct gas supply systems
supply Construction/expansion of energy storage facilities
Development of a smart distribution system (smart grids)
258
Integration of renewable energy sources in the power network
Reduction of energy Construction of a new energy production plant displacing existing ones
costs for substitution of Direct Construction/modernisation of energy supply systems within the country
the energy source Development of a smart distribution system (smart grids)
Construction/expansion of storage facilities
Market integration Direct
Development of new cross-border transmission lines
Improved energy Modernisation of energy facilities to improve production efficiency
Direct
efficiency Modernisation of an energy distribution system to reduce losses
Variation of GHG
Externality All types of energy projects
emissions
Variation of air
Externality All types of energy projects
pollutant emissions
Source: Authors
Table 5.4 presents the different methods suggested to evaluate the above-mentioned benefits, along
with the counterfactual scenario usually adopted. Methodologies are more extensively discussed in the
following sections. The case study on the gas pipeline, at the end of this chapter, presents a worked
example for the evaluation of the direct benefits 'increase of energy supply to meet increasing demand'
and 'reduction of energy costs for the substitution of the energy source'.
258 In case of intermittent forms of renewable energies, such as solar, wind and tidal, the generation is not 'dispatchable', i.e. the amount of
electricity generated cannot be controlled and adjusted to match demand. Thus, the impact of the benefit from increased security and
reliability of energy supply should be considered net of additional external costs related to the use of standby capacity, which is required to
provide reliable supplies round the clock.
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Table 5.4 Methods to value the benefits of energy projects
Economic benefit Valuation method(s) Counterfactual
Increase and diversification - ‘Do-minimum’ option: next best
Willingness to pay (WTP) for increased energy
of energy supply to meet alternative to meet increased
consumption
increasing demand demand
- WTP for increased security and reliability - Business as usual, or
Increase of security and of supply (e.g. value of lost load in - ‘Do-minimum’ option: next best
reliability of energy supply electricity) alternative to increase security and
- Avoided social cost for non-served energy reliability of energy supply
- Business as usual: the same
Reduction of energy costs
Variation in economic costs of the energy source or electricity
for substitution of the energy
substituted/substituting energy source/fuel production mix continues to be
source
used
- Cost savings
- Increased socioeconomic welfare - Business as usual
Market integration
(consumer surplus + producer surplus +
congestion rents for electricity)
Variation in economic costs of the energy
Improved energy efficiency - Business as usual
source/fuel
Variation of GHG emissions Shadow price of GHG emissions - Business as usual
Variation of air pollutant
Shadow price of air pollutants - Business as usual
emissions
Source: Authors
RELATION BETWEEN BENEFITS AND POLICY OBJECTIVES
The estimates of benefits can be commented on to show the contribution of the project to some of the objectives
of the EU energy policy. In particular:
- if the project concerns the displacement of an imported energy product (e.g. electricity) with self-production
at a lower cost, the estimate of reduced energy production/supply costs from the substitution of the energy
source captures the decreased energy import dependency of the country;
- if the project allows importing energy at a cheaper price and displacing less efficient national generation,
thanks to the increased interconnection capacity of the country, the benefit would reflect the increased
integration of the EU market;
- if the project concerns the replacement of a fossil fuel with a renewable energy source, the estimate captures
the progress towards a low-carbon economy and the increased diversification of energy sources;
- if the project concerns interventions to reduce energy losses/consumption so as to lower
production/consumption costs, the estimate captures an increase of energy efficiency and the reduction of
GHG emissions and pollutants.
5.8.1.1 Increase and diversification of energy supply to meet increasing demand
A project aimed at increasing (and diversifying) the current total level of energy production in a
country or a region in order to meet growing demand, or at extending the energy network to areas
currently not served, yields higher revenues for the energy producer/distributer, which are accounted
for in the financial analysis.
While, in the case of power, average wholesale prices do generally reflect the marginal cost of energy
generation, the socioeconomic value ascribable to the improved energy service is not properly
reflected in observed prices to final users, due to various market distortions, like feed-in tariffs. For
this reason, in the economic analysis the financial revenues should be replaced by a shadow price
computed as the users' willingness-to-pay for receiving one more unit of energy.
The WTP can be estimated in three possible alternate ways:
revealed preference method: the avoided costs associated with the alternative systems of
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energy production (e.g. self-generation of electricity and heat through micro turbines and
boilers respectively) that the user would employ in order to meet the demand not addressed
by the existing supply system can be considered as a proxy of the economic value of increased
energy consumption;
stated preferences method: an ad hoc contingent valuation can be put in place to derive the
maximum price that the project’s users would be willing to pay for one more unit of energy
consumed;
benefit transfer: the economic value for one more unit of energy consumption estimated
through a contingent valuation for other countries can be plugged into the project’s economic
analysis, provided that the necessary adjustments are made in order to better adapt the value
to the specificities of the project context. In general, the unit economic cost of incremental
energy should be adjusted to the national per capita GDP.
Having the WTP for one unit of energy consumed, the benefit can be estimated by multiplying it with
the incremental volume of energy consumed.
5.8.1.2 Increase of security and reliability of supply
Some investment projects in the electricity sector – such as the improvement of a power transformer
station, the integration of renewable energy sources in the power grid or smart grid projects259 to
meet peak demand better – could contribute towards determining a reduction in the frequency of
episodes of power disruptions during the day or periods of the year or in geographical areas. Similarly,
for projects in the gas sector, such as the construction of liquefied natural gas terminals, the increase
of the domestic storage capacity or new pipelines changing or diversifying the source of gas, could help
to avoid unexpected gas supply shortfalls. In all these situations, the final energy consumers enjoy the
benefit of increased security and reliability of energy supply, which must be properly valued. To this
end, two possible approaches could be adopted.
The first one entails the estimation of the users’ WTP for increased energy reliability and security of
supply. The WTP can be estimated via:
revealed preferences: if a compensation system for users covering the losses incurred due to
a disruption of energy supply is in place, the compensation paid for the quantity of energy not
supplied or for the time of disruption can be taken as a proxy of the users' willingness-to-
accept for the poor quality of service, which, in principle, should be equal to the willingness-to-
pay for an improved service. Alternatively, if there is no compensation system and the project
users employ alternative systems of energy production/supply (own systems or provided by
others) in order to ensure the continuity of the service even during (usually short) periods of
disruption, the total costs associated with these alternative systems can be considered as a
proxy of the value of increased reliability of energy consumption. Finally, another method is to
consider the avoided cost of ensuring security of supply through the next best alternative (for
example, in the case of a gas interconnection project, the next best alternative could be an
underground gas storage or a LNG facility);260
stated preferences: an ad hoc contingent valuation can be put in place to derive the maximum
price that the project’s users would be willing to pay for a reduction in the frequency/duration
of episodes of energy interruptions;
benefit transfer: the possibility of transferring values of WTP estimated in other countries to
the country in which the project is implemented (benefit transfer) should also be examined.
However, this method might not be very effective, since the WTP is usually estimated on the
basis of customer damage functions (modelling social costs for interrupted energy as a
259 See European Commission (2012) JRC Reference Reports, Guidelines for a Cost-Benefit Analysis of Smart Grid projects.
260 See also Guidelines of Good Practice on Estimation of Costs due to Electricity Interruptions and Voltage Disturbances, Council of European
Energy Regulators, 7 December 2010.
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function of the interruption duration), which are very country-specific. Therefore, it is
generally recommended to adjust the WTP values to the specificities of the project, otherwise
different methods of estimation should be applied.
As a second best option, the project appraiser could value the social cost of non-served energy that is
avoided thanks to the project implementation. This cost can be obtained, for example, by dividing the
annual gross value added (GVA) by the annual volume of energy (electricity, gas, heat, etc.) consumed
in the economy, possibly distinguishing between different economic sectors (e.g. industry, commerce
and services, agriculture, fishing, etc.). For domestic consumers, the cost of energy not supplied can be
determined in a similar way, by dividing the annual household disposable income by annual domestic
energy consumption. This is a very simplistic method, but has the advantage of not relying on direct
surveys to assess the consumers’ WTP.
The cost of non-served energy should be used to value the additional energy made available in the
system thanks to the project, against a without-the-project scenario in which interruptions are more
frequent or prolonged. Hence the probability of future energy disruption should be compared to the
probability existing without the project implementation, so as to estimate the value of energy of the
avoided interruption.
5.8.1.3 Reduction of energy costs for substitution of the energy source
A variety of energy investment projects aims at reducing energy production and distribution costs, by
substituting one energy source with another. The concept of energy substitution can be intended in
different ways, namely:
substitution of the energy import country: the project implementation (e.g. a new gas
pipeline, a LNG terminal or a high-voltage power line) allows for substituting part (or all) of
the energy imports supplied by certain countries with more convenient (i.e. cheaper) energy
supplied by a different country;261
substitution of self-production with import: a project increasing the interconnection of the
energy market could allow the substitution of energy produced domestically with cheaper
energy imported from another country;
substitution of import with self-production: the project (e.g. the construction of a new
energy generation plant or interventions to increase their capacity) intends to decrease
dependency on energy imports by substituting part (or all) of the imports with domestically
produced energy;
substitution of the source or fuel for electricity production: the project allows the
production of electrical energy that uses an energy source/fuel in substitution of another one,
thus changing the production mix of electricity (e.g. the construction of a new power
generation plant for renewable sources to substitute electricity produced from fossil-based
sources, or the installation of co-generation plants producing electricity and heat from natural
gas instead of oil products).
Of course, these projects could also produce a variation of external costs, such as GHG and pollutants’
emissions, and/or a change in energy reliability and security of supply. However, these benefits should
be treated as separated (see also the gas pipeline case study and the waste-to-energy case study) and
valued as shown elsewhere in this section. The focus here is on the reduction of costs that are possibly
experienced by the energy producer and distributer because of the substitution of the energy source.
Note that the project could also be associated with an increase in energy production/distribution
261The substitution of the energy import country could also be aimed at increasing the security of supply, by supplying energy from a more
reliable source. However, this benefit is already captured by another estimate (see section on 'Increase of security and reliability of energy
supply'). Here the focus is on projects that allow a reduction of energy costs, regardless of any possible contribution to security and reliability
of supply.
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costs, for example where projects displace dispatchable fossil-fuel generation with intermittent
renewable energy sources, which generally impose an extra cost to the system for balancing (cost of
countertrading by the transmission system operator to avoid the overloading of saturated
transmission lines or to increase generation when RES production is lower than forecast). An increase
of costs imputable to the substitution of energy sources must be valued through the same
methodology as presented in this section. However, projects of this type could still produce a net
benefit to society if these costs are overcome by other benefits.
In the economic analysis, the variation of the costs related to tradable energy sources (e.g. natural gas
and electricity) should be estimated by computing the opportunity cost of the different energy items
produced in the project reference markets and the counterfactual scenario.
For projects involving the substitution of the energy source/fuel for electricity generation, the
opportunity cost of the substituted and substituting sources/fuels (oil, natural gas, biomass,
nuclear, solar, wind, hydro, etc.) should be considered as valuing the variation of energy costs. In
general, the most costly source is displaced by cheaper ones, but there may be other power dispatch
rules. For this reason, the project promoter is recommended to explain and justify which particular
energy source/fuel is identified as the one displaced by the project.
As regards projects for which it is not possible to identify what specific electricity source/fuel will be
displaced by the increased project’s power production262, a shortcut method for the benefit evaluation
is to assess the variation of the energy opportunity cost against a counterfactual one in which the
average electricity production mix of the market is taken into account. Hence, the opportunity cost of
the substituted electricity would depend on the specific mix of sources/fuels used to produce it: the
average of opportunity costs of each source/fuel weighted by the share of electricity produced by each
source over the total production should be computed.
The opportunity cost of energy products and sources/fuels should be based on the long run marginal
cost (LRMC) of production, reflecting the total social cost incurred to produce an extra unit of
energy,263 plus the transport cost of the energy source from the place where it is produced to where it
is used, if applicable.
5.8.1.4 Market integration
This benefit is related to price alignment effects across places (for transmission) or time (for storage)
thanks to the capacity of exploiting differences in energy prices (e.g. for storage, base vs. peak loads for
electricity, summer vs. winter for gas). Market integration in particular reflects the potential benefits
of (cross-border) electricity transmission264 or energy storage investments265.
For example, a new cross-border electricity transmission project that increases grid transfer
capabilities266 between two bidding countries/areas allows generators in the lower-priced
country/area to export power to the higher-priced (import) area, thus reducing the total cost of the
electricity supply. This market effect turns into an economic effect when the project contributes to:
reducing network bottlenecks that restrict the access of generation to the full European
market;
providing a direct system connection to new, relatively low-cost, generation; or
facilitating increased competition between generators, reducing the price of electricity to final
consumers.
262 For example, projects entailing the substitution of imported electricity with self-produced electricity or, vice-versa, of self-produced
electricity with imported electricity.
263 For the definition of long run marginal cost, see Annex III.
264See ENTSO-E, Guideline for Cost-Benefit Analysis of Grid Development Projects and its future updates, November 2013. www.entsoe.eu
265 See ENTSOG, Cost-Benefit Analysis Methodology, November 2013. www.entsog.eu
266The grid transfer capability reflects the ability of the grid to transport electricity across a boundary, i.e. from one bidding area (area within
a country or a transmission system operator) to another, or at any other relevant cross-section of the same transmission corridor having the
effect of increasing this cross-border grid transfer capability.
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The benefit can be estimated as the reduction in generation costs associated with the grid transfer
capability variation created by the project.
In the gas sector, storage facilities allow more gas to be bought in summer, when it is readily available
and generally cheaper, and withdrawn in winter, when gas may be in short supply and additional
volumes will generally be very expensive. In this way no investments are needed to meet increased
demand during the winter period. The benefit is given by the difference between the value of
summer and winter gas, i.e. by the so-called 'value of swing'. In practice, the value of swing seen as a
difference in the average prices of gas between two different periods shall be multiplied by the
working volumes of the gas storage facility along each year of the time horizon of the analysis.
5.8.1.5 Improved efficiency
An improvement of the quality of the energy system can bring increased energy efficiency thanks to a
reduction of energy losses or a general improvement of the energy production or
transport/transmission/distribution technology, which allows lowering the unit cost of energy. The
benefit is enjoyed by the energy producer or distributor, and it could also eventually affect consumer
prices. The increase in energy efficiency is valued via the decrease of energy cost, incurred by the
energy producer/distributor to produce/distribute the same quantity of energy without the project.
Different to the financial analysis, the variation in costs is expressed in terms of the opportunity cost
(shadow price) of the energy fuel or source, instead of its actual market price.
The opportunity cost of the energy inputs pertinent to the specific project case reflects the loss to
society by the diversion of them from the best alternative use. It should be calculated, as usual, as the
long run marginal cost of production and transportation.
Note that the variation in the economic cost of the energy fuel/source due to increased efficiency does
not incorporate the full value of external costs (e.g. GHG emissions and pollution), which must be
separately assessed (see section below).
5.8.1.6 Variation of GHG and air pollutant emissions
The different stages of the life cycle of energy production plants, from their construction to their
operation and eventual dismantling, provoke the emission of greenhouse gases (GHGs), such as,
mainly, carbon dioxide (CO2), and, to a lesser extent, also methane and nitrous oxide (CH4 and N2O). In
principle, the Emissions Trading System (ETS) or other similar national systems rewarding energy
operators that produce low levels of GHGs and penalising those producing high GHGs are conceived to
internalise in the project’s account the climate change impact. The permit price ideally reflects the loss
of profits of the business whose production is crowded-out, i.e. the compensation (permit price) just
covers that loss of producer surplus. If so, the permit price reflects a real opportunity cost. According
to this perspective, the cost sustained or saved to buy emissions permits should already capture the
cost or benefit of the project on climate change.
However, more frequently, the price of allowances cannot be regarded as a reliable economic cost of
emissions since it is likely to be distorted, even to high extent, by various country-specific political
factors. Therefore, the recommended method for the evaluation of changes in GHG emissions is that of
replacing the permit price with unit economic costs.267
Other pollutant compounds are also produced by energy infrastructures, such as sulphur dioxide,
nitrogen oxides, non-methane volatile organic compounds as precursors of ozone, particulate matter,
mercury and other heavy metals, etc. Even if modern plants are equipped with scrubbers, filters and
combustion control equipment that limit the release of these unhealthy pollutants within legally
267 In fact, since there is a permit system, it is likely that total emissions of (some) greenhouse gases will remain unchanged because someone
else will purchase the released permits and hence emit more. Thus, the overall impact on environment becomes nil and shall not be included
in the economic analysis. This is true if a 'static' perspective is adopted. On the contrary, if a 'dynamic' perspective is adopted – entailing the
progressive reduction of total emissions in the long term in the EU – it makes sense to account for the reduction of emissions in economic
analysis too. The same logic applies for reduction of GHG emissions in consumption energy efficiency projects (section 5.8.2.3).
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specified levels defined under EU law, a residual is usually still emitted. This represents an external
cost that must be valued in the economic analysis. The same approach suggested for the valuation of
GHGs applies to pollutants.
The data needed to evaluate the economic costs of GHG emissions and pollution is given below in more
detail.
Changes in GHG emissions and pollutants. All types of power plants produce some GHGs
and pollutants during their life cycle (construction, operation, dismantling and fuel), including
those fed with renewable energy sources. Therefore, the amount of GHG emissions and
pollutants produced by both the project and the counterfactual case have to be quantified, in
order to determine the increase or decrease in emissions/pollutants’ volume. These have to be
consistent with the information provided in the Environmental Impact Assessment Report,
whenever required. If the volume of emissions associated with the energy project under
assessment is not available, relevant sectorial literature or previous studies can provide
benchmark values on emission factors. For example, the CASES database268 contains the
default volume of emissions released by different types of electricity and heat generation
plants and technologies. Also, the EMEP/EEA air pollutant emission inventory guidebook 2013
provides detailed literature on air pollutant for sectors including energy.
Unit economic costs. A monetary value reflecting the climate change or pollution cost of
different typologies of energy infrastructures must be attributed to the incremental volume of
pollutants produced by the project against the counterfactual value. A key reference study
providing the unit values of air pollutants produced by energy infrastructures in EU Member
States is Extern-E269 through its integrated environmental impact assessment model. Another
key reference is the NEEDS Integrated Project,270 which provides unit damage costs for air
pollutants from emerging electricity generation technologies. As for climate change, it is
suggested to use the values for the shadow price of CO2 as illustrated in section 2.9.9.
5.8.2 Energy-efficient consumption for buildings and productive systems
Projects involving a refurbishment of public and private buildings or works to improve the industrial
productive systems are associated with an increase of energy efficiency, either of the building or of the
production system, which is reflected in a reduction of energy consumption costs. Additionally,
insulation works and the improvement of heating systems in buildings could determine an increase in
the level of inner temperature and, thus, of comfort.
As with any other energy project, the projects aimed at improving consumption energy efficiency are
also characterised by environmental externalities, such as variations of GHG emissions and pollution
(e.g. in particular, airborne pollutants such as SO2, NOx, PM, VOC, mercury and other heavy metals,
etc.).
Table 5.5 illustrates the types of benefits discussed in this subsection.
Table 5.5 Typical benefits of energy-efficient consumption projects
Economic benefit Type of effect Examples of project
Refurbishment of public buildings
Refurbishment of flats and private buildings to improve their
Increase of consumption efficiency Direct energy characteristics
Measures for energy saving and efficiency improvement of
productive systems
268 http://www.casesdatabase.com
269 http://www.externe.info/
270 New Energy Externalities Developments for Sustainability, available at: http://www.needs-project.org/
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Refurbishment of public buildings
Increase of comfort Direct
Refurbishment of flats and private buildings to improve their
energy characteristics
Reduction of GHG emissions Externality All types of energy projects
Reduction of air pollutant
Externality All types of energy projects
emissions
Source: Authors
In the next sections, the methodologies used to assess the above-mentioned benefits are presented.
For the sake of clarity, Table 5.6 provides a synthetic overview of the evaluation methodologies,
including the counterfactual scenario to be assumed in order to evaluate incremental benefits.
Table 5.6 Methods to value the benefits of energy-efficient consumption projects
Economic benefit Valuation method Counterfactual
Increase of efficiency for Variation in economic costs of the
- Business as usual
consumption energy source/fuel
- Economic energy cost sustained to
Variation in economic costs of the maintain a 'thermal comfort' temperature
Increase of comfort
energy source/fuel through the without-the-project
technology/system of energy production
Reduction of GHG emissions Shadow price of GHG emissions - Business as usual
Reduction of air pollutant
Shadow price of air pollutants - Business as usual
emissions
Source: Authors
5.8.2.1 Increase of efficiency for consumption
Refurbishment investment projects to improve the energy performance of both public or private
buildings (both domestic and business facilities) generally involve insulation works to facades and
roofs, the renewal of windows and an improvement to heating systems, and the installation of own-
energy generation appliances from renewable energy sources The typical effect that these projects
produce is an increase in energy efficiency for consumption. Projects aimed at improving the energy
characteristics of productive systems are also expected to generate an increase in energy efficiency.
Unlike the energy-efficiency improvement to infrastructures for energy production or
transport/transmission/distribution, the benefit here occurs on the energy consumption side; yet the
methodology to estimate such a benefit is the same.
The benefit is valued via the decrease of energy cost incurred when attaining the same final useful
effect as in the without-the-project scenario. The cost reduction should not be expressed at market
prices, but by considering the opportunity cost of the avoided energy input i.e. the fuel saved due to
the increased efficiency of the building’s heating system or the industry’s energy management system
in gas or electricity or oil products. Their respective conversion factor should then apply to the
project’s specific energy input; the saved costs compared to the counterfactual scenario would
represent the project’s benefit.
5.8.2.2 Increase of comfort
In some cases, besides the reduction of unit costs of energy consumption, interventions aimed at
improving the energy characteristics of buildings could also determine an increase of comfort for
users, caused by the higher temperature reached inside buildings. Higher temperatures can be reached
because, due to the reduction of unit energy costs, consumers decide to increase the temperature level
in the premises.
If this additional comfort benefit is expected, the methodology presented in the previous paragraph,
focusing on valuing the reduction of unit cost of energy consumption, should be revised and the
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method presented here should be applied. In other words, when both an increase of comfort and a
reduction of energy unit costs are expected, these benefits have to be valued together.
The suggested approach consists of evaluating the savings of energy consumption costs (expressed as
the opportunity cost of energy) achieved by the project against a counterfactual case, in which the
energy consumption is assumed to be such that the 'standard' comfort temperature is ensured in the
building. Hence, the only difference compared with the method to value the reduction of unit energy
costs concerns the selection of the counterfactual scenario.
Alternatively, the benefit can be captured by the expected increase in property values (hedonic price
method). In such cases, however, care should be taken to avoid any double counting. The increase of
sales and rental prices of properties already includes any cost savings from improved energy efficiency
and, in some cases, other aspects such as renewed facades, etc.
The perceived thermal comfort in buildings is country-specific and indications about the minimum or
average temperature in public and private buildings for ensuring adequate thermal comfort should be
provided by national official documents and guidelines. In general, the standards for warmth are
higher than the minimum temperatures recommended by the World Health Organisation, which are
18 °C for healthy people and 20 °C for the sick, disabled, very old or very young.
Some practical examples illustrating how increased energy efficiency in buildings should be valued, in
case the projects allow for either a reduction of unit energy cost only or a reduction of unit costs and
an increase of temperature, are presented in the box in the next section.
5.8.2.3 Reduction of GHGs and pollutant emissions
Projects in the sector of buildings' energy efficiency could also bring external benefits, such as a
reduction of GHGs and pollutant emissions, due to the renovation works reducing heat dispersion and
the amount of energy consumption. The economic value of a change in emission of CO 2, or other
external environmental costs, such as SO2, NO2 and particulate matter, have to be estimated following
the same methodology described for the external cost of energy production or
transport/transmission/distribution projects.
VALUATION OF INCREASED ENERGY EFFICIENCY IN BUILDINGS: SOME EXAMPLES
Case 1: reduction of unit costs of energy consumption
This case regards a project involving insulation works and the replacement of the heating system, which allows
reduced energy-consumption costs to keep the temperature inside the building at the same level as in the
without-the-project scenario. It is assumed that an energy bill of 1 000 is annually paid by the owner of the non-
renovated building, which corresponds to a temperature of 18 °C. After the project’s implementation, the energy
efficiency of the building increases and this is reflected in a decrease of annual energy costs (to 900) that is
required to maintain the same inner temperature. The financial analysis records a decrease in operating cost
amounting to 100. In the economic analysis, the opportunity cost of energy should be considered, by applying a
conversion factor to the cost saving. This is assumed to be here 1.1 (because emission costs are internalised).
Thus, the project’s benefit would amount to:
Benefit = (1 000 ∗ 1.1) – (900 ∗ 1.1) = 110
This value expresses the benefit of saving energy fuel, valued at its opportunity cost, without affecting comfort.
Positive results would also be obtained at temperatures other than 18 °C, whenever a reduction of energy cost is
recorded to keep the temperature constant.
Case 2: reduction of unit costs of energy consumption and increase of comfort
Taking the same without-the-project scenario as in case 1, i.e. a temperature before the renovation works of
18 °C, it is now assumed that the project leads to an increase of the inner temperature to the thermal comfort
level, assumed to be 22 °C, and at the same time a decrease of energy costs, from 1 000 to 900. The financial
analysis would report a saving of 100 at market prices. The economic analysis, instead, should capture both the
benefit of the cost saving and the increase of comfort associated with an increase of temperature. To this
purpose, it is estimated that, under the counterfactual without-the-project scenario, the thermal comfort of 22 °C
\218
would be reached only by raising the energy costs to 1 200. Then the benefit would be as follows:
Benefit = (1 200 ∗ 1.1) – (900 ∗ 1.1) = 330
Actual Energy cost Economic
Actual
temperature Annual energy cost Annual energy cost savings at benefit a
temperature
without the without the project with the project market shadow
with the project
project prices prices
Case 1 18 °C 18 °C 1,000 900 100 110
Case 2 18 °C 22 °C 1,200 900 300 330
5.9 Risk assessment
In the sensitivity analysis, CBA results should be tested for changes in the following variables (where
relevant for the project):
incremental energy demand;
number of years necessary for the realisation of the infrastructure;
investment costs (as disaggregated as possible);
operation costs (as disaggregated as possible);
maintenance costs;
market price or opportunity cost of energy sources and products (either for the financial or the
economic analysis);
energy mix displaced by the project;
energy saved by the project;
estimated willingness-to-pay for energy consumption;
estimated willingness-to-pay for increased energy reliability of security of supply;
gross value added, if used to estimate the cost of non-served energy;
assumed economic value and/or quantities of GHG emissions and pollutants produced;
value of life considered for the valuation of the risk of accidents.
Via the sensitivity analysis, critical variables can be identified. On this basis, a fully-fledged (or at least
qualitative) risk assessment must be carried out, typically by assessing the risks presented in the
following table.
Table 5.7 Typical risks in energy projects
Stage Risk
- Changes of environmental requirements
- Changes of economic instruments (e.g. renewable energy source support
Regulatory schemes, EU ETS design)
- Changes in energy policy (e.g. concerning the discontinuation of certain types of
energy sources and fuels)
- Demand shortfalls
- Unexpected evolution of prices of different competing fuels
Demand
- Inadequate analysis of climatic conditions affecting the energy demand for heating
and/or cooling
- Inadequate site surveys and investigation
- Inadequate design cost estimates
Design
- Innovation in energy production/transmission or energy storage technology making
the one in the project obsolete
\219
- Building or other permits
Administrative
- Utility approvals
- Land costs higher than predicted
Land acquisition - Higher costs for the acquisition of rights of way
- Procedural delays
Procurement - Procedural delays
- Project cost overruns
- Delays due to unexpected technical difficulties (such as the installation of undersea
pipelines or underground power cables)
Construction - Delays in complementary works outside the project promoter’s control (e.g. cross-
border projects)
- Flooding, landslides, etc.
- Accidents
- Maintenance and repair costs that are higher than predicted
- Accumulation of technical breakdowns
Operation
- Long out-of-service time for accident or external causes (earthquake, flood,
sabotage, etc.)
- Changes in the tariff system
Financial - Changes in the system of incentives
- Inadequate estimate of energy price trends
Source: Adapte from Annex III to the Implementing Regulation on application form and CBA methodology.
\220
Case Study – Natural gas transmission
pipeline
I Project description
The project consists of the construction of a new gas-transmission pipeline between the two gas nodes
of Alpha and Beta. The designed maximum transmission capacity is 700 000 m3/h, or
16.8 million m3/day. The investment includes the following main components:
a 175 km-long steel pipeline with a diameter of 700 mm (DN 700), to be operated at a pressure
of 8.4 MPa;
two intermediate pressure-reduction and metering stations located in Lambda and Theta;
the installation of fibre-optic communication system.
The project promoter is the national transmission system operator (TSO).
An existing DN 500 pipeline currently transmits gas between Alpha and Beta. The pipeline was built
30 years ago and is operated at full capacity. Following the increase in demand for gas transmission
services in the country and the ongoing expansion of the regional underground gas storage (UGS)
facilities, the existing pipeline is no longer able to meet incremental demand and ensure reliable
supplies throughout the year.271
II Project objectives
The project objectives are well aligned with the main goals of priority axis X: 'Sustainable, secure and
competitive energy' of the Operational Programme 'Infrastructure'. In particular, the investment will
contribute to the following OP indicators.
OP Project
Indicator
2023 target (% of OP target)
Length of new gas transmission pipelines (km) 500 175 (35 %)
3
Additional gas transmission capacity (Mm /day) 40 16.8 (42 %)
The construction of the new Alpha-Beta gas pipeline will allow the transmission of additional volumes
of gas to/from the expanded UGS facilities in Gamma and Delta, as well as from a new entry point to
the network, the liquefied natural gas (LNG) terminal currently under construction in Epsilon.
Therefore, energy security will be improved by ensuring the continuity of gas supplies during both
peak and off-peak periods to the distribution network and to the large industrial customers directly
connected to the transmission network.
Also, the increased penetration of natural gas in the country should in the medium to longer term
contribute to the replacement of coal and oil products as energy sources. As gas is a relatively clean
fossil fuel, the project will indirectly bring about a reduction in emissions of greenhouse gases (GHG)
and airborne pollutants, thereby contributing to the sustainable growth dimension of the Europe 2020
strategy.
271
The promoter expects that after the new pipeline comes on line, the old one may still be used if needed, but at a reduced pressure and
capacity.
\221
III Demand analysis
Natural gas is the third most important source of energy in the country, after coal and oil, accounting
for approximately 20 % of total primary energy supply. The total consumption of natural gas was
18 Gm3 in 2013, with peak demand in the transmission system reaching 83 million m3/day on
6 February.
According to the scenarios and forecasts presented in the 'National Energy Strategy to 2030', the
demand for gas transmission across the country is expected to develop as shown in the table below.
National gas demand 2015 2020 2025 2030
3
Annual consumption (Gm /y) 19.3 25.2 26.5 27.8
3
Peak demand (Mm /day) 92 120 126 132
As regards demand in the project area, an 'open season' procedure was launched to test the market
interest in additional transmission capacity. Compared to a counterfactual scenario without the
project – where supply is constrained at the maximum capacity of the existing DN 500 pipeline, the
promoter forecasts that the following additional gas volumes are expected to be transmitted as a
result of the construction of the new Alpha-Beta pipeline.
Demand – project area 2035
2017* 2020 2025 2030
Incremental gas flows onwards
3 428
Mm /year 332 348 374 401
3 16.9
PJ/year (at 39.50 MJ/m ) 13.1 13.7 14.8 15.8
* Planned first year of operation
According to the promoter’s analysis of the regional gas market, 50 % of the incremental gas supplies
associated with the project will be delivered to industrial customers, 35 % to the power sector and the
remaining 15 % to the residential/commercial sector throughout the regional gas distribution system.
Although the market shares may to some extent vary over the project time horizon, it was assumed for
simplicity in the economic analysis that they remain fixed.
IV Option analysis
The option analysis prepared in the Feasibility Study assesses the following two sets of options:
Choice of pipeline alignment. Three different alternative alignments were considered. The
project option is selected based on a least cost-path analysis coupled with qualitative analysis
of environmental and technical dimensions. The selected pipeline alignment between Alpha
and Beta has the following characteristics:
o the lowest 'levelised unit transmission cost'272, with a value of EUR 7.40/1 000 m3,
o the least interference with natural areas, including Natura 2000,
o it allows the project to be implemented in stages.
Technical specifications of the pipeline. Further technical analyses were performed to
optimise the selection of the pipeline diameter, material and wall thickness. According to the
simulations performed by the TSO, a 700 mm diameter is the most efficient solution for the
target capacity of 700 000 m3/h, with L485MB steel pipes and a wall thickness of 17.5 mm.
272
The 'levelised cost' is a life-cycle cost indicator, commonly used to gauge long-run unit costs. It is calculated here as the ratio of (i) the
present value of the total (capital and operating) costs over the entire project reference period to (ii) the present value of the total amount of
gas transmitted by the pipeline over the same time horizon.
\222
V Project costs and revenues of the selected option
A breakdown of the investment cost, in constant prices, for the selected project alternative is
presented in the following table.
Project investment cost (millions of EUR) Total cost Ineligible cost Eligible cost
Planning/design fees 4.5 4.2 0.3
273
Land purchase 7.6 6.6 1.0
Building and construction 62.2 - 62.2
Plant and machinery or equipment 63.5 - 63.5
274
Contingencies - - -
Price adjustment (if applicable) - - -
Publicity 0.1 - 0.1
Supervision during construction implementation 2.5 - 2.5
Technical assistance 0.4 - 0.4
Sub-TOTAL 140.8 10.8 130.0
(VAT) 31.0 31.0 -
TOTAL 171.8 41.8 130.0
In addition to the costs above, the promoter will have to fund EUR 2.6 million of interest during
construction (IDC). Not all costs are eligible for EU support, as some expenditure was already incurred
before the beginning of the programming period. The eligible cost amounts to EUR 130 million.
The unit investment cost of around EUR 210/km/cm2 is in line with that of other similar projects
recently completed by the promoter in the context of its current Network Development Plan.275
Operating and maintenance (O&M) costs are budgeted at around 2 % of project assets, based on the
promoter’s cost data on other similar sections of the transmission network. O&M costs include
expenses related to gas compression and gas losses, repair and maintenance, insurance and overheads.
No asset replacement costs are forecast over the 25-year reference period.
The natural gas transmission activity is regulated by the National Energy Authority so as to allow the
TSO to recover the justified costs and earn a return on the Regulatory Asset Base (RAB) based on the
contracted transmission capacity and the expected transmitted volumes. Transmission charging in the
country is based on an 'entry-exit' system: tariffs are paid at entry and exit points to/from the
transmission system and are independent of location and distance. The gas transmission tariffs consist
of two main elements: a fixed 'capacity fee', in EUR/m3/h, and a variable 'commodity fee', in EUR/m3.
The capacity fee varies depending on the service supplied (e.g. firm vs. interruptible capacity, annual
vs. short-term capacity).
As regards the project incremental revenue, this is, for simplicity, calculated in the financial analysis
based on the average transmission charge of EUR 25/1 000 m3, multiplied by the incremental gas
flows associated with the investment (as identified in the demand analysis). According to the
estimates of the TSO, thanks to the EU grant, the tariffs for gas transmission will not have to be
increased in real terms, given that the share of project assets co-financed by the EU contribution is
excluded from the RAB on which the return-on-capital component of the transmission tariffs is
calculated.
273
Also includes costs related to acquiring rights of way.
274
Technical contingencies are not included as the investment was budgeted on the basis of 'reference class forecasting' – see Annex VIII of
the Guide. This approach was, in this case, feasible as the promoter, the national TSO, has access to a fairly large sample of cost data for this
typology of investment. Also, no price adjustment (for inflation) was included in the cost estimate, although potentially eligible for co-
financing.
275
The unit investment cost is calculated here by dividing the total investment cost by both the pipeline length and the area of the section, so
as to also take into account the pipe size (diameter).
\223
VI Financial and economic analysis
The analysis is performed using a 25-year reference period, including three years of investment phase
and 22 years of operations. As the average economic life of the project assets is assumed to be 25
years, a residual value is considered in the last year of the time horizon, equal to the discounted value
of the net cash flows in the remaining years of life.276 The financial and economic analyses are carried
out in constant prices. A 4 % discount rate in real terms is used in the financial calculations, while a
5 % social discount rate is used in the economic analysis, in line with the EU-wide benchmark set by
the European Commission.
Financial analysis
The project is subject to the rules on State aid and was therefore notified to the European Commission
(Directorate-General for Competition) and subsequently authorised. To ensure proportionality of the
aid, it was decided that the EU grant would be determined based on the project’s 'funding gap', in line
with the applicable Guidelines on State aid for environmental protection and energy277.
Based on the costs and revenue assumptions described in the section above, the estimated 'funding
gap rate' is 30 % (discounted net revenue = EUR 90.9 million, discounted investment cost =
EUR 129.8 million, see calculation further below). The EU contribution for the project is in this case
fixed at EUR 33.2 million, by multiplying the eligible cost shown in section V above (EUR 130 million)
by the 'funding gap rate' (30 %) and by the co-financing rate of the relevant priority axis of the OP
(85 %). The remainder of the investment is funded by the promoter with equity and debt, as shown in
the following table.
Financing Sources millions of EUR % share
EU grant 33.2 23.1 %
Promoter’s equity 60.2 42.0 %
Loan 50.0 34.9 %
278
Total funding 143.4 100.0 %
The loan has a maturity of 15 years. Based on the loan pricing conditions and inflation expectations, an
average interest rate of 3 % in real terms is used in the financial analysis to estimate the loan cash
flows. The loan is to be disbursed in the first two years of the investment phase. The principal
repayment would start in the first year of operation, while a total of EUR 2.6 million of interest charges
is paid during construction.
The following profitability indicators (before-tax, real) are calculated – see cash flow tables below:
Return on investment (before EU grant): FNPV(C) = EUR -39.0 million
FRR(C) = 1.2 %
Return on national capital (after EU grant): FNPV(K) = EUR -6.5 million
FRR(K) = 3.2 %
The project is expected to be financially sustainable, as cumulative net cash flows are never negative
over the project reference period.
276
For simplicity, the net cash flows of the three remaining life years are assumed to be equal to that of the last year of the reference period.
In the economic analysis, the net economic benefit is used instead of the financial cash flow. Accordingly, the financial residual value is
estimated at EUR 21 million, while the economic one is forecast at EUR 119 million.
277 Note that, although the project generates net revenue, Article 61 of Regulation (EU) No 1303/2013 was not applied because an individual
verification of financing needs had already been carried out in accordance with the applicable State aid rules – see Article 61(8)(c) of
Regulation (EU) No 1303/2013.
278
Total funding exceeds the total investment cost as it also covers interest during construction equal to EUR 2.6 million. In addition,
EUR 31 million of VAT is also pre-financed by the promoter (the VAT is recoverable).
\224
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 20 25
EU GRANT
Construction Operation
Calculation of Discounted Investment Cost (DIC) NPV 4 %
Investment cost M EUR 129.8 33.2 63.6 44.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
DISCOUNTED INVESTMENT COST (DIC) M EUR 129.8 33.2 63.6 44.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Calculation of Discounted Net Revenues (DNR) NPV 4 %
Incremental gas flows Mm3 4,861.8 0.0 0.0 0.0 332.0 337.0 342.0 348.0 353.0 358.0 364.0 369.0 374.0 380.0 385.0 390.0 417.0 428.0
Average transmission tariff EUR/th.m3 321.2 0.0 0.0 0.0 25.0 25.0 25.0 25.0 25.0 25.0 25.0 25.0 25.0 25.0 25.0 25.0 25.0 25.0
Revenue M EUR 121.5 0.0 0.0 0.0 8.3 8.4 8.6 8.7 8.8 9.0 9.1 9.2 9.4 9.5 9.6 9.8 10.4 10.7
O&M costs M EUR -38.5 0.0 0.0 0.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0
Residual value of investments M EUR 7.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 21.0
DISCOUNTED NET REVENUES (DNR) M EUR 90.9 0.0 0.0 0.0 5.3 5.4 5.6 5.7 5.8 6.0 6.1 6.2 6.4 6.5 6.6 6.8 7.4 28.7
ELIGIBLE COST (EC): M EUR 130.0
FUNDING GAP RATE (FGR = (DIC - DNR) / DIC): 30.0%
CO-FINANCING RATE OF PRIORITY AXIS (CF): 85.0%
EU GRANT ( = EC x FGR x CF): M EUR 33.2
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 20 25
FRR(C)
Construction Operation
Return on Investment NPV 4 %
Investment cost M EUR -129.8 -33.2 -63.6 -44.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Revenues M EUR 121.5 0.0 0.0 0.0 8.3 8.4 8.6 8.7 8.8 9.0 9.1 9.2 9.4 9.5 9.6 9.8 10.4 10.7
O&M costs M EUR -38.5 0.0 0.0 0.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0
Residual value of investments M EUR 7.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 21.0
Project cash-flow M EUR -39.0 -33.2 -63.6 -44.0 5.3 5.4 5.6 5.7 5.8 6.0 6.1 6.2 6.4 6.5 6.6 6.8 7.4 28.7
FRR(C) - before EU grant 1.2%
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 20 25
FRR(K)
Construction Operation
Loan Balance
Beginning balance M EUR 0.0 25.4 50.0 50.0 47.3 44.5 41.6 38.7 35.7 32.6 29.4 26.1 22.7 19.2 15.6 0.0 0.0
Loan disbursements M EUR 25.4 24.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Interest payments M EUR 0.0 1.1 1.5 1.4 1.3 1.2 1.2 1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.0 0.0
Principal repayments M EUR 0.0 0.0 0.0 2.7 2.8 2.9 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 0.0 0.0
Ending balance M EUR 25.4 50.0 50.0 47.3 44.5 41.6 38.7 35.7 32.6 29.4 26.1 22.7 19.2 15.6 11.9 0.0 0.0
National Financing Sources
National public (grant) M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
National private (equity) M EUR 0.0 25.1 35.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Return on National Capital NPV 4 %
National public (grant) M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
National private (equity) M EUR -54.4 0.0 -25.1 -35.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Interest payments M EUR -10.7 0.0 -1.1 -1.5 -1.4 -1.3 -1.2 -1.2 -1.1 -1.0 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 0.0 0.0
Principal repayments M EUR -32.2 0.0 0.0 0.0 -2.7 -2.8 -2.9 -2.9 -3.0 -3.1 -3.2 -3.3 -3.4 -3.5 -3.6 -3.7 0.0 0.0
O&M costs M EUR -38.5 0.0 0.0 0.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0
Revenues M EUR 121.5 0.0 0.0 0.0 8.3 8.4 8.6 8.7 8.8 9.0 9.1 9.2 9.4 9.5 9.6 9.8 10.4 10.7
Residual value of investments M EUR 7.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 21.0
National cash-flow M EUR -6.5 0.0 -26.2 -36.6 1.2 1.3 1.5 1.6 1.7 1.9 2.0 2.1 2.3 2.4 2.5 2.7 7.4 28.7
FRR(K) - after EU grant 3.2%
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 20 25
FINANCIAL SUSTAINABILITY
Construction Operation
Financial sustainability
National public (grant) M EUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
National private (equity) M EUR 0.0 25.1 35.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
EU grant M EUR 7.8 15.0 10.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Loan disbursement M EUR 25.4 24.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Revenues M EUR 0.0 0.0 0.0 8.3 8.4 8.6 8.7 8.8 9.0 9.1 9.2 9.4 9.5 9.6 9.8 10.4 10.7
Total cash inflows M EUR 33.2 64.7 45.5 8.3 8.4 8.6 8.7 8.8 9.0 9.1 9.2 9.4 9.5 9.6 9.8 10.4 10.7
Investment cost M EUR -33.2 -63.6 -44.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M costs M EUR 0.0 0.0 0.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0
Interest payments M EUR 0.0 -1.1 -1.5 -1.4 -1.3 -1.2 -1.2 -1.1 -1.0 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 0.0 0.0
Principal repayments M EUR 0.0 0.0 0.0 -2.7 -2.8 -2.9 -2.9 -3.0 -3.1 -3.2 -3.3 -3.4 -3.5 -3.6 -3.7 0.0 0.0
Corporate Income Tax M EUR 0.0 0.0 0.0 0.0 0.0 0.0 -0.1 -0.2 -0.2 -0.3 -0.4 -0.5 -0.6 -0.7 -0.8 -1.2 -1.3
Total cash outflows M EUR -33.2 -64.7 -45.5 -7.1 -7.1 -7.1 -7.2 -7.3 -7.3 -7.4 -7.5 -7.6 -7.7 -7.8 -7.9 -4.2 -4.3
Net cash-flow M EUR 0.0 0.0 0.0 1.2 1.3 1.5 1.5 1.5 1.7 1.7 1.7 1.8 1.8 1.8 1.9 6.2 6.4
Cumulated net cash-flow M EUR 0.0 0.0 0.0 1.2 2.5 4.0 5.5 7.0 8.7 10.4 12.1 13.8 15.6 17.5 19.3 37.2 69.2
Economic analysis
The economic analysis investigates the impact on society of the additional volumes of natural gas
made available by the project to the different economic sectors. The project's economic costs are those
used in the financial analysis. Unemployment is relatively low in the region and the procurement of
materials, works and engineering services is to follow an open, competitive procedure in line with the
applicable public procurement rules. Therefore, the project cost estimates used in the financial
analysis are, in this case, deemed to adequately reflect social opportunity costs.
The change in social welfare associated with the investment is valued as the difference between
society’s maximum willingness-to-pay (WTP) for the incremental gas and its opportunity cost. The
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maximum WTP is proxied by the costs for the purchase (at border price),279 transportation and use of
the next best alternative fuels in the power, industry and residential/commercial sectors, including the
externalities related to CO2 emissions from combustion. The economic cost of the incremental gas is
valued at border price plus the cost of transportation to the relevant market plus the shadow cost for
the CO2 emissions from combustion.280 As the consumers’ WTP for natural gas is valued at the burner-
tip, adjustments are made, where feasible, to allow for possible differences in efficiency and costs
associated with the use of other competing fuels.281
The alternative fuels are in this case assumed to be coal in the power sector, gasoil in the
residential/commercial sector and a mix (50/50) of coal and fuel oil in the industrial sector. Where
possible, differences in efficiency of the technologies using different fuels were taken into account to
determine the amount of alternative fuels to be displaced by natural gas.
The European border prices of natural gas, coal, fuel oil and gasoil were estimated by the promoter
over the project reference period, based on the fuel cost projections to 2035, which were developed by
the International Energy Agency in its latest World Energy Outlook. Based on these assumptions, the
following economic cost and benefits streams were forecast over the reference period.
►►◄◄ ►►◄◄
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 20 25
ERR
Construction Operation
Socio-economic costs NPV 5 %
Project investment cost M EUR -92.2 -33.2 -63.6 -44.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 119.0
Project O&M costs M EUR -34.1 0.0 0.0 0.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0
Total economic costs M EUR -126.3 -33.2 -63.6 -44.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 116.0
Socio-economic benefits NPV 5 %
B1. Value of gas to the power sector M EUR 742.2 0.0 0.0 0.0 50.8 52.4 54.0 55.8 57.4 58.9 60.7 62.3 64.0 65.9 67.6 69.3 78.5 85.1
B1a. Avoided coal costs (border price + transportation) M EUR 314.8 0.0 0.0 0.0 23.8 24.3 24.8 25.4 25.8 26.2 26.7 27.1 27.5 28.0 28.4 28.8 31.0 32.0
B1b. Avoided CO2 emissions from coal M EUR 357.4 0.0 0.0 0.0 21.6 22.6 23.6 24.7 25.8 26.9 28.1 29.2 30.4 31.7 32.9 34.1 40.7 46.1
B1c. Δ capital and O&M costs (coal Vs. gas power plants) M EUR 69.9 0.0 0.0 0.0 5.4 5.5 5.6 5.7 5.8 5.8 5.9 6.0 6.1 6.2 6.3 6.4 6.8 7.0
B2. Value of gas to industry M EUR 1,138.7 0.0 0.0 0.0 80.7 82.8 84.9 87.5 89.6 91.9 94.3 96.5 98.8 101.3 103.5 105.7 117.8 125.3
B2a. Avoided coal costs (border price + transportation) M EUR 161.6 0.0 0.0 0.0 12.2 12.5 12.7 13.0 13.2 13.5 13.7 13.9 14.1 14.4 14.6 14.8 15.9 16.4
B2b. Avoided CO2 emissions from coal M EUR 183.6 0.0 0.0 0.0 11.1 11.6 12.1 12.7 13.3 13.8 14.4 15.0 15.6 16.3 16.9 17.5 20.9 23.7
B2c. Avoided fuel oil costs (border price + transportation) M EUR 643.5 0.0 0.0 0.0 48.3 49.2 50.2 51.4 52.3 53.3 54.4 55.3 56.3 57.3 58.2 59.1 63.9 65.9
B2d. Avoided CO2 emissions from fuel oil M EUR 150.1 0.0 0.0 0.0 9.1 9.5 9.9 10.4 10.8 11.3 11.8 12.3 12.8 13.3 13.8 14.3 17.1 19.3
B3. Value of gas to the residential/commercial sector M EUR 611.3 0.0 0.0 0.0 44.6 45.6 46.7 48.0 48.9 50.0 51.2 52.1 53.2 54.4 55.4 56.5 62.0 64.9
B3a. Avoided gasoil costs (border price + transportation) M EUR 525.3 0.0 0.0 0.0 39.4 40.2 41.0 42.0 42.7 43.5 44.4 45.1 45.9 46.8 47.5 48.3 52.2 53.8
B3b. Avoided CO2 emissions from gasoil M EUR 86.0 0.0 0.0 0.0 5.2 5.4 5.7 6.0 6.2 6.5 6.8 7.0 7.3 7.6 7.9 8.2 9.8 11.1
C1. Economic cost of incremental gas M EUR -2,087.9 0.0 0.0 0.0 -147.7 -151.7 -155.8 -160.4 -164.4 -168.5 -173.0 -177.1 -181.3 -185.8 -189.9 -194.0 -216.2 -228.6
C1a. Cost of incremental gas (border price + transportation) M EUR -1,654.0 0.0 0.0 0.0 -121.5 -124.3 -127.1 -130.4 -133.1 -135.8 -138.9 -141.6 -144.4 -147.4 -150.0 -152.6 -166.8 -172.7
C1b. CO2 emissions from incremental gas M EUR -433.9 0.0 0.0 0.0 -26.2 -27.4 -28.7 -30.0 -31.3 -32.7 -34.1 -35.5 -36.9 -38.4 -39.9 -41.4 -49.4 -55.9
Total economic benefits (B1+B2+B3-C1) M EUR 404.3 0.0 0.0 0.0 28.4 29.1 29.8 30.9 31.5 32.3 33.2 33.8 34.7 35.8 36.6 37.5 42.1 46.7
Net benefits (ENPV) M EUR 278.0 -33.2 -63.6 -44.0 25.4 26.1 26.8 27.9 28.5 29.3 30.2 30.8 31.7 32.8 33.6 34.5 39.1 162.7
ERR 17.7%
B/C RATIO 3.20
With an estimated 17 % economic rate of return (ERR), a positive economic net present value of
EUR 278 million and a benefit/cost ratio equal to 3.2, the construction of the new Alpha-Beta gas
pipeline is expected to increase social welfare. Therefore, it is worth supporting with a contribution
from the EU. The step-by-step monetisation of the project benefits is elucidated in the following table
(for year 4, i.e. the first year of operations).
279
As fuels are traded internationally, the use of border prices instead of national market prices allows excluding taxation and other market
distortions so as to better reflect the opportunity cost of these resources in the economic analysis. The relevant borders here are assumed to
be North-West Europe (Amsterdam/Rotterdam/Antwerp area) for oil products and coal, and the German border for pipeline gas.
280
Changes in emissions of airborne pollutants (e.g. SOx and NOx) between natural gas and the alternative fuels assumed could have also been
included in the analysis based on unit emission factors and the shadow cost of emissions (e.g. from ExternE studies). On the other hand,
methane emissions due to losses from the new gas pipeline were not included as a negative externality of the project, as their impact was
considered to be insignificant compared to the impact of CO 2 emissions from gas combustion.
281
See, for example, the monetisation of the benefits for the power sector, which takes into account differences in efficiency and in capital,
and operating costs between gas and coal plants.
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Value
Monetisation of project benefits282 (Year 4)*
in million EUR
B1. Value of gas to the power sector 50.8
B1a. Avoided coal costs (border price + transportation)
According to the demand analysis, incremental gas to the power sector in the first year of operation is 13.1 PJ *
35 % = 4.6 PJ. This can displace 4.6*57 %/41 % = 6.4 PJ or 0.255 Mt of coal (at calorific value of 25 GJ/ton), where 23.8
57 % and 41 % are the assumed efficiency of gas-fired and coal-fired power plants respectively. In that year, the
border price of coal (CIF, North-West Europe) is forecast by the promoter at EUR 83.2/t, with transport cost
estimated at EUR 10/t. The avoided coal costs are then equal to (83.2+10)*0.255 = EUR 23.8 million.
B1b. Avoided CO2 emissions from coal
With an emission factor of 95.09 tCO2eq/TJ283 of coal and the shadow price of CO2 estimated for that year at 21.6
EUR 36/ton, the avoided CO2 emissions are valued at 6.4*(95.09*1000)*36 = EUR 21.6 million.
B1c. Differences in capital and O&M costs (coal vs. gas power plants)
A gas-fired power plant (e.g. a combined-cycle gas turbine) has higher fuel costs but lower unit capital and 5.4
operating costs compared to a coal-fired power plant. According to the promoter’s calculation, the difference would
be EUR 0.85/GJ of coal, so the net savings to the sector would be (0.85*10^6)*6.4 = EUR 5.4 million.
B2. Value of gas to the industrial sector 80.7
B2a. Avoided coal costs (border price + transportation)
According to the demand analysis, incremental gas to the industrial sector in the first year of operation is 13.1 PJ *
50 % = 6.56 PJ. Assuming the alternative fuels in the sector are a mix (50/50) of coal and fuel oil, the additional gas 12.2
supplied by the project can displace 6.56*50 % = 3.28 PJ or 0.131 Mt of coal. With the border price of coal forecast
at EUR 83.2/t and transport cost estimated at EUR 10/t, the avoided coal costs to industry would be equal to
(83.2+10)*0.131 = EUR 12.2 million.
B2b. Avoided CO2 emissions from coal
With an emission factor of 95.09 tCO2eq/TJ of coal and the shadow price of CO2 estimated for that year at 11.1
EUR 36/ton, the avoided CO2 emissions are valued at 3.28*(95.09*1 000)*36 = EUR 11.1 million.
B2c. Avoided fuel oil costs (border price + transportation)
In industry, natural gas can also displace 6.56*50 % = 3.28 PJ or 0.076 Mt of fuel oil (calorific value of 43 GJ/ton). 48.3
The forecast border price (cif, North-West Europe) is EUR 573/t, with transportation to the project market at
EUR 60/t. Avoided fuel oil costs to industry are (573+60)*0.076 = EUR 48.3 million.
B2d. Avoided CO2 emissions from fuel oil
9.1
Unit factor is 77.65 tCO2eq/TJ of fuel oil. Emissions are then valued at 3.28*(77.65*1000)*36 = EUR 9.1 million.
B3. Value of gas to the residential/commercial sector 44.6
B3a. Avoided gasoil costs (border price + transportation)
According to the demand analysis, in the residential/commercial sector gas can displace 13.1*15 % = 1.97 PJ or 39.4
0.046 Mt of gasoil (at 43.08 GJ/t). Border price (cif, North-West Europe) and transportation costs are forecast
respectively at EUR 783/t and EUR 80/t. Avoided costs are (783+80)*0.046 = EUR 39.4 million.
B3b. Avoided CO2 emissions from gasoil
5.2
Unit factor is 74.35 tCO2eq/TJ of gasoil, so emissions are valued at 1.97*(74.35*1000)*36 = EUR 5.2 million.
C1. Economic cost of incremental gas 147.7
C1a. Cost of incremental gas (border price + transportation)
The price of pipeline imports of natural gas at EU borders for the first year of project operation is forecast at
EUR 8.2/GJ. Transportation costs are assumed to be EUR 0.50/GJ to power and industry and EUR 4.50/GJ to the 121.5
residential/commercial sector. Total economic cost is then equal to (8.2+0.50*85 %+4.50*15 %)*13.1 =
EUR 121.5 million.
C1b. CO2 emissions from incremental gas
26.2
Unit factor is 56.15 tCO2eq/TJ of gas. Emissions are then valued at 13.1*(56.15*1 000)*36 = EUR 26.2 million.
Total economic benefit (B1+B2+B3-C1) 28.4
* First year of operations
Possible discrepancies in the calculations shown in this table are due to a rounding of the figures reported from the CBA spreadsheet.
282
Unit emission factors of greenhouse gases are taken from the Guidelines for National Greenhouse Gas Inventories of the Intergovernmental
283
Panel on Climate Change (IPCC).
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VII Risk Assessment
Sensitivity analysis
The sensitivity analysis assesses the robustness of the CBA conclusions to possible changes in the key
project variables. As regards the economic benefits, the analysis is carried out using disaggregated
variables (i.e. demand and prices are assessed separately) to better identify possible critical variables.
The estimated elasticity of the ENPV and FNPV(C) with respect to the different project variables is
shown in the table below.284
Variable ENPV elasticity FNPV(C) elasticity
Investment cost -0.46 % -3.33 %
O&M costs -0.12 % -0.99 %
Incremental gas flows 1.45 % 3.41 %
CO2 shadow price 1.23 % -
Fuel costs (border prices) 0.08 % -
The incremental gas flow transmitted by the new pipeline is the most critical variable for the
socioeconomic viability. However, the 'switching value' is relatively high: the ENPV would drop to zero
if the volume of the incremental gas flows decrease on average by 69 % over the entire reference
period, which does not appear to be very likely. Also, a pessimistic scenario is analysed, where
investment costs would be 30 % higher than currently budgeted, while demand and the shadow price
of CO2 would be 20 % lower than in the assumed base-case scenario. Under this pessimistic scenario,
the ENPV would still be positive (EUR 104 million), with a 9 % ERR. Therefore, it can be concluded that
the project should also remain economically viable under reasonably adverse conditions.
As regards the financial profitability of the investment, investment cost and incremental demand are
the most critical variables. The FNPV(C) (which is estimated to be negative) would become positive in
case the savings in investment costs exceeded 30 % or incremental gas throughput increased by more
than 29 % on average over the reference period. The values indicate that the investment would most
likely have a negative NPV, so supporting the project with an EU grant appears justified.
Risk analysis
Based on the results of the sensitivity analysis and taking into account uncertainties related to aspects
not directly reflected in the CBA calculations, a risk matrix was prepared in order to identify possible
risk prevention and mitigation measures.
284
The elasticity is defined as the percentage change in the NPV indicator for a +1 % change in the variable.
\228
Probability* Severity* Risk level* Residual
Risk description Risk prevention / mitigation measures
(P) (S) (=P*S) risk
Demand & supply risks
Projected incremental gas flows based on the
Significant shortfall in results of 'open season' procedures. Current
demand for B III Moderate economic downturn and protracted low price of Low
transmission capacity EU carbon allowances are also factored in.
Function in charge: promoter.
Project implementation units of different
projects to liaise with, and under the
Supply risks:
supervision of, the Ministry of Economy.
implementation delays
Incremental project demand can also be met by
of new LNG terminal C III Moderate Moderate
flexibility in current long-term gas import
and expansions of UGS
contract (where maximum annual quantity is
facilities
reportedly 115 % of annual contract quantity).
Function in charge: Ministry of Economy.
Financial risks
Cost budget based on 'reference class
forecasting' to correct possible optimism bias.
Investment cost overrun C III Moderate Publication of contract notices in the Official Low
Journal of the EU to ensure wider competition.
Function in charge: promoter.
Involve JASPERS technical assistance early on
in the project cycle. Pre-financing of EU grant to
Late availability of EU
B II Low be arranged by the promoter. Function in Low
grant co-financing
charge: Ministry of Regional Development and
promoter.
Gas transmission activity is regulated to ensure
cost recovery. Tariffs are adjusted by the
Weak profitability to
B I Low regulator to give an adequate financial return to Low
jeopardise debt service
the operator in the medium term. Function in
charge: National Energy Authority.
Implementation risks
Problems with land The project is part of the list of national strategic
purchase and infrastructure enshrined in the new Energy Act
B II Low Low
acquisition of rights of for which facilitated land rights procedures are
way foreseen.
Difficult ground conditions (e.g. river crossing,
Unforeseen technical wetland, forest) to be analysed at concept
B II Low Low
problems during works stage. Final pipeline alignment to minimise
difficulties. Function in charge: promoter.
Promoter’s procurement division to be
Delays related to supported by specialised technical assistance.
extension of tender C III Moderate Appropriate time contingencies to be factored in Low
procedures into the project schedule. Function in charge:
promoter.
Environmental risks
'Horizontal directional drilling' technique to be
adopted to prevent open excavations
Negative impacts on
generating significant impacts; also,
protected areas (Natura A II Low Low
construction works to be banned during the
2000)
fauna’s reproductive season. Function in
charge: contractor.
Use of L485MB steel pipes with wall thickness
Unexpected methane
B II Low up to 17.5mm and cathodic protection against Low
emissions from pipes
corrosion. Function in charge: contractor.
* Evaluation scale: Probability: A. Very unlikely; B. Unlikely; C. About as likely as not; D. Likely; E. Very likely.
Severity: I. No effect; II. Minor; III. Moderate; IV. Critical; V. Catastrophic.
Risk level: Low; Moderate; High; Unacceptable.
The results of the sensitivity and risk analyses indicate that the project overall risk level is low to
moderate. Also, the measures put in place to prevent the occurrence of the identified risks and/or
mitigate their adverse impact should result in a lower residual risk. The probability of the project
failing to attain its targeted objective at a reasonable cost can be considered to be marginal. Therefore,
the residual project risks are deemed to be fully acceptable and probabilistic risk analysis was not
carried out in this particular case study. In the practice, however, it is common that large energy
investments undergo a probabilistic risk analysis.
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6. Broadband
6.1 Introduction
The EU policy framework for broadband investments is the Digital Agenda for Europe and the
Industrial Policy Update, which includes a new initiative for digital entrepreneurship as part of the
Entrepreneurship 2020 Action Plan. While there is no standardised definition of broadband285, the
Digital Agenda foresees the following by 2020:
all Europeans have access to much higher Internet speeds of above 30 Mbps;
50 % or more of European households subscribe to Internet connections above 100 Mbps.
All-encompassing nation- and Europe-wide access to (high-speed) broadband infrastructure is
considered essential for a digital economy to contribute towards stimulating social and economic
cohesion and as such is one of the priorities of the cohesion policy. Major projects will support large
investments in broadband in all Member States and regions, and in particular rural areas, by pursuing
investment priority 2a286. The priority is on next generation access networks (NGA), i.e. networks that
are capable of delivering broadband access services with enhanced characteristics (i.e. with speeds
above 30 Mbps)287.
Investments may concern both the passive (e.g. cable, optical fibre, antenna, etc.) and the active (e.g.
router, hub, switch, etc.) components of the infrastructure, including fixed and wireless access
solutions. They usually address the extension or upgrade of the regional backbone/backhaul network
and/or the area networks, but can also address the last-mile connections. Compliance with the EU
State aid rules normally needs to be formally assessed, except for certain categories of aid that are
presumed to be compatible with the internal market, provided certain conditions are met, pursuant to
the General Block Exemtion Regulation288 (GBER).
A selective list of policy documents for the broadband sector is provided in the box below.
THE EU POLICY FRAMEWORK
Strategies
The Digital Agenda for Europe
The Digital Agenda for Europe – Driving European growth digitally (Mid-term Review)
Telecom Single Market Connecting Europe Facility
European Broadband: investing in digitally driven growth [COM(2010) 472]
Better access for rural areas to modern ICT [COM(2009) 103 final] and Commission Staff working document
[SEC(2009) 254 of 3.3.2009]
Future networks and the Internet [COM(2008) 594 final]
Bridging the Broadband Gap [COM(2006) 129]
Mobile broadband services [COM(2004) 447 final]
285 See Holznagel et al. (2010), p. 15.
286 See Draft Thematic Guidance Fiche for desk officers enhancing access to and use and quality of ICT high-speed broadband roll-out, Version
2, 13/03/2014.
Available at: http://ec.europa.eu/regional_policy/sources/docgener/informat/2014/thematic_guidance_fiche_ict_broadband.pdf
287In particular, the existence of national or regional next generation networks (NGN) plans, which take account of regional actions in order
to reach the EU high-speed Internet access targets, is one of the thematic ex ante conditionalities foreseen for the period 2014-2020. The
conditionality is applicable if a Member State is planning to allocate ERDF funding to extend broadband deployment and the roll-out of high-
speed networks and support the adoption of future and emerging technologies and networks for the digital economy (Article 5(2)(a) of the
ERDF Regulation). It should be noted that NGN/NGA represents more than just higher bandwidth; it also includes several architectural and
service-related characteristics. See ITU-T Recommendation Y.2001 (12/2004) – General overview of NGN (ITU 2014).
288 See: http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32014R0651&from=EN
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The eEurope 2005 action plan: an information society for everyone [COM(2002) 263 final]
A European Information Society for growth and employment [COM(2005) 229 final]
Guidelines
Guide to High Speed Broadband Investment
EU Guidelines for the application of State aid rules in relation to the rapid deployment of broadband networks
Thematic Guidance Fiche for desk officers enhancing access to and use and quality of ICT high-speed broadband
roll-out
6.2 Description of the context
Broadband investments need to be seen within the greater context of a broadband plan consistent
with the priorities set within the Digital Growth Strategy developed, for instance, within the
national/regional Smart Specialisation Strategy.
Both the NGN plan and the Digital Growth Strategy constitute ex-ante conditionalities289
(preconditions to be met) enabling the use of EU funds.
Good planning of specific broadband investment that pursues the goals a broadband plan requires the
context analysis of the following elements:
relevant socio-economic issues that characterise the territorial context and affect demand,
e.g.: ageing, education, income, level of information and communication technologies (ICT)
training/skills, employment status, etc.;
technical conditions, including a mapping of current broadband coverage, topography,
population density, technological alternatives, prospective up-take rates and bandwidth
availability;
market: broadband investments shall primarily come from commercial investors, so it is
important that public funds are used in this sector to complement and not to substitute the
investments of market players. The mapping of future private investments over the next three
years constitute a key element to avoid the displacement of market investment. User
requirements need to consider the future development of public and private services over the
medium/long term.
Table 6.1 Presentation of the context: Broadband sector
Information
- National and regional GDP growth
- Income disposal
Socioeconomic- - Demographic projections
trend - Employment status
- Level of education
- Level of ICT training and skills
- Reference to the EU Digital Agenda
Political, - Reference to national/regional digital growth strategic policy framework
institutional and
- Reference to national/regional next generation networks plans
regulatory factors
- Availability of regional incentives for future investments into broadband infrastructure
- Topography
Technical - Users' density
conditions
- Presence of existing Infrastructure
289 See Guidance on Ex ante Conditionalities:
http://ec.europa.eu/regional_policy/sources/docgener/informat/2014/eac_guidance_esif_part2_en.pdf
\231
- Level and quality of existing services
- Bandwidth availability
- Current market size and future investment
- Competition level (market share of operators)
Market conditions
- Users’ needs (market trends, services offered, future requirements, etc.)
- Users’ habits and behaviours regarding Internet usage
Source: Authors
6.3 Definition of objectives
The main objective of broadband investments is to promote sustainable socioeconomic development
and growth through an increased coverage and take-up of broadband services. Intervention is needed
when there is no sufficient presence or access to adequate infrastructure, resulting in high prices
and/or low quality of services.
In more detail, broadband investments generally aim at:
improving access to Internet and e-services for households;
developing new professional opportunities for enterprises;
driving innovation (new and existing businesses);
ensuring equity of access to broadband in rural areas and reducing the digital divide;
increasing productivity for businesses through the use of ICT;
strengthening development and growth of business start-ups;
promoting efficiency of the public services through e-government;
facilitating the provision of reliable e-health, e-education, e-learning, e-commerce, e-culture
services;
strengthening competition in the telecommunication services market.
Project objectives should be always linked to the specific objectives of the EU Digital Agenda and the
national/regional ICT policy framework strategy. When feasible, it is also recommended to specify the
contribution of the project to the achievement of the OP priorities through the use of indicators290.
6.4 Project identification
The focus of broadband investments concerns:
network coverage expansions: e.g. projects deploying fibre or cable access networks, as well
as high speed mobile access and related support infrastructures to areas that are currently not
covered by any access;
network quality improvements: if the existing quality network is poor and therefore
impeding service uptake, the deployment of a higher quality is likely to increase the uptake
rate in the area. For instance, in the case of fibre-to-the-home (FTTH) deployment in areas
with an existing copper (DSL) network, the FTTH deployments enable much higher broadband
access speeds that, in turn, increase the penetration rate of those digital services that require a
high bandwidth (e.g. video streaming).
As already mentioned, investments in broadband may comprise both the passive infrastructure and
290For instance, the following indicators can be used: length of regional fibre optical network; number of Network Management Centres;
percentage of enterprises with a basic/NGA broadband access; percentage of households with a basic/NGA broadband access; percentage of
households living in rural areas served by broadband networks; number of broadband subscriptions per 100 people, etc. It is recommended
that the impact of the project is clearly presented by providing information on the indicators before and after the project.
\232
the active components of the network (technology). Passive components291 consist of the physical
infrastructure over which information is transmitted, including dark fibre292. Active components
include the technological equipment needed to encode the information into signals to be sent over the
infrastructure (e.g. transponders, routers and switches, control and management servers).
The technical identification of the project should include a description of:
the implementation area. This should be supported by maps, indicating the target areas for the
intervention and their characteristics (level of presence of actual and targeted broadband
transmission speeds and services);
the network architecture and design, the topology assumptions and the reasons behind it (e.g.
the geography of the region, the services finally delivered etc.);
the design standards and specifications of each project element (e.g. network management
centre, fibre optic networks, backbone/distribution nodes, etc.).
The project promoter should specify how the identified technical solution will meet the requirements
to reuse, where possible, existing infrastructures, provide open access to both the physical
infrastructure and the active equipment and respect the principle of technology neutrality. In
particular, the outcome of the mapping exercise with the identification of black, grey and white areas
shall be presented vis-à-vis the scope and location of the project. In addition, to identify a broadband
project also means to define its institutional set-up, as briefly illustrated in the box below.
INSTITUTIONAL FRAMEWORK
According to the latest update of the Commission's Guide on High Speed Broadband Investment, four levels of
involvement of the public sector can be identified, in terms of engagement into investment models to take vis-à-
vis the market, the citizens and the businesses in the region.
Public-run municipal network model: the public authority (PA) builds and operates a broadband network
(mostly the physical, more rarely the active infrastructure) , which may take place in collaboration with the
market (PPP) but the ownership of the network remains with the PA. It is sometimes referred to as public
design, build and operate (DBO).
Private-run municipal network model: the PA procures the building, but keeps the ownership of of the
passive infrastructure, but leaves the operation of the active layer to a private actor that provides wholesale
services to retail providers, under an Indefeasible Right of Use (IRU) of, for example, 20 years. This is sometimes
referred to as public outsourcing/concession.
Community broadband model: the broadband investment is done as a private initiative, in a so-called bottom-
up approach. The role of the PA in this case is to provide support in the form of co-financing, but also of
counselling, right-of-way (RoW) granting, regulation and coordination with other infrastructure deployments
and access to points of presence, such as major public data centres.
Operator Subsidy(Gap-funding) model: the public authority (PA) does not intervene, limiting itself to
subsidising one market actor (typically a major telecom operator) to upgrade its infrastructure. Both passive and
active infrastructure are owned and managed by the operator. Risks associated with building new infrastructure
and attracting sufficient customers are borne by the recipients of the funding.
Source: European Commission (2014)
291This can be a twisted pair of copper wires (traditionally used for telephony), coaxial cables (traditionally used for TV distribution within
buildings), optical fibres (traditionally used for the transmission of a very large amount of data over very long distances), or antenna towers
and sites if the transmission is done wirelessly (e.g. for radio and satellite transmission).
292The term 'dark fibre' was originally used when referring to the potential network capacity of telecommunication infrastructure, but now
also refers to the increasingly common practice of leasing fibre optic cables from a network service provider, or, generally, to the fibre
installations not owned or controlled by traditional carriers. The complement to dark fibre is 'lit fibre', referring to the active use of a
(rented) 'dark; fibre infrastructure by a network or service provider.
\233
Finally, the implementation of any broadband investment should be justified against a set of feasible
alternative options allowing the achievement of the same objective (see section 6.6).
6.5 Demand analysis
The role of demand analysis under the conditions of the European Digital Agenda targets (Europe-
wide and nationwide, all-encompassing, full coverage for all inhabitants; minimum thresholds, strict
time line for achievement, etc.) is quite different if compared to other infrastructure projects.
Demand analysis is required in order to find out the level of current and prospective demand and to
identify which areas and to what extent these requirements can be satisfied through normal market
dynamics and those areas which will require some form of public intervention.
Often the question is not whether broadband infrastructure investments should serve those
underserved regions that display high actual demand first and those with low demand later (or the
other way round), but what actual and foreseeable demand can be discovered in order to make sound
decisions for project financing. In this context, the results of demand analysis do not lead to a ranking
of projects because eventually all underserved areas and regions will have to be covered by
broadband, according to the European policy priorities regarding broadband and Digital Europe.
In this context it must also be kept in mind that European broadband infrastructure investments do
not only aim at meeting the current existing demand, but at satisfying and possibly also creating
potential demand for services in the future. Consultation with users both in the public and private
domains and consideration about technological development and future needs are key aspects to
properly size the requirement over the long term, taking into account relevant EU and national aims in
the field.
That said, demand forecasts, in terms of expected number of users, are certainly essential to further
calculate both the financial and the economic performances of the project (see below).
6.5.1 Factors influencing demand
When forecasting demand for broadband investments, different inter-related factors affecting the
take-up rate of digital services need to be taken into account (see Table 6.2).
Table 6.2 Factors influencing demand
Factors
Socioeconomic conditions: higher standards of living and growing economies are usually associated
with a higher use of the Internet.
Digital education and skills: the higher the digital skills of the population, the more likely the use of
digital services.
Geographical and demographic features: in urban/metropolitan areas there is already a wide use of
digital services because of favourable market conditions, while the majority of unmet demand for
broadband in Europe is in rural areas. In this regard, local communities can play a very important role in
Demand driving demand for new services and in some cases providing part of the investment needed.
issues
Demand aggregation: aggregation of demand for digital services from the side of public authorities
(local government, libraries, hospitals, schools, etc.) and the local community (business associations, civil
communities/ groups, etc.), generally helps to make the project financially stable over the medium-to-
long terms as it secures the use of the infrastructure for the provision of these services.
Affordability and users’ willingness to pay: capacity and service availability have to consider users’
293
(households, businesses and public institutions) actual ability/willingness to pay for them.
Perspective for future demand crated by new infrastructure: structural developments.
Supply Capacity and quality of the network/services provided: the take-up of digital services depend on: the
293 These consideration may lead to an adaptation of the investment model as well as the adoption of demand-support measures to reverse
the vicious circle between low skills, low education low income and low availability/affordability of service
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issues infrastructure endowment that can be used for delivery of digital services, the limitations in the quality of
services currently provided or services not available in the region, and the level of access to data
transmission services. This should equally be compared with estimated future bandwidth and service
requirements.
Competition level: price-sensitive consumers' willingness to pay is directly related to competition: the
higher the number of operators existing in the market and the variety of services offered, the lower the
prices. Additionally, it is recommended that the tariffs paid by the end-user are analysed to see if they
would allow for the profit margin that last-mile operators normally expect on the market. Different models
294
of investment allow different degrees of competition.
Source: Authors
6.5.2 Hypotheses, methods and input data
The demand analysis should present both current and future demand. The analysis of the current
demand should be based on the inventory of the existing demand potential as well as market
conditions by mapping the broadband network. This requires presenting the type, scope and quality of
existing infrastructure and relative services provided, as well as having a pricing policy in place and
future plans.
Given the existing market situation, and considering all the factors affecting demand, forecasts should
be estimated by referring to national or international benchmarks of digital service take-up.
The methodology adopted to forecast demand should be clearly explained, with particular reference to
the assumptions made on the following:
expected growth rate during the project horizon;
degree to which one can expect supply to create demand, as is often the case in infrastructure
provisioning;
future types of services and an analysis of the required bandwidth;
anticipated structure of revenues generated by the project;
anticipated level of tariffs and the role of the national regulator as regards price control;
anticipated market share.
6.5.3 Output of the forecasting exercise
Broadband investments can either aim to provide wholesale services only, retail services (e.g. in the
case of a public administration network), or a combination of both. In the first case, demand analysis
should be conducted from the point of view of the project users (last-mile network operators); in the
second case, from the point of view of the final users. Given that demand from last-mile network
operators depends on the demand from final users, such as individuals, businesses and public
institutions, it is however common to analyse demand at both levels.
The demand analysis results should therefore be presented in terms of increased coverage, take-up
and use (intensity, quality) of digital services, preferably distinguished between the following:
commercial operators that will obtain wholesale access to the infrastructure and types and
features of the digital services provided;
number of people and households benefiting from the project: in total, as a percentage of the
national/regional population, and broken down by municipality (and/or other administrative
units) and by urban/rural areas;
businesses and public institutions making use of digital services.
294 The selection of the model will have to fit the situation on the ground in terms of the socio-economic issues affecting demand (of
demography, income, education, ICT training, etc.). See also Guide to high speed broadband investment.
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6.6 Option analysis
As regards the relevance of option analysis in the context of European broadband projects, the initial
remarks in section 6.5 (demand analysis) apply here as well. Option analysis should be carried out in
order to help design the best-suited broadband projects in a given regional environment. However, the
results of option analysis do not decide on the provision of broadband as such. Option analysis might
further underscore the necessity of broadband deployment, but cannot lead to 'no broadband',
because the European policy goals demand full broadband coverage in the European Union.
The baseline for the option analysis, a scenario without the project, should be discussed by presenting
any adverse impact, if quantified as relevant. A scenario without the project usually concerns an option
without any infrastructure at all. Alternative options should be analysed and compared with each
other on the basis of the following dimensions:
strategic: compliance and fulfilment of EU objectives and national strategies; socioeconomic
impact (who would benefit from the project); scope of intervention (phasing, division into sub-
projects, etc.);
technological: adequate number of different technological alternatives, such as network
architecture, dimensioning and topology, hierarchical structure, network transmission
medium and protocol, construction of optical cabling or wireless routes, ducting and cable
type, in order to maximise the coverage, up-take and sustainability (future-proofed) of the
network solution;
institutional: showing the advantages and disadvantages of alternative investment models for
the implementation, indicating which one is best suited for the project promoter, such as in-
house management; outsourcing; setting up a special purpose vehicle; separation of
construction and operation of the network into two tenders (concession); design-build-
operate-transfer (DBOT);
environmental: observance of environmental quality standards, the potential effect on Natura
2000 sites, etc.;
financial and economic: project costs and revenues/benefits;
societal: enabling more and better participation in social life
Once all the feasible options are shortlisted, it is recommended that a simplified CBA is undertaken to
rank and select the most optimal solution.
6.7 Financial analysis
6.7.1 Investment and operating costs
In the case of broadband investments, the passive components of the network (i.e. the permanent
physical infrastructure such as copper, fibre and coaxial cable networks, antenna towers) are typically
characterised by high capital expenditure, low operational expenditure and limited economies of scale.
Furthermore, physical infrastructure is highly local, hard to duplicate and inherently subject to
regulation because it most often constitutes a natural monopoly. On the other hand, active equipment
(i.e. the application technology installed on the passive infrastructural components, such as routers,
transponders, switches, control and management servers, gateways, access points) is characterised by
high operational expenditure, economies of scale, and is subject to selective regulation (e.g. regulated,
mandatory bit-stream access, which is becoming more and more important in the context of NGA/NGN
but must, in most cases, be implemented in active components).
In terms of sources of financing, broadband investments are suitable for delivery through either
financial instruments or grants, or a combination of both. In the former case, leverage resources and
increased efficiency and effectiveness gains, due to the revolving nature of funds, can give access to a
wider spectrum of financial tools for policy delivery and attract private sector support (and financing)
to public policy objectives (see box).
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THE CONNECTING EUROPE FACILITY
In the new programming period the Connecting Europe Facility will devote a limited budget to financing high
speed broadband infrastructure. The Connecting Europe facility will operate through a credit enhancement
mechanism providing better conditions to loans, guarantees and project bonds issued by the European
Investment Bank. The logic behind it is risk sharing, whereby the European Commission and the EIB will join
forces to take more risk and improve the credit rating of specific projects that otherwise would find it more
difficult to attract investors.
The Connecting Europe Facility is open to contributions from Member States and regions, in particular from
European Structural and Investment Funds. Such contributions, which must be geographically ring-fenced (i.e.
could only be spent in a MS / region making the contribution) would benefit from the high leverage effect of CEF
financial instruments and thus could help maximize the impact of public intervention.
Projections of O&M costs shall be split in fixed and variable costs. Typical operating cost items of
broadband investments include Internet traffic and interconnection charges, energy consumption,
maintenance costs, and technical and administrative personnel costs. In the case of projects where
costs are divided between the owner of the infrastructure and the operator, such a division shall be
clearly described.
6.7.2 Revenue projections
In most cases, EU-funded broadband projects are designed as wholesale projects. Therefore, revenues
should be calculated based on the services provided by the wholesale operator and not against the
tariff paid by the final users. Typical sources of revenues are:
data transmission service fees;
network connection fees;
colocation/equipment hosting services fees;
infrastructure rental revenues, including dark fibre rental, ducts rental, masts rental.
The above categories of revenues should be based on a clearly explained tariff policy. It should, in
particular, indicate:
the benchmarked prices (in case no national benchmark exist, provide international
comparison), and
if the national regulator has been consulted on the tariff setting methodology.
6.8 Economic analysis
6.8.1 Typical benefits and valuation methods
The economic literature suggests that a large number of socioeconomic benefits are associated with
broadband coverage and the upgrade of digital services. Examples of benefits that are usually
identified are: time savings for Internet browsing, getting more people online, making best use of
network capacity, improving micropayment systems, extending the reach of smart solutions, reducing
the opportunity cost of providing goods and services via Internet, equity, ubiquity, improved
competition, cost savings for the public sector, etc. In particular, an increased use of e-commerce
services, especially in rural disadvantaged areas, is seen as a main driver towards economic growth
and reduction of territorial disparities and social exclusion. The availability of a state-of-the-art
infrastructure is also a key element to improve the attractiveness and competitiveness of an area and
its overall competitive edge and can help in reversing the trend of relocation of economic activity and
depopulation.
Table 6.3 provides a standardisation of types of economic benefits and relative methodologies for
evaluation, which are discussed in more detail in the following sections.
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While the economic benefits of broadband investment are widely reported and discussed in the
literature, problems nevertheless exist in finding a single, widely accepted methodology to value these
benefits in monetary terms, owing to the complexity of the industry. As a consequence, for the main
types of benefit (i.e. increased take-up of digital services and improved quality of digital service, see
Table 6.3), different evaluation methods are proposed because all are considered acceptable from a
methodological point of view.
In addition, while the macroeconomic link between broadband investments and GDP growth is widely
recognised and acknowledged, a microeconomic approach to benefit estimation is adopted in this
guide. With this approach, the effects on national or regional growth are excluded and replaced by
microeconomic estimates as detailed in this chapter. This approach differs from and should not be
used together with the methodology for calculating the economic return of coverage expansions
looking at the effect on GDP growth.
Table 6.3 Benefit evaluation of broadband investments
Economic benefit Type Valuation method(s)
- Stated preferences
Increased take-up of digital services for households - Travel cost
Direct effect
and businesses - Benefit transfer
- Local gross value added
- Stated preferences
Improved quality of digital service for households - Travel cost
Direct effect
and businesses - Benefit transfer
- Local gross value added
Improved provision of digital services for public
Direct effect - Cost saving
administrations
Source: Authors
A typical (important) benefit that is not included in the list, largely because of a financial nature, are
the operational efficiency gains (O&M cost savings) that can be the sole aim of some business-driven
network/service modernisation projects. While these projects may lead in some cases to some quality
improvements, and also reduced CO2 emissions, the basic rationale typically lies in reducing the
operation and maintenance costs of the provider. A typical example is the modernisation of Global
System for Mobile Communication (GSM) and third-generation cell-phone technology (3G) networks,
where the trend is to move from having separate network equipment for GSM and 3G networks to a
single radio access network design, whereby these same services are provisioned by much less active
equipment, resulting in lower O&M costs. Therefore the benefit estimation of operational efficiency
gains, to a large extent, coincides with the results of the financial analysis.
Finally, in respect to energy consumption, broadband investments are expected to have a neutral or
positive impact on CO2 emissions. This comes from the consideration that although ICT networks
consume energy, one expects that they will significantly contribute to a reduction of travelling, thereby
offsetting the consumption at a minimum. However, it is not yet clear as to what extent new and
powerful means of information and communication also generate new demand for the transportation
of goods and people with the implication of increased consumption of transport energy. The research
base today is not mature enough to measure the net effect of broadband investment on the
environment and it is therefore recommended, until relevant studies become available, to discuss this
benefit in qualitative terms rather than value its impact in the CBA model.
6.8.2 Increased take-up of digital services for households and businesses
This benefit arises with respect to projects aimed at both network coverage expansion and network
quality improvements.
The methodology for benefit evaluation relies on the concept of WTP for the new users (distinguished
between households and businesses) of the digital services.
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In the case of competitive markets, the price actually paid by households and businesses for
subscription to broadband access (usually in the form of a fixed charge per month) can be used as a
proxy of WTP. In other words, the amount paid in subscription charges provides an indication of the
value of digital services to consumers. The operational step for the benefit evaluation consists of
multiplying the number of households and businesses additionally connected by the expected average
revenue per user over the time horizon of the analysis295. Then, in the case of investments designed as
wholesale services only, a pro rata factor should be applied to take into account the fact that only part
of the benefit to end-users can be attributed to the project.
For the majority of broadband projects, and specifically in the case of regulated prices, it is however
reasonable to assume that market prices do not adequately reflect users’ WTP, which is expected to be
greater than the price actually paid because of the perceived productivity gains (time and cost savings)
to customers. In such cases, the WTP must be recalculated together with the following methods, which
are mutually exclusive for the same group of users296:
stated preferences, for instance contingent evaluation or discrete choice experiments, to
directly measure the value attributed by users to the applications used over the connection.
The disadvantages of this method are that it can be time and resource consuming;
travel cost: time and cost (e.g. fuel) savings deriving from the use of online services, which
replace the need to physically reach a given facility, are estimated on an annual basis in order
to incorporate the productivity gains achieved by customers. Although very practical, this
method requires a large amount of data that cannot always be available to the project
promoter;
benefit transfer: the result calculated in previous studies is transferred to the project context.
In this respect, however, careful judgement is required to determine whether the results are
transferable or what adjustments need to be made to make them useful for the project under
assessment;
the local gross value added can be used to estimate the benefit of additional broadband take-
up by businesses. The empirical literature suggests, in fact, that productivity gains arise from
broadband take-up. The method for benefit evaluation consists of estimating the percentage
rise in the expected GVA per employee as a result of the project. While being supported by
empirical evidence, this approach is, however, subject to the potential benefit of being double-
counted due to the difficulty of measuring the share of GVA rise that can be attributed to the
project only.
In light of the constraints each method presents, the benefit transfer seems the most practical, and less
costly, approach. It is therefore suggested to always refer to the international literature as a data
source where estimated values can be transferred. For a review of selected studies see the reference
section.
6.8.3 Improved quality of digital services for households and businesses
The quality of the service is improved when the broadband network is upgraded to enable a higher
performance (i.e. higher download speeds, reliability and upload speeds). Typical project examples are
the deployment of backbones, such as submarine cables to replace satellites, for instance providing
backhaul traffic, or the deployment of fibre-based fixed lines or long-term evolution (LTE)/fourth
generation (4G) access networks to improve the DSL or 3G-based broadband access networks. The
main benefit is produced when the technological upgrade is such that there is a substantial shift from
basic to NGA broadband.
295 To compute the number of households and businesses additionally connected, the expected take-up rate must be multiplied by the
number of households and businesses covered and passed by the infrastructure. It must be kept in mind that this is a pure quantitative
calculation leaving out information on the intensity and the quality of use.
296 Clearly, the methods mentioned above should be treated as an alternative only if addressing the same category of users. On the contrary, if
one method (e.g. benefit transfer) is used to evaluate the increase coverage benefit on e.g. households, this can be combined with other
methods (e.g. gross value added to evaluate the increase coverage benefit on businesses).
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As regards assessing the economic return while the service to be enabled already exists on some level,
the benefit needs to be corresponded with the increased quality. This calls for a service-based
approach, i.e. to investigate the additional possibilities enabled by higher quality services and their
productivity gains. Productivity gains may consist, for example, of , lower consumers’ costs in using
specific applications, the cost saving for an organisation adopting cloud-based services or the Internet
of Things, or the increase in value-added in product design or service delivery, or a more targeted
advertising provided by applications based on the exploitation of big-data, social networks, etc.
The methodological framework to estimate the WTP for improved quality of digital services follows
the same logic as depicted in the previous section. However, care should be taken to ensure that the
benefit assessment is carried out in incremental terms so as to measure what consumers would be
additionally willing to pay for improvement. In other words, in case of using end-user prices as a
proxy, the net benefit is given by the difference between future broadband subscriptions over the
current ones. Again, given the difficulties of empirically estimating a WTP that incorporates
productivity gains to customers, it is suggested that the benefit estimation is based on data taken from
the international literature and, when applicable, adapted to the project context, depending on the
project entity, location and scope.
6.8.4 Improved provision of digital services for public administrations
A project aimed at network/service coverage expansion or quality improvements can facilitate the
adoption of e-government services, leading to better public service provision and cost savings. For
example, the establishment of a fibre-based broadband network may see the government improve and
broaden the range of web services for which it is responsible.
The method for benefit evaluation consists of estimating the annual cost savings on the regional/local
government expenditure.
In this regard, if project-specific data is not available, the anticipated figure for e-government savings
could already be available within the country, probably in an e-government strategy. The benefit
realised by the project can therefore be derived as a percentage of the overall target estimated in the
region’s strategy. This can be estimated by taking into account the relative 'weight' of the project
within that strategy (e.g. on the basis of the share of total households affected by the project).
Recognising, however, that not all countries or regions have developed strategies or quantified the
savings, a possible means of estimating the project-specific e-government savings is proposed in
JASPERS 2013.297
In addition, these projects can facilitate the provision and use of e-services in the different sectors of
public expenditure, including health, education, culture, etc. In the context of the major projects, health
care is a key sector that is potentially affected. The main benefit from e-health relates to productivity
gains in service provision. These unfold when adopting digital applications that:
improve the capability of patient, clinical and practice management systems to support key
electronic information flows between care providers;
provide datasets that summarise a consumer’s key health data and their current state of
health, treatments and medications;
encourage the development of specific tools that improve the quality of clinical decision-
making and can reduce adverse events and duplicated treatment activities;
implementing electronic health records (EHRs), which provide consumers with access to their
own consolidated health information and provide care providers with a means of improving
the coordination of care.
Again, the method for benefit evaluation consists of estimating the annual cost savings on the
297Cost-benefit analysis framework for broadband connectivity projects. Available at JASPERS Network Platform:
http://www.jaspersnetwork.org/plugins/servlet/documentRepository/searchDocument?resourceType=JASPERS%20Working%20Papers
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regional/local health care budget.
6.9 Risk assessment
When carrying out the sensitivity analysis, it is recommended to test the following variables:
investment cost (as disaggregated as possible);
the anticipated time of usage/lifetime of infrastructure;
O&M costs (as disaggregated as possible);
expected demand for services;
anticipated level of tariffs from the national regulatory authority;
anticipated market share;
revenues from different categories of services (as disaggregated as possible);
unit WTP for households from increased broadband availability or quality or, alternatively,
value of time (as relevant);
unit WTP/ gross value added for businesses from increased broadband availability or quality;
e-government savings and e-health savings.
Through the sensitivity analysis the most critical variables can be identified. On this basis, detailed
qualitative risk assessment must be carried out, typically by assessing the risks presented in the
following table.
Table 6.4 Typical risks in broadband projects
Stage Risk
- Change of orientation of the strategic policy
Context and - Change in excepted behaviour of future private investors
Regulatory - Change in regulations in the retail market
- Unsuccessful State-aid application
- Lower than estimated service take-up from retail and/or wholesale providers
Demand - Low investments in last-mile network by service providers
- Low take-up by end-users from service providers
- Capital expenditure underestimation
Design
- Operational expenditure underestimation
Administrative - Risk of not obtaining required property rights
Procurement - Delays in project public procurement process
- Investment cost overruns
Construction
- Implementation delays
- Loss of key personnel during project operation
Operation
- Increase in O&M cost
- Insufficient committed funding on a national/regional level during the operational
Financial
phase
Source: Adapted from Annex III to the Implementing Regulation on application form and CBA methodology.
\241
Case Study – Broadband infrastructure
I Project description
The scope of the broadband project involves the construction of a fibre-based regional backbone and
distribution network infrastructure in a region with 5.25 million inhabitants that have a currently low
penetration of broadband services. The project will allow for an important expansion in the provision
of two categories of services to households and businesses (in particular SMEs): basic broadband and
next generation access (NGA)298. This will allow a considerable improvement to the speed and quality
of broadband services. The country’s telecommunication’s market is characterised by moderate
competition with broadband being accessed predominantly through traditional copper infrastructure,
mobile subscriptions (2G/3G) and cable connections (35 %; 30 % and 25 % respectively). Over 50 %
of broadband connections are offered at a speed of between 2 and 10 Mb/s and the share of high-
speed connections (at least 30 Mbps) is lower than the EU average.
The project promoter and the owner of the infrastructure is the regional government, which will
tender out the design, construction and operation of the network through a concession contract to a
private partner.
The infrastructure consists of both passive and active components. The main technical components
defined at a preliminary design stage comprise a fibre optic network with a total length of around
3 600 km, and a total of 180 network nodes, repartitioned between the backbone and distribution
network. To reduce the cost of the project and avoid duplications, it was already foreseen at
preliminary design level that the final design of the new infrastructure to be carried out by the selected
private partner shall incorporate (lease, e.g. indefeasible rights of use, for the project duration) already
existing telecommunication infrastructure belonging to operators active in the region.
The project promoter will ensure that retail providers have open and non-discriminatory access to the
infrastructure. Last-mile infrastructure is not part of the project. To confirm that sufficient demand
exists from last-mile operators, letters of intent have been signed with the majority of service
providers in the region.
II Project objectives
The project objectives are aligned with the goals of the Digital Agenda for Europe in terms of access to
basic broadband, next generation access and the country’s National Strategy for the Development of
the Information Society.
The general objective of the investment is to help to eliminate the digital divide related to the
availability of basic broadband in areas where this is currently not provided due to market failures,
and to lower the investment barrier for NGA services.
More specifically, the project aims at the following:
households in general: improving access to e-services (e-commerce, e-banking), better access
to information, development of new professional opportunities for skilled residents (e.g.
teleworking);
businesses: increasing productivity through the use of ICT (e.g. by a reduction of
transportation costs, etc.);
for government, facilitating the adoption of e-government services, leading to better service
and cost savings;
for the healthcare sector: facilitating the provision of faster and better tailored e-health
298 In accordance with the national broadband strategy, basic broadband is defined in this specific case as allowing for a minimum speed of
2 Mb/s, while in the case of NGA services the minimum speed is 30 Mb/s.
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services.
Other sectors that can benefit from the project in the medium term are the energy sector (smart grids,
controlling decentralised energy generation) and the transport sector (multimodal traffic planning).
As a direct result of the project, it is estimated that NGA broadband coverage will increase from 63 %
to 75 % of the population (additionally connecting 630 000 inhabitants or 300 000 households). In
addition, fixed basic broadband coverage will increase from 80 % to 96 % of the region’s population
(additionally connecting 840 000 inhabitants or 400 000 households).
The project is well aligned with the goals of the relevant priority axis of the operational programme
concerned. Specifically, the project will contribute to the following OP indicators:
Result indicator OP Project
2023 target (% of OP target)
Additional households with basic broadband access 450 000 400 000 (89 %)
Additional households with NGA broadband access 400 000 300 000 (75 %)
Additional enterprises with NGA broadband access 60 000 40 000 (66 %)
Output indicator OP Project
2023 target (% of OP target)
Increase in the length of fibre optical network 5 000 3 600 (72 %)
III Demand analysis
In order to define the areas of intervention, the region was mapped according to the existing level of
competition for relevant broadband services, based on a method described in the State aid guidelines
for broadband projects299.
The demographic and socioeconomic characteristics of the selected areas were then benchmarked
with historic market developments in comparable areas at national and European level, to produce
detailed forecasts of project demand. The following main factors were analysed in detail: i) potential
increase in take-up of bandwidth; ii) market share potential of project operator; iii) assessment of
demand for existing and new e-services from households and businesses (accompanied by estimations
of associated bandwidth requirements).
The resulting prognoses were consulted with service providers active in the market, both wholesalers
and potential last-mile operators, for a reality check of the initial assumptions. After some final
corrections, the following uptake rates were estimated for the end-users of the infrastructure.
Cat. Broadband uptake in project area (%) 2018 2023 2028 2033
Households
I New uptake of basic broadband 20 25 25 25
II New uptake of NGA (where previously zero) 15 35 53 55
300
III Upgrade from basic broadband to NGA 15 42 58 58
Businesses
IV New uptake of or upgrade to NGA (from basic broadband) 50 80 90 90
299 Following the 'EU Guidelines for the application of State aid rules in relation to the rapid deployment of broadband networks'; OJ C25,
26.01.2013, p. 1, areas have been divided into three categories (white, grey and black) depending on the availability of broadband
infrastructure. White areas have no infrastructure at all and there are no plans for operators to develop these in the near future; grey areas
are those in which one network operator is present but it is unlikely that another network will be developed in the near future; and black
areas are those where at least two basic broadband networks of different operators already exist or there are plans to develop these;
broadband services are provided under competitive conditions. Generally, public intervention is only justified in white areas and, under
certain circumstances, also in grey areas, whereas there is no need for public intervention in black areas.
300 This category comprises households from ‘grey’ areas, where basic broadband services from one operator have been available, and as a
result of the project it will be possible to offer NGA services.
\243
IV Option analysis
The baseline for the option analysis is an option with no infrastructure. This was deemed as non-
compatible with both the national objectives and those objectives set out in the Digital Agenda for
Europe. Public consultations with operators resulted in a list of areas where there are no plans to
invest in relevant broadband infrastructure in the near future. It was therefore concluded that not
implementing the project would lead to an increase in the digital divide (the use of ICT) between the
areas identified as non-attractive to the market and the remaining areas of the region. This would
result in the digital exclusion of citizens and brain drain, as well as negative competitive effects for
local business.
As a first stage, two strategic options were assessed by analysing compliance with the national and EU
objectives:
phasing the infrastructure deployment (splitting the implementation over separate periods of
time, initially providing backhaul and last-mile services to only part of the target areas of the
region);
providing backhaul network coverage to the maximum number of households and SMEs.
The phasing of infrastructure deployment was discarded on the grounds of a lower mid-term
socioeconomic impact and compatibility with EU objectives. The estimated higher total project costs as
well as the technical challenges resulting from a split of the implementation were also assessed as
unreasonable. The option of maximising the network coverage was deemed as fulfilling the EU
objectives and enabling coverage to the largest number of households and businesses, further
leveraging private investments into last-mile network infrastructure.
The option analysis then considered three sets of options concerning different aspects of the project.
technical alternatives;
linear infrastructure alternatives;
business model alternatives.
Technical alternatives
A number of technical options were analysed in detail for:
network architecture, dimensioning and topology,
hierarchical structure,
network transmission medium and protocol,
construction of optic cabling routes, ducting and cable type.
The choice of network architecture and topology and its hierarchical structure followed what is
generally considered to be best practice for network design. Consequently, the baseline design
proposed a two-layer hierarchical design, with a crossover ring topology for the backbone and a star
topology for the backhaul network. The final design will take into account the existing infrastructure in
the region as much as possible and will be updated accordingly, subject to the approval of the project
promoter.
The selection of other network technologies was guided based on the optimisation of capacity and the
efficiency of the planned network. The main criterion for the selection was the requirement to ensure
that the technologies used could be considered as future-proof, i.e. that they minimise additional
investments in case of an increase in demand or capacity requirements. Consequently, the project
promoter equally analysed the options of partial upgrading of existing infrastructure as well as the use
of satellite technology for the backhaul network. However, these were discarded as they would not
meet the long-term requirements of a future-proof network. Fibre was deemed to be the optimal
choice to ensure that the objectives of the project were met.
\244
Linear infrastructure alternatives
Three public utility infrastructure networks were considered to help to bring down the construction
cost by using already existing routes to lay down the fibre:
scenario A – railway infrastructure
scenario B – road infrastructure
scenario C – energy infrastructure.
Variants were compared, based on multiple criteria, such as how well the different options would
allow the maintenance of an optimal network design and capacity, potential cost savings, and their
technical feasibility and environmental compliance. In this case, the rail infrastructure was assessed as
offering the highest potential use of the existing infrastructure, with a comparable cost structure to the
road scenario and lower than the energy scenario, it was feasible and would have the least negative
impact on the environment, as would the energy scenario. It was ultimately selected as the preferred
choice for the construction of the network, as it is technically and economically feasible.
Business model alternatives
The choice of the operational model for the project was drawn from an analysis between five different
management models:
in-house management,
technical outsourcing,
setting up a special purpose vehicle,
separation of construction and operation of the network into two tenders,
design-build-operate-transfer (DBOT).
The options were compared, based on multiple criteria such as estimated cost, possibilities for
management oversight and audit by regional authorities, operational risk, and the competences of
potential private partners. As a result, the design-build-operate-transfer concession model, in which
the construction and operation of the network are tendered in one stage, was selected. Under the
chosen DBOT model, the public partner (regional authority) will provide for the financing of the
investment and be the owner of the assets, and the selected private partner will be responsible for the
design, construction and subsequent management and operation of the infrastructure during the
concession period, after which the project’s infrastructure will be returned to the public partner. The
private partner will cash in the revenues from the wholesale services delivered to users (last-mile
operators and others) and pay a certain percentage of that income to the public partner as rent for the
infrastructure (to be defined in the tender process). A claw-back mechanism will be included in the
contract to avoid any over-compensation to the private partner.
V Project costs and revenues of the selected option
The total project investment costs of the selected option were estimated based on best industry and
in-house expertise. A cost breakdown is presented in the table below.
Total project costs Eligible costs (C)=(A)-
EUR Ineligible costs (B)
(A) (B)
1 Planning/design fees 11 000 000 0 11 000 000
2 Land purchase 0 0 0
3 Building and construction 62 000 000 0 62 000 000
4 Plant and machinery 13 000 000 0 13 000 000
5 Contingencies 0 0 0
6 Price adjustment (if applicable) 0 0 0
7 Technical assistance 0 0 0
8 Publicity 4 500 000 0 4 500 000
9 Supervision during construction 7 000 000 0 7 000 000
\245
implementation
10 Sub-TOTAL 97 500 000 0 97 500 000
11 VAT 20 585 000 20 585 000 0
12 TOTAL 118 085 000 20 585 000 97 500 000
With regards to operation and maintenance (O&M) costs, a detailed breakdown by type of cost was
prepared as part of the project feasibility study. The owner of the infrastructure will bear the
administrative costs related to the audit and oversight, estimated at being in the region of
EUR 0.7 million annually (with a gradual increase from EUR 0.3 million in the first year of operation).
The costs assigned to the private partner include Internet traffic and interconnection charges,
maintenance costs, energy consumption and third-party services (administration and personnel,
insurance). This showed that the O&M cost would be about EUR 2 million in the first year of operation,
with a gradual increase to EUR 5.4 million in the last years of operation. The increase in costs related
to Internet traffic, interconnection charges and energy consumption is linked to the increase in
broadband uptake rates and the increase in forecast demand for bandwidth (moving from basic
broadband to NGA broadband) over the duration of the project. The replacement of active equipment
totalling EUR 9.3 million is planned in years 11-13 after the start of operations and will be covered by
the infrastructure operator.
The results of the demand analysis were used to estimate revenues from the three broad categories of
wholesale services:
data transmission services
lease of infrastructure
colocation/equipment hosting services.
These revenues have been estimated at about EUR 2.2 million in the first year of operation with a
gradual increase to EUR 9 million in the last year of operation. The estimation of financial revenues
was based on benchmarked wholesale service prices in areas where relevant wholesale services are
provided and set at the level of EUR 30/month for NGA access to businesses; EUR 20/month for NGA
access to households and EUR 10/month for basic broadband access. The regulator was consulted on
the prices and will continue to monitor their level during the project operation. Revenues from line
rental and colocation services were calculated together as a percentage of the revenues from
wholesale services, which was estimated at 55 % of the revenues from transmission services during
the project duration and reflects the results of surveys on fixed and mobile network operators, which
verified the market demand for these services.
VI Financial and economic analysis
The financial and economic analysis of the project is based on the incremental approach. All cash flows
are stated in constant EUR and the real discount rates applied are 4 % in the financial analysis and 5 %
in the economic analysis. The reference period was set at 20 years, including three years of
construction. As the average economic life of the project assets is assumed to be 20 years, a residual
value is considered in the last year of the time horizon, reflecting the discounted value of the net cash
flows in the remaining years.301
Financial analysis
The financial analysis is conducted in a consolidated manner, including the owner and the operator of
the infrastructure, without consideration of the internal cash flows between them (rent paid for the
301 The net cash flows of the three remaining life years are assumed to be equal to that of the last year of the reference period, taking into
account the replacement costs of the active components. In the economic analysis, the net economic benefit is used instead of the financial
cash flow. Accordingly, the financial residual value is estimated at EUR 7.6 million, while the economic one is forecast at EUR 55.3 million.
Replacement costs of active components are equal to a percentage (30 %) of replacement costs from years 11-13, reflecting additional
duration of operations.
\246
infrastructure). The financial profitability indicators calculated for return on investment [FNPV(C) of
the project is EUR -68.5 million and the financial rate of return on the investment, FRR(C) is -6.4 %]
confirm that the project would not take place without grant support.
The project is subject to the rules on State aid and was therefore notified to the European Commission.
After examination by the Directorate-General for Competition the project was found to be compatible
with State aid regulations and subsequently authorised. A calculation of discounted net revenue is in
principle not necessary for projects when an individual verification of financing needs is carried out in
accordance with applicable State Aid rules. However, in this case, national rules required the project
promoter to nevertheless undertake this calculation in order to determine the appropriate level of
ERDF contribution and avoid overcompensation.
Based on the costs and revenues described in the section above, the estimated pro-rata application of
discounted net revenue is 77 % (DIC = EUR 88.7 million, DNR = EUR 20.2 million, see further
calculation below). Multiplying the eligible cost (EUR 97.5 million) by the pro-rata application of
discounted net revenue and by the co-financing rate of the relevant priority axis of the OP (85 %), the
EU grant for the project results in EUR 64 million. The remainder of the investment (EUR 33.5 million)
is to be funded by the project promoter and owner of the infrastructure.
The fact that the financial rate of return on national capital [FRR(K) is equal to 0.9 %] is below the
discount rate applied and that the financial return on national capital is negative [FNPV(K) is equal to
EUR -10.3 million] further shows that the investment aid granted is not over-proportionate.
It needs to be noted here that although last-mile operators were consulted in advance, there is a
certain level of uncertainty with regards to the final level of revenues that will be generated by the
infrastructure. This was acknowledged in Directorate-General for Competition's State aid decision,
which required the inclusion of a claw-back mechanism into the concession contract that would apply
in case revenues are higher than originally foreseen302. The State aid decision also includes provisions
on the use of the revenues recovered through the claw-back mechanism on the side of the public
authorities303.
The sustainability analysis was performed for the project as a whole and shows that based on the
assumptions described above the project will not run out of cash during the implementation and
operating periods. Sufficient securities were provided by the regional authority as the project
promoter that allow there to be sufficient confidence in its capability to co-finance the project.
Table 1 Financial cash flows and performance indicators of the project
302The Broadband State Aid Guidelines require projects applying for public aid to include a reverse payment (claw-back) mechanism into the
concession contract with the successful bidder so as to ensure that there is no over-compensation of the contractor if demand for broadband
in the target area grows beyond anticipated levels. The provision of such a mechanism is aimed at minimising ex post and retroactively the
amount of aid deemed initially to have been necessary. The claw-back mechanism needs to be explained in the project notification as well as
the indicators applied to check for over-compensation. Although there is no standard definition for over-compensation, which leaves some
room for interpretation, it can generally be presumed where profits are higher than in the original business plan or the industry average. In
case practice to date, the following indicators for over-compensation have been proposed and accepted by the Commission: i) profit is higher
than 10 % of the value of the network and equipment (e.g. N 626/2009); ii) profits are calculated cumulatively and reclaimed if exceeding the
average industry’s profit (e.g. N 30/2010); iii) based on a comparison of the operator’s EBITDA (earnings before interest, tax, depreciation
and amortisation) with the market benchmark [e.g. N 407/2009; SA.33438 (2011/N)]; iv) application of weighted average cost of capital as a
benchmark for the industry’s level of return (e.g. N 596/2009).
303As explained in the Broadband State Aid Guidelines, 'Granting authorities can foresee that any extra profit reclaimed from the selected
bidder could be spent for further broadband network expansion within the framework scheme and at the same conditions of the original aid
measure.' Such an approach was applied in several cases [e.g. N 183/2009; SA.32866 (2011/N)].
\247
EU GRANT
Calculation of Discounted Investment Cost (DIC) NPV 4%
Investment cost (w/o contingencies) mEUR -88.7 -9.5 -36.5 -51.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
DISCOUNTED INVESTMENT COST (DIC) mEUR -88.7 -9.5 -36.5 -51.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Calculation of Discounted Net Revenues (DNR) NPV 4%
Revenues - data transmission services mEUR 46.1 0.0 0.0 0.0 1.4 2.2 4.3 4.6 4.9 5.2 5.5 5.7 5.8
Revenues - lease of infrastructure and dark fibre mEUR 25.4 0.0 0.0 0.0 0.8 1.2 2.4 2.5 2.7 2.9 3.0 3.1 3.2
O&M cost - maintenance mEUR -14.9 0.0 0.0 0.0 -0.7 -1.1 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5
O&M cost - energy mEUR -3.7 0.0 0.0 0.0 -0.1 -0.2 -0.3 -0.4 -0.4 -0.4 -0.4 -0.5 -0.5
O&M cost - IP traffic mEUR -13.8 0.0 0.0 0.0 -0.4 -0.6 -1.3 -1.4 -1.5 -1.6 -1.6 -1.7 -1.7
O&M cost - labour and administrative costs mEUR -16.6 0.0 0.0 0.0 -0.7 -1.0 -1.7 -1.7 -1.7 -1.7 -1.7 -1.7 -1.7
Replacement cost mEUR -5.8 0.0 0.0 0.0 0.0 0.0 0.0 -3.1 -3.1 -3.1 0.0 0.0 0.0
Residual value of investments mEUR 3.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.6
DISCOUNTED NET REVENUES (DNR) mEUR 20.2 0.0 0.0 0.0 0.2 0.4 1.9 -0.9 -0.5 -0.1 3.2 3.5 11.2
ELIGIBLE COST (EC) mEUR 97.5
Pro-rata application of DNR = (DIC - DNR) / DIC: 77%
CO-FINANCING RATE IN PRIORITY AXIS (CF): 85%
EU GRANT ( = EC x PRO-RATA x CF): mEUR 64.0
◄◄ ►► ◄◄ ►►
1 2 3 4 5 10 11 12 13 14 15 20
FRR(C)
Construction Operation
Return on Investment NPV 4%
Investment cost (w/o contingencies) mEUR -88.7 -9.5 -36.5 -51.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M cost mEUR -49.0 0.0 0.0 0.0 -2.0 -2.9 -4.8 -4.9 -5.0 -5.1 -5.2 -5.3 -5.4
Replacement cost mEUR -5.8 0.0 0.0 0.0 0.0 0.0 0.0 -3.1 -3.1 -3.1 0.0 0.0 0.0
Revenues mEUR 71.5 0.0 0.0 0.0 2.2 3.4 6.7 7.1 7.6 8.1 8.5 8.9 9.0
Residual value of investments mEUR 3.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.6
Net project cash-flow / FNPV(C) - before EU grant mEUR -68.5 -9.5 -36.5 -51.5 0.2 0.4 1.9 -0.9 -0.5 -0.1 3.2 3.5 11.2
FRR(C) - before EU grant -6.4%
◄◄ ►► ◄◄ ►►
1 2 3 4 5 10 11 12 13 14 15 20
FRR(K)
Construction Operation
National Financing Sources
National public (grant) mEUR 3.3 12.5 17.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Return on National Capital NPV 4%
National public (grant) mEUR -30.5 -3.3 -12.5 -17.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M cost mEUR -49.0 0.0 0.0 0.0 -2.0 -2.9 -4.8 -4.9 -5.0 -5.1 -5.2 -5.3 -5.4
Replacement cost mEUR -5.8 0.0 0.0 0.0 0.0 0.0 0.0 -3.1 -3.1 -3.1 0.0 0.0 0.0
Revenues mEUR 71.5 0.0 0.0 0.0 2.2 3.4 6.7 7.1 7.6 8.1 8.5 8.9 9.0
Residual value of investments mEUR 3.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.6
Net national cash-flow / FNPV(K) - after EU grant mEUR -10.3 -3.3 -12.5 -17.7 0.2 0.4 1.9 -0.9 -0.5 -0.1 3.2 3.5 11.2
FRR(K) - after EU grant 0.9%
◄◄ ►► ◄◄ ►►
1 2 3 4 5 10 11 12 13 14 15 20
FINANCIAL SUSTAINABILITY (consolidated)
Construction Operation
Financial sustainability
National public subsidy (grant) mEUR 3.3 12.5 17.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
National private (equity) mEUR 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
EU grant mEUR 6.2 24.0 33.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Revenues mEUR 0.0 0.0 0.0 2.2 3.4 6.7 7.1 7.6 8.1 8.5 8.9 9.0
Total cash inflows mEUR 9.5 36.5 51.5 2.2 3.4 6.7 7.1 7.6 8.1 8.5 8.9 9.0
Investment cost mEUR -9.5 -36.5 -51.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
O&M cost mEUR 0.0 0.0 0.0 -2.0 -2.9 -4.8 -4.9 -5.0 -5.1 -5.2 -5.3 -5.4
Replacement cost mEUR 0.0 0.0 0.0 0.0 0.0 0.0 -3.1 -3.1 -3.1 0.0 0.0 0.0
Income tax (public and private mEUR 0.0 0.0 0.0 0.1 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3
Corporate tax (private partner) mEUR 0.0 0.0 0.0 0.0 0.0 -0.1 0.0 0.0 -0.2 -0.1 0.0 -0.3
Total cash outflows mEUR -9.5 -36.5 -51.5 -1.8 -2.7 -4.5 -7.7 -7.8 -8.1 -5.0 -5.0 -5.3
Net cash-flow mEUR 0.0 0.0 0.0 0.4 0.6 2.2 -0.6 -0.2 0.0 3.5 3.8 3.7
Cumulated net cash-flow mEUR 0.0 0.0 0.0 0.4 1.0 8.3 7.7 7.6 7.5 11.0 14.9 33.4
\248
Economic analysis
The economic analysis is conducted from the perspective of the society that will benefit from an
increased broadband connectivity.
On the cost side, the same investment and operating costs used in the financial analysis are applied
and corrected where necessary. In this case, corrections to financial prices were made for:
non-skilled labour component in the investment cost (in particular in the building and
construction component), by applying a shadow wage correction factor (CF) to account for the
high unemployment level in the project area, correction factor = 0.7;
taxes (municipal taxes, not related to VAT, to be paid for the use of infrastructure) were
removed from the economic analysis (correction factor = 0);
energy prices in O&M costs, by taking into account the share of taxes and levies paid by
industrial customers based on Eurostat data, correction factor = 0.8;
all other project cost components were left uncorrected, as it was assumed that these are
adequately priced on the market, correction factor = 1304.
On the benefit side, financial revenues of the project were disregarded305 and instead the project’s
socioeconomic benefits were estimated by applying proxies for the WTP of users in accordance with
the methodology and assumptions presented in the following table. The economic benefits are directly
linked to the project objectives and the expected demand of end-users, i.e. local businesses,
households and providers of public services such as government and health services.
To take into account the fact that the project does not include last-mile networks and services, the
estimated project benefits were allocated in accordance with the project’s share of the total costs
required to provide the services to the end users (estimated at 50 %). Furthermore, for upgrades from
the basic to the NGA broadband category, an 80 % scaling factor has been applied when calculating e-
government and tele-health-care benefits to recognise the effect a higher bandwidth has on the type of
services that can be provided.
306
Table 2 Assessment of socioeconomic benefits
Indicator Assessment
Benefit 1: Business employee benefits
Business benefits are expressed as a percentage increase of local gross value added (GVA) per
employee in the private sector for different broadband (BB) services:
- new connection to basic BB: 4.5 % rise in GVA per employee
- new connection to NGA BB: 6.0 % rise in GVA per employee
Business benefit - upgrade from basic BB to NGA BB: 1.5 % rise in GVA per employee
per employee
The values proposed are the results of an analysis of productivity resulting from broadband take-
up and are based on the available report, which suggests an average potential rise in GVA per
307
person across ‘aspiring’ countries of around 11 %, including the one EU-12 Member State in
the study with a figure of around 6 %. As the project is realised in a country with a similar level of
GDP per capita, no further GDP adjustments were applied and the figure was maintained.
304Most other project components are specialised technological equipment and professional services which can be assumed to be adequately
priced on the market.
305 The project intervenes in areas where there is market failure or reduced competition resulting in no interest from private operators to
invest in these areas, and making these areas eligible for public support. In addition, due to the State aid requirements, the prices applied are
benchmarked and may not correctly reflect the local project users' real willingness-to-pay (WTP).
306 The values used in the economic analysis have been based on a benefit transfer method and derived from analysis of available literature.
GDP adjustment was done in those cases where the results were based on studies from countries with different GDP levels. A detailed list of
referenced studies and national statistics has been provided in the Feasibility Study.
307
\249
Figures regarding the GVA rise for other broadband categories have been derived from an
International Telecommunications Union (ITU) study that assumes doubling the broadband speed
308
results in 0.3 % rise in GVA .
The GVA rise due to basic broadband is 4.5 % (6.0 % - 5*0.3 %) because it is assumed that the
basic broadband speed needs to be doubled approximately five times to reach NGA broadband
speeds. Finally, the GVA rise from basic to NGA broadband is calculated as the differential
between NGA broadband and basic broadband.
This category of benefits is assumed to take four years after project operations have been initiated
to fully emerge.
Calculated as: GVA value in the region * number of employees connected to basic or NGA
broadband as a result of the project * percentage rise in GVA as explained above.
Based on the assumption that most businesses newly connecting to broadband services are very
small SMEs and in order to apply a conservative assumption, it is assumed that for each
enterprise that is newly connected or upgrading its broadband connection, the average number of
employees using modern ICT in their daily work is 1.
Benefit 2: Household consumer surplus
Household benefits are expressed in EUR per month and household for different BB services:
- new connection to basic BB: EUR 12 per month and household
- new connection to NGA BB: EUR 8 per month and household
- upgrade from basic BB to NGA BB: EUR 4 per month and household
To estimate the level of consumer surplus, the benefit transfer method was applied: estimations of
consumer surplus from NGA-types of services were derived from the industry study and were
adjusted for differences in income levels and differences in the costs of living (using Eurostat data
on GDP per capita in purchasing power standards, PPS).
Consumer
Consumer Consumer
surplus in GDP
surplus in surplus
USD based adjustment Average
EUR adjusted
Consumer surplus on the study (EUR)
EU Country 1 28 21 0.6 12
EU Country 2 26 19 0.7 13
12
EU Country 3 22 16 0.6 10
EU Country 4 17 13 1.0 13
As the speed of broadband connectivity is as important as the range of benefits that can be
obtained, the value of EUR 8 per month for basic broadband Internet and a differential of EUR 4 if
the consumer switches from basic to NGA broadband was further applied, based on expert
knowledge.
Calculated as: Level of consumer surplus as set above * number of connected households to
basic or NGA broadband as a result of the project * number of months per year * benefit ratio
Benefit 3: e-government savings
Estimation of savings from e-government was based on the region’s strategy, which states that
the implementation of e-government measures (broadband connectivity and e-government
e-government services) would result in annual savings of EUR 100 million. This target was then scaled down to
savings only take into account the share of total households connected by the project.
Calculated as: Target e-government savings from regional strategy * share of households
connected to the network as the result of the project * benefit ratio.
Benefit 4: Tele-health-care benefits
The analysis has made an attempt to apply the benefit transfer method to estimate the savings
Tele-health-care related to tele-health-care benefits. While available studies confirmed that a high-speed network
savings can yield benefits such as more efficient management and improved health outcomes, the results
are preliminary and indicate the need to measure the scale of benefits further. For the purpose of
308 www.itu.int/ITU-D/ict/newslog/Doubling+Broadband+Speed+Leads+To+03+GDP+Growth+In+OECD.aspx. The paper says a 0.3 % rise in
GDP rather than GVA but it is assumed that GVA and GDP are broadly equivalent in this context because GVA usually represents at least 90 %
of GDP.
\250
analysis, conservative assumptions were made to estimate tele-health-care savings as a 1-3 %
share of the local health budget (1 % in first five years after roll-out and 3 % thereafter) and scaled
down to only take into account the share of total households connected by the project.
Calculated as: Local health budget * percentage share of households connected to the network as
a result of the project (further application of 0.8 scaling factor for new connections to basic
broadband and upgrade from basic to NGA) * estimated share in realising the savings (1 % or 3 %
as above) * benefit ratio
Based on these assumptions, the following economic indicators are calculated (see Table 3).
Table 3 Calculation of economic rate of return (ERR) and economic cost-benefit ratio
◄◄ ►► ◄◄ ►►
ERR
1 2 3 4 5 10 11 12 13 14 15 20
Construction Operation
TOTAL
Project investment cost (w/o contingencies) mEUR 97.5 9.5 36.5 51.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
of which:
Traded goods and skilled labour 82.2 8.8 31.1 42.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Non-traded goods 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Unskilled labour 12.4 0.6 4.4 7.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Taxes 2.9 0.1 1.0 1.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Conversion Factors
Traded Goods and Skilled Labout Coef. 1.0
Non-traded goods Coef. 1.0
Unskilled Labour Coef. 0.7
Taxes Coef. 0.0
Energy Coef. 0.8
Socio-economic cash-flows NPV 5%
Economic investment cost (w/o contingencies) mEUR -79.9 -9.2 -34.2 -47.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Economic O&M cost (including replacement costs) mEUR -45.6 0.0 0.0 0.0 -2.0 -2.9 -4.7 -7.9 -8.0 -8.2 -5.2 -5.2 -5.3
Residual value of investments mEUR 18.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 55.3
Economic benefits - Business employee benefits mEUR 73.9 0.0 0.0 0.0 5.3 5.8 8.4 8.9 9.5 9.5 9.5 9.5 9.5
Economic benefits - Household consumer surplus mEUR 82.7 0.0 0.0 0.0 3.5 5.6 9.3 9.7 10.2 10.7 11.0 11.4 11.5
Economic benefits - e-Government savings mEUR 35.6 0.0 0.0 0.0 1.5 2.4 4.0 4.2 4.4 4.6 4.8 4.9 5.0
Economic benefits - Tele-health care benefits mEUR 5.0 0.0 0.0 0.0 0.1 0.1 0.6 0.6 0.7 0.7 0.7 0.7 0.7
Net project benefits / ENPV mEUR 100.5 -9.2 -34.2 -47.6 8.4 11.0 17.7 15.5 16.6 17.3 20.8 21.3 76.7
ERR 14.4%
B/C RATIO 1.85
Despite its low financial profitability, the high economic profitability (ERR: 14.4 %, B/C Ratio: 1.85)
makes the project worthy of the support of EU funds.
VII Risk assessment
Sensitivity analysis
A sensitivity analysis was carried out to identify the 'critical' variables of the model. Changes of 1 %
were considered to the value of investment costs, revenues, operating costs and economic benefits.
Those variables that led to more than a 1% change in ENPV, FNPV(C) and/or FNPV(K), i.e. the critical
variables, are the investment costs, demand analysis and consumer surplus (see Table 4
Results of sensitivity analysis
).
Table 4 Results of sensitivity analysis
Variable ENPV elasticity Switching FNPV(C) Switching value
value elasticity
Investment cost -0.9 % 108 % 1.3 % -75 %
O&M costs -0.5 % 207 % 0.7 % -140 %
Demand for services 2.2 % -46 % -0.8 % 127 %
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Revenues from data transmission services -0.7 % 148 %
Revenues from leasing of infrastructure -0.4 % 270 %
Business benefits 0.9 % -
Consumer surplus 1.0 % -
e-government savings 0.4 % -
e-health savings 0.1 % -
Figure 1: Charts sensitivity analysis
Sensitivity Analysis - ENPV Sensitivity Analysis - FNPV(C)
250 0
Econ. Investment cost
(incl. reinvestment) Investment
200 Econ. O&M costs (excl. -20
reinvestments) Fin. O&M costs (excl.
Demand for services reinvestment cost)
150 -40 Demand for services
FNPV(C) (mEUR)
ENPV (mEUR)
Consumer surplus
Revenues from leasing
100 Business benefits of infrastructure
-60
e-government savings Revenues from data
transmission services
50 -80
e-health savings
0 -100
-50 -120
40% 60% 80% 100% 120% 140% 160% 40% 60% 80% 100% 120% 140% 160%
Change in variable Change in variable
The high switching values for the critical variable (investment costs) identified in the financial analysis
suggest that the project is most likely to maintain a negative FNPV(C), even under reasonably
optimistic assumptions on the change in investment costs, thus supporting the project with an EU
grant appears justified. The most critical variable for the project’s ENPV is the change in demand,
which shows a switching value of 46 %. The demand analysis was based on the detailed analysis of
market trends and the region’s demographics, and was further supported by consultations with
network operators, hence the probability of a situation in which the project fails to secure the
necessary demand being low. All other variables show notably higher switching values, which means
that the result of the economic analysis is robust and the project will remain worthy of EU financing
even under pessimistic assumptions.
Risk analysis
The risks of the project are evaluated in the following risk matrix. The analysis considers demand side
risks and financial risks during implementation and operations, as well as institutional and legal risks.
The identified risk factors are evaluated against their probability of occurrence and their expected
impact on the project. Finally, risk prevention and mitigation measures are established to manage the
risk (see Table 5 for a summary).
Table 1 Project risks
Risk Probability* Severity* Risk level* Risk prevention/ mitigation measures Residual
description (P) (S) (= P*S) risk
Demand risk
Low B IV Moderate Market consultations with potential last- Low
investments in mile network operators were carried out
last-mile by the project promoter during preliminary
network by network design.
service
providers
Low take-up by C V High Actively promote the project amongst the Moderate
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Risk Probability* Severity* Risk level* Risk prevention/ mitigation measures Residual
description (P) (S) (= P*S) risk
end-users from potential users and local public
service administration through appropriate
providers publicity campaigns. An appropriate
budget for this purpose has therefore
been included in the project investment
cost.
Implement demand stimulation activities,
like training and promotional measures by
the project promoter.
Coordinate with complementary priorities
of the OP: subsidy for the end-users with
low income, and development of new e-
government and e-health services.
Risks during implementation
Change of the C III Moderate An active dialogue between the project Low
project promoter and the private sector was
investment carried out at the stage of project
costs development (to ensure correct cost
estimations), which will be continued
during the DBOT procurement process
(to ensure that the private sector
understands the project requirements).
The project promoter shall identify and
secure other sources of funding in case
additional financing is required (i.e. bids
for DBOT contract are higher than
expected).
Implementation C V High The implementation plan takes into Moderate
delays account time contingencies. The DBOT
contract will further contain detailed
clauses in relation to dates when given
parts of the network must be delivered or
compensatory payments will need to be
paid by the private partner. This will allow
sharing the implementation risk with the
private partner and give an incentive to
the private partner to limit delays.
Ensure an adequately skilled internal
resource is in place on the project
promoter’s side for implementation.
Assign a full-time project manager on the
project promoter’s side and manage
project in a structured environment.
Actively use dialogue sessions involving
all key personnel, including private sector
partner, to ensure implementation is on
track.
Institutional risks
Unsuccessful A V Moderate The project promoter ensured that there Low
ERDF was regular communication with the
application, managing authority and the European
lack of EU Commission at an early stage of project
funding development so as to identify and
address any issues in a timely manner.
Additional external support was sought to
assist in the project development (private
consultants, JASPERS).
Legal risks
Procurement D III High Prepare detailed tendering Moderate
delay documentation by experienced
internal/external experts appointed by the
project promoter.
Introduce time contingencies in project
planning by the project promoter taking
into account possible procurement delays
(i.e. management of claims by
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Risk Probability* Severity* Risk level* Risk prevention/ mitigation measures Residual
description (P) (S) (= P*S) risk
competitors).
Risk of not B II Low The project promoter ensured close Low
obtaining cooperation with the local administration
required authorities at the stage of network pre-
property rights design.
The project promoter took into account
the minimum number of permits required
when preparing the pre-design of the
network.
Each year, areas where permits can be
problematic need to be identified.
Possible alternative locations will be the
private partner’s responsibility at the
stage of the final network design.
Financial risks during operations
Increase in C IV High Regularly verify the project cost Moderate
project assumptions at the stage of network
operating costs implementation by the private partner.
Ensure close dialogue between the
private partner and the last-mile
infrastructure operators so as to minimise
future operating costs at the design
stage.
Agree on possible modifications of the
level of rent between the project promoter
and the private partner.
Identify sources of funding by the project
promoter and private partner to cover any
potential increase in operating costs
assigned to the project promoter or
private partner.
Evaluation scale: Probability: A. Very unlikely; B. Unlikely; C. About as likely as not; D. Likely; E. Very likely.
Severity: No effect; II. Minor; III. Moderate; IV. Critical; V. Catastrophic.
Risk level: Low; Moderate; High; Unacceptable.
The risk analysis indicates that without appropriate risk prevention and mitigation measures the
overall risk level for the project would be unacceptably high. However, the measures put in place to
prevent the occurrence of the identified risks and/or mitigate their adverse impact should lower the
individual risk levels and result in an overall manageable and acceptable residual risk for the project.
The risk of the project failing to achieve its targeted objectives at a reasonable cost can be considered
to be low.
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7. Research, development and innovation
7.1 Introduction
The research, development and innovation (RDI) infrastructure is the generic name for investment
projects that are designed and operated according to very different specifications. In some cases their
features are unique, and cannot be analysed with the same degree of standardisation of methods as,
for example, in railways or in water, for which there are several decades of evaluation experience and
a large library of appraisal documents.
Moreover, while the target groups of other infrastructures are relatively well identified, e.g.
passengers for high-speed rail or residents in a urban area for solid waste management, the
multifaceted nature of RDI is such that many types of direct and indirect target groups are involved,
from businesses to the general public. Each of them has standing in the CBA, and this makes the
evaluation of infrastructures a particularly complex task. 309
It is expected that over the next planning period, a portfolio of CBAs of RDI infrastructures will be
gradually built within the Member States, following the high priority given to research and innovation
for the EU growth strategy, and this chapter offers some hints about how to proceed for applicants of
EU funds in the context of cohesion policy.310 Differently from the other chapters of the guide, this
chapter does not include a complete case study, because of the large variability of types of RDI
infrastructures. However, it includes several practical examples.
Cost-benefit analysis of RDI infrastructures is a new field and the project proposer should be aware
that, at the same time, it requires a solid understanding of the principles of CBA, professional
experience in project evaluation in different areas and a very flexible practical approach tailored to the
specific project under appraisal.
7.1.1 RDI projects in the EU policy agenda
Research, development and innovation are at the core of the policy agenda as key drivers of
sustainable long-term economic development.311 In the last decade, the European Union has pushed
towards the expansion of RDI capacities and the increase of expenditure in RDI activities, with the final
objective of making the EU a leading knowledge-based economy, and regaining its place as a world
leader in science and technological progress.
Building on the intent of increasing public and private expenditure in research and development
throughout the EU Member States so as to approach 3 % of GDP by 2020, the European Commission
adopted the Europe 2020 Strategy in 2010, which puts RDI at the top of the EU agenda for smart,
sustainable and inclusive growth. In order to take a more strategic and overarching approach to
innovation, improve the innovation systems in the EU and overcome fragmentation, the Commission
309 A staff working paper developed by JASPERS (2013) and the European Investment Bank Guide (2013) have been used in the past as
preliminary guidance for application of the CBA approach into the practice of the RDI sector. These guidelines reflect the authors’ experience
gathered with RDI projects developed in the programming period 2007-2013, including some prepared in the context of EU funded
programmes. It can be anticipated that these guides will be updated from time to time to consider new developments in best practice and
academic research. The reader should also be aware that, in order to improve the methodological framework for the appraisal of RDI
infrastructure, the European Investment Bank University Research Sponsorship programme (EIBURS) is currently funding an academic
research project entitled ‘Cost/Benefit Analysis in the Research, Development and Innovation Sector’ (http://www.eiburs.unimi.it/), which
started in December 2012 and will continue until December 2015.
310 Other procedures may be in place in other contexts and the CBA perspective should be seen as a complement to them; see, for example,
the evaluation process for the European Strategy Forum for Research Infrastructures (ESFRI) projects (ESFRI, 2011; European Commission,
2013), the Organisation for Economic Cooperation and Development (OECD) Global Science Forum reports for large research infrastructures
(OECD 2008 and 2010) and the FenRIAM Guide (Curaj and Pook, 2011).
311 In this field, different acronyms are often used in policy and regulatory documents, such as RI (research and innovation), R&D (research
and development), RTDI (research, technological development and innovation). In this chapter the abbreviation RDI is used, in order to
explicitly account for different typologies of infrastructures, which may span from research to innovation activities, including technological
development. As explained in section 7.1.2, the boundaries between the different activities are narrow and it is often difficult to disentangle,
in practice, pure research activities from development, and applied research/development from innovation.
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launched the 'Innovation Union' flagship initiative, aimed to ensure that innovative ideas can be
turned into products and services that create economic growth and jobs.312
Efforts to promote RDI throughout the EU Member States may include a variety of initiatives. The
European Commission’s Guide to Research and Innovation Strategies for Smart Specialisations (RIS3)
(2012) identifies a mix of delivery instruments that could be part of a regional innovation strategy,
such as cluster development, measures of innovation friendly business environment, research
infrastructures, centres of competence and science parks, support to internationalisation, financial
engineering instruments and others. Among all these, only operations whose total eligible costs
exceeds EUR 50 million and fall within the definition of major projects, according to Article 100 of EU
Regulation No 1303/2013, should be appraised through CBA.
RDI infrastructures can be promoted by enterprises and/or universities, research institutes and other
entities, often in collaboration with each other. Enterprises include both large businesses and SMEs,
which could participate either individually or in aggregation with other enterprises (e.g. clusters,
consortia, etc.). The types of eligible investment in RDI and the volume of public aid should comply
with the Community framework for State aid.313
Selected policy and regulatory documents relevant to the RDI sector are listed in the box below.
THE EU POLICY FRAMEWORK
European Commission Communication, 'Europe 2020. A strategy for smart, sustainable and inclusive growth',
COM(2010) 2020 final.
European Commission Communication, 'Europe 2020 Flagship Initiative – Innovation Union', COM(2010) 546.
European Commission Communication, 'Regional Policy contributing to smart growth in Europe 2020” -
COM(2010) 553.
Commission Staff Working Document, 'A rationale for action', SEC(2010)1161 final, accompanying document to
COM(2010) 546.
European Commission Communication, 'A Reinforced European Research Area Partnership for Excellence and
Growth', COM(2012) 392 final.
European Commission Communication, 'A Stronger European Industry for Growth and Economic Recovery'
COM(2012) 582 final.
European Commission, DG Regional Policy, 'Guide to Research and Innovation Strategies for Smart
Specialisations (RIS3)', March 2012.
European Commission Green Paper, 'From Challenges to Opportunities: Towards a Common Strategic
Framework for EU Research and Innovation funding', COM(2011) 58.
European Commission Communication, 'Framework for State aid for research and development and innovation',
(2014/C 198/01).
European Commission Communication, 'Preparing for our future: Developing a common strategy for key
enabling technologies in the EU', COM(2009) 512 final.
European Strategy Forum on Research Infrastructures – ESFRI 'Research infrastructures and the Europe 2020
Strategy'.
Innovation: How to convert Research into Commercial Success Story?, Study of the European Commission, 2013
312 European Commission Communication, 'Europe 2020. A strategy for smart, sustainable and inclusive growth', COM(2010) 2020 final.
313 The European Commission considers that State aid for innovation for both SMEs and large companies should be authorised to the extent
that it relates to precise and truly innovative operations, which clearly address the market failures that hamper innovation and prevent
increasing the level of research and development in the EU economy. State aid for RDI should be targeted to projects that would have not
taken place, or would be carried out in a more restricted manner without State aid.
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7.1.2 Definitions of RDI infrastructures and the focus of the cohesion policy’s intervention
The innovation process is generally associated with a number of activities, related to fundamental
research, applied research, experimentations and technological development, production and
commercialisation. When RDI investments are characterised by a clear prevalence of one type of
activity over another, it is possible to distinguish RDI projects as investments focused either on
research and development, or on innovation.
In what follows, the following definitions are adopted.
Research and development infrastructures are science-related physical realisations
(laboratories, facilities, etc.) developed with the main purpose of acquiring new knowledge in a
given scientific and technological field.
Research and development infrastructures, in turn, can be discriminated between:
o infrastructures for fundamental research, i.e. infrastructures that are meant to
undertake theoretical or experimental work primarily to acquire new knowledge on the
underlying foundations of phenomena and observable facts, without any direct practical
application or use in view; and
o infrastructures for applied research and experimental development, i.e.
infrastructures directed to a more practical purpose, where research and investigation are
aimed at the acquisition of new knowledge and skills for developing new products, processes
or services or for bringing about a significant improvement in existing products, processes or
services, which are not yet directly intended for commercial use.
Innovation infrastructures are infrastructures aimed at combining knowledge and
technology for the development of new or improved products, services and business processes
that could be sold on the marketplace.
In many cases, however, it is not possible to sharply distinguish between research and development
infrastructures and innovation infrastructures. RDI infrastructure projects in reality are likely to
encompass multiple activities, ranging throughout the whole innovation process spectrum (section 7.4
contains some examples of typical RDI projects). The combination of knowledge creation with
knowledge transfer activities, ultimately intended for the commercialisation of research results, aims
to produce direct economic impact on the regional/national dimensions in terms of industrial
competitiveness.314
According to the new European strategic orientations, defined in the Europe 2020 strategy, and in line
with thematic objective 1 'Strengthening research, technological development and innovation' of the
EU Regulation No 1303/2013 (Article 9), during the 2014-2020 programming period the European
Commission will focus on reinforcing links between education, business, research and innovation.
Accordingly, major projects are expected to target, in particular, innovation and applied research and
technological development infrastructures, which are closer to the market, as a means of translating
knowledge into tangible and immediate business opportunities.
The ERDF could only support investments in building fundamental research in exceptional cases,
insofar as they are expected to produce tangible effects for regional and national economies and create
a competitive environment in which the endogenous strengths of given regions (reflected in specific
existing or emerging industries) are translated into market innovations.315
314 In turn, industrial competitiveness has several dimensions: human capital, fixed capital accumulation, labour productivity, etc.
315In particular, fundamental research infrastructures and purchasing equipment for fundamental research may be supported under the
following conditions: i) the research fields must be in line with the smart specialisation strategy, ii) there must be a justification on how the
results of the research will be used to benefit the economic development of the region concerned, iii) as regards major projects, all the CBA
and other planning aspects (in particular a business plan to ensure financial sustainability of the investments) have to be taken into account
at the earliest stage, preferably as part of the OP, iv) preference should be given to such projects that are part of the ESFRI roadmap or a
regional partner facility of ESFRI infrastructures and in line with the smart specialisation strategy.
See Draft Thematic Guidance Fiche for Desk Officers, Research and Innovation, Version 3 – 13/03/2014. Available at:
http://ec.europa.eu/regional_policy/sources/docgener/informat/2014/draft_thematic_guidance_fiche%20research_innovation_final.pdf
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7.2 Description of the context
The analysis of the socioeconomic context is crucial to the development of RDI infrastructure as it
affects the decision on size, sector and purpose of the infrastructure. The degree to which the RDI
infrastructure to be developed fits into the (regional, national and international) context and are
tailored to the RDI needs should be clearly assessed.
The analysis of the socioeconomic trend provides important information for the assessment of existing
research and innovation gaps and needs, and should therefore be the starting point for the project
appraisal. Information related to the socioeconomic trend should also be discussed in detail because
they are likely to influence the forecasting of benefits (see section 7.8).
From the perspective of policy and legislative context elements, investments in RDI should fit into the
smart specialisation strategy of a country or region and thus contribute to its place-based economic
transformation, supporting territorial competitive advantages and potentials. Reference to other
relevant policy and programming documents should be made explicit.
An analysis of the industry in the region/area that can benefit from the RDI project is needed for the
assessment of needs and the verification of the project’s relevance, especially when the scope is to
trigger innovation processes. Conditions and the capacity for existing research facilities, human capital
endowment (in terms of students and researchers) and employment opportunities should be carefully
assessed to identify the bottlenecks that the project is aimed to fix. The potential of cost savings,
efficiency gains and economies of scale achieved through collaboration with other countries/regions
and possibly existing infrastructures should be explored.
The main context information that is generally relevant to RDI infrastructures and which should be
discussed in the project appraisal, where applicable, is shown in Table 7.1. Possible data sources
include Eurostat, the OECD, the European Spatial Planning Observation Network (ESPON), Innovation
Union Scoreboard indicators, etc.
Table 7.1 Presentation of the context: RDI sector
Information
- National and regional GDP growth
- Magnitude and characteristics of industry in the catchment area of the infrastructure
- Demographic statistics (population size and growth)
- Education statistics (current and future student body, percentage of population having
Socioeconomic completed tertiary education, etc.)
trend - Percentage of population employed in the education sectors
- Gross domestic expenditure in research and development (in absolute terms, as a share
of GDP, per capita expenditure)
- Degree of achievement of national targets related to the RDI sector
- Education background: number of graduates, students, educational specialisation
- Reference to EU sector policy documents (see above) and other horizontal policies
- Reference to the priority axis and the interventions areas of the OP
Policy and - Reference to the Regional and Innovation Strategy for Smart Specialisation (RIS3)
legislative
- Reference to national and regional strategic documents and development plans
framework
- Connection with other EU programmes and initiatives
- Reference to State aid legislation
- Geographical proximity to universities, industries and other research laboratories to favour
networking and collaboration
- Geographical proximity to the research object (e.g. as regards facilities for studying a
Geographical particular biological habitat)
conditions and - Proximity to ancillary services or facilities (e.g. housing and accommodation)
availability of
resources - Accessibility
- Number and specialisation of scientists and students in the infrastructure’s reference area
and field
- Availability of well-established technical engineering expertise in the infrastructure’s
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reference area
- Percentage of employees in the research and development sector
- Knowledge intensity of businesses in the region
- Number of patent applications and patent per capita in different economic sectors
Current level of - Scientific publications among the top 10 % most cited publications worldwide as a
research and percentage of the total scientific publication of the country
innovation - Venture capital investment as a percentage of GDP
- SMEs innovating in-house as a percentage of SMEs
- SMEs introducing product or process innovations as a percentage of SMEs
- Sale of new-to-market and new-to-business innovations as a percentage of turnover
- Current state of the existing infrastructures and facilities in the same
scientific/technological field
- Current number of research centres in the same field in the infrastructure’s reference area
and in other regions/countries
Conditions of the - Benchmarking with other RDI infrastructures operating in the same field in other
existing research regions/countries, e.g. in terms of availability of spaces and experimental areas in existing
facilities and
laboratories, scientific and technical characteristics of existing installations and equipment,
infrastructural
needs etc.
- Past and present scientific activity carried out by the project promoter, e.g. in terms of
research budget breakdown, number and value of research projects conducted,
publications, awards, scheduled directions of research
- Cooperation agreements with existing entities or other relevant research programmes
Source: Authors
7.3 Definition of objectives
RDI projects can be associated with a multitude of long-term objectives, including amongst others:316
contribute to the advancement of knowledge and maintaining Europe at a world-class level in
science and technology;
accelerate the development and deployment of innovative, enhanced, more efficient and higher
value added products, processes or services that meet the demand of customers and users;
strengthen the cooperation between research, innovation, education and business to create
more jobs and increase economic competitiveness;
enhance the attractiveness of a cluster or science park for investors and companies;
increase the number of graduates in specific fields to foster smart specialisation;
help address societal challenges in a number of fields, including, for example, energy security,
sustainable transport, climate change and resource efficiency, health and ageing,
environmentally friendly production methods and land management, etc.;
develop and strengthen the European Research Area by making national research systems
more effective, ensuring optimal transnational cooperation and competition among
researchers, and guaranteeing access and transfer of knowledge;
reduce the 'permanent' brain drain in certain geographical areas and/or scientific fields by
promoting the development of RDI infrastructures, which could persuade scientists and
students not to move elsewhere;
promote the mobility of researchers and associated exchange of ideas;
increase technological spillovers potentially generated from large-scale RDI infrastructures;
stimulate students to take up scientific studies and undertake a career in a specific scientific
316 The list is purely illustrative, drawing from several policy documents and project appraisal documents.
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field.
When defining the project objectives, the promoter shall always state how the project will help
contribute to specific national and EU policies, e.g. Horizon 2020, Smart Specialisation Strategy, as well
as the objectives of the relevant OP and priority axis.
7.4 Project identification
The proposed project must be described in detail as a self-sufficient unit of analysis.
When RDI investments consist of single-site facilities, i.e. a single or a set of infrastructure and
equipment located in a single physical location, as defined by ESFRI (2012), the project identification
becomes relatively straightforward. As an example, single-site RDI infrastructures include telescopes,
medical research facilities, laboratories for technological experimentation and others.
Geographically distributed RDI facilities, consisting of a network of infrastructures and equipment
located in different places (or even different countries), can also be identified as a self-sufficient
project if there is a strong functional relationship among all of its parts, meaning that the distributed
facilities cannot operate and/or produce RDI results without contributions from any of the facilities.
Examples of the distributed RDI infrastructures could be research centres in the field of climate
change, biosciences, geology, and with measurement stations or systems of satellites located at
different sites.
RDI investments aimed at fostering cooperation between a number of research facilities and
knowledge transfer/innovation facilities, which are located in the same area (e.g. city or region) but
are not incorporated within one single-site infrastructure stricto sensu, could still be considered as a
single project and a self-sufficient unit of analysis for the purpose of the CBA, as long as they create
strong synergies, critical mass and achieve cost savings for each facility involved. Project boundaries
need to be precisely traced and the rationale for conceiving separate infrastructures as a unitary major
project should by justified.
In any case, the proposed project should clearly aim at addressing a relatively well-defined research or
innovation objective. Investments merely focusing on the construction or purchase of new university
buildings not directly intended for research purposes, or an improvement in the energy efficiency of
research facilities should not be considered as RDI projects.
An indicative and far from exhaustive list of typical major RDI projects that are expected to be financed
by the ERDF are presented in the table below. For illustrative purposes, they are distinguished
between infrastructures mainly for (applied) research and development, those mainly for innovation
and those for both research/development and innovation, depending on the possibility of identifying
the prevalent activity carried out.
Table 7.2 Examples of typical RDI infrastructural major projects
Type of RDI Examples of major projects and activities/services offered
infrastructure
- Competence centres and laboratories and equipment specialised in a specific
(Applied) research technology or field (e.g. clinical research centre, microscopy facilities, laser light facilities,
and development laboratories for biological studies, etc.)
infrastructures - R&D centres and laboratories for research organisations (universities, research
institutes, other bodies)
- Facilities and/or equipment for developing and/or testing prototypes and innovation, not
yet intended for commercialisation (e.g. large-scale demonstrator to test innovation in a
real-life environment)
- Laboratories and equipment for single private enterprises to support the development,
testing and manufacturing of innovative products or services (e.g. pilot plants)
Innovation - Technology park including facilities for innovation: business incubators, innovation
infrastructures
centres, centres for experimental development, living labs, fab labs, Design Factory,
spin-offs, etc.
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- Science and technology parks, comprising applied research laboratories and innovation
facilities (business incubators, innovation centres, centres for experimental development,
living labs, fab labs, Design Factory, spin-offs, etc.)
Infrastructures for - Laboratories and equipment for aggregations of private enterprises, research institutes,
research, and universities, to support the development, testing and manufacturing of innovative
development and
innovation products or services
- Research centres with applications of research outputs to final users (e.g. clinical
research infrastructures developing new health protocols for the treatment of patients at
the centre)
Source: Authors
7.5 Demand analysis
As presented in Chapter 2, the demand analysis implies identifying the need for an investment, which
is expressed by the current and future demand. Quantifications of the demand in the scenarios with
and without the project are both essential for formulating the project demand projections in
incremental terms. The demand analysis should be carried out before the option, financial and
economic analyses, since it provides inputs that are necessary for the subsequent appraisal steps.
Different to other sectors, which are more focused on the delivery of a limited set of specific services,
the RDI sector has a particularly heterogeneous variety of possible projects, to which any number of
diverse drivers of demand can be associated. The demand of RDI infrastructures is actually driven by
the social and economic needs expressed by a multiplicity of target groups, i.e. stakeholders
who/which will ultimately benefit from the intervention. These may include both project users and
non-users, whose welfare will be affected by the construction, operation and services provided by the
infrastructure. Such multiplicity prevents any generic discussion about the demand analysis, which
should be based on the project specificities.
To simplify this, three macro categories of target groups, which drive the demand for the RDI project
at regional and/or national level, can be identified:
businesses, including SMEs and large enterprises, high-tech businesses, spin-offs and start-
ups, which enjoy the services provided by the project and/or the indirect spillover effects;
researchers, young professionals and students, who would use the RDI facility to carry out
their own research to increase scientific and technological knowledge in a given field, or for a
training programme;
target population and the general public, who are attracted by the project outreach
activities or who are the direct or indirect target of research.
In principle, the list may be broken down to a more detailed level of analysis (see below).
It is important to understand that not all categories of target groups may be involved in the same
project. In fact there is no rigid correlation between the taxonomy of RDI infrastructures introduced in
previous sections of this chapter (section 7.1 and 7.4) and the target group(s). Some categories of
actors but not others could potentially be involved in fundamental or applied research, development
and innovation infrastructures, depending on the specific project features. For example, hi-tech
businesses may be important as recipient, albeit indirect, of a fundamental research project, while they
may not immediately be involved as users in applied research.
For each identified target group, the project promoter has to examine those specific factors that could
influence the volume and trend of demand. Different methods can be used for demand projections, as
suggested in Table 7.3.
The project promoter should pay particular attention in dealing with uncertainty when forecasting
future demand from the potential target groups. Optimism bias in the identification and quantification
of the demand should be avoided and the risk attached to demand projections should be tested in the
risk assessment phase (section 7.9). Some hints on how to forecast future demand are provided in
section 7.8, with specific reference to the valuation of economic benefits.
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Table 7.3 Data, methods and outputs of the demand analysis
Target group Examples of factors driving the demand Possible methods for data gathering and Examples of output from the demand
estimation analysis
- Statistical analysis of historical data
- Average growth of the industrial base in the RDI project field in - Databases of financial information and - Annual number of spin-offs /start-ups
the last years other details about companies expected to be generated/supported by the
- Average annual profitability of the industrial base in the RDI - Track record of the business in producing project
project field patents and innovation in general - Expected number of businesses using the
- Knowledge intensity of businesses in sectors related to the RDI - Relevant literature and existing studies infrastructure to develop new/improved
project - Benchmarks with similar RDI projects products and processes
Businesses - Access to venture capital funds possibly stimulating the - Interviews, surveys, consultations - Expected annual number of patents
establishment of start-ups - Letters of intent for potential industrial registered by project users
- Level of public investment in fields related to the RDI project research collaborators - Expected trend of revenues from licensing
- Capacity of the incubator or other RDI facilities - Details for potential collaborative research and technology transfer
- Number of enterprises potentially interested in using the projects - Expected number of non-user businesses
services provided by the RDI project - Smart specialisation priorities and possibly enjoying knowledge/technology
- Level of involvement of enterprises in the governance of the allocation of budget resources in the spillovers
infrastructure related fields
- Number of scientists operating in the RDI project field and in the - Statistical analysis of historical data
geographical area targeted by the infrastructure - Relevant literature and existing studies
- Annual number of researchers who will
- Number of existing facilities operating in the same field and - Benchmarking with other similar, existing
directly use the RDI infrastructure
competing with the RDI infrastructure RDI facilities
- Number of scientific publications expected to
- Technical characteristics and scientific potential of the RDI - Scientometric analysis of publications and
be produced by the project users
Researchers, infrastructure citations in the RDI project field
- Number of citations expected to be received
young - Reputation and track-record of researchers - Demographic projections
by users’ publications
professionals - RDI project capacity to attract funding and users - Surveys, interviews, consultations to
- Annual number of young professionals and
and students - Current number of students in the RDI project field or related assess the attractiveness of the RDI sector
students who will use the RDI infrastructure
fields in the geographical area targeted by the infrastructure among students
- Duration of the training programme at the RDI
- Applicability of RDI skills acquired from the research project in - Unemployment rates of graduates / speed
infrastructure
the labour market to find employment after graduation
- Revenues from student fees
- Potential for generating income through student fees and private - Number of business scholarships
sponsoring sponsoring students’ fees
- Number of people affected by environmental and health risks - Annual number of people potentially targeted
and virtually targeted by the RDI project - Statistical analysis of historical data by the project
Target - Existence of knowledge transfer agreements to other RDI - Relevant literature and existing studies - Annual number of patients treated by
population infrastructures - Benchmarks with similar RDI projects innovative medical technologies
and general - Attractiveness and appeal of the RDI infrastructure among the - Interviews, surveys, consultations - Annual number of people potentially
public wider public interested in visiting the project or potentially
- Provision of outreach activities by the project promoter targeted by other outreach activities
- Price charged for guided tours or other outreach activities
Source: Authors
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7.6 Option analysis
The project that is proposed for implementation should be justified among a number of alternative
options. The option analysis aims at identifying the most promising project option that can achieve the
expected objective given a certain demand.
The baseline for the option analysis is the description of a scenario without-the-project for which
alternative options can be conjectured. It is important to bear in mind that all possible options should
be defined as alternative ways to achieve the same specific project objective, for example in terms of
performance improvement of products and process, an increase in research capacity, or local
development in the framework of a smart specialisation and place-based strategy. Projects aiming at
different objectives cannot be compared across each other.
RDI project options could differ one from another from multiple perspectives. When deciding to build,
for instance, a new competence centre, the project promoter faces a number of choices concerning the
project localisation in a given region or country, the technological solution employed for carrying out
experiments, and many other factors. A set of possible options can thus be described for each
particular aspect of the project (see the box below for some examples).
EXAMPLES OF STRATEGIC OPTIONSS IN THE RDI SECTOR
Listed below are some examples of alternative options that are likely to be presented in the option analysis of
RDI projects.
- Strategic options: A set of alternatives (e.g. A, B, C, D) which may concern the structure of the overall project.
For example, alternative A may involve the regrouping of different research centres, while B proposes the
construction of a new research facility.
- Technological options: A set of alternatives (e.g. A, B, C, D), which may concern different technologies to be
purchased by the project. Several (more or less sophisticated and cost-intensive) technological set-ups may
be available on the market, which allow carrying out the proposed research.
- Location options: A set of alternatives (e.g. A, B, C, D) which may concern the location or the geographical
set-up of the project. For example, a higher education and research infrastructure project may be located in
one of several locations, or split between a number of different locations. In other cases, the choice could be
about whether to build the RDI facility in one city or in another, or in the urban centre rather than in the
suburbs or countryside.
- Architectural options: A set of alternatives (e.g. A, B, C, D) that concern the architectural design of the
building where a project is located. For example, a research centre may be located in a newly built building or
in an old refurbished building.
Source: Adapted from JASPERS (2013)
Each option should be assessed against a number of criteria, such as:
its expected costs,
expected revenues,
expected economic benefits, including positive and negative externalities,
possible wider regional effects,
implementation time,
degree of uncertainty and the risk involved.
Options should be compared across each other by means of both a multiple criteria analysis and a
simplified CBA, where rough estimates of financial and economic flows are used to calculate financial
and economic performance indicators. See Chapter 2 for details. The proposed project should be the
one that combines the best performing alternative options within each range of available options, in
such a way that it allows the greatest benefits to be achieved in the most efficient way. When a similar
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economic impact is expected to be achieved using different options, the preferred option can be
selected by considering either the financial net present value (the lower the financial net present value
the more efficient the project is) or other qualitative aspects arising from the multi-criteria analysis.
7.7 Financial analysis
7.7.1 Investment, operation and maintenance costs
Categories of financial costs, which are generally related to RDI infrastructures, are synthetically
presented in Table 7.4 below.
Table 7.4 Typical investment, operation and maintenance costs of RDI infrastructures
Investment cost O&M costs
- Materials and equipment
- Planning and design costs
- Consulting services
- Land acquisition
- Cost of scientific personnel
- Construction costs, possibly disaggregated by
- Cost of administrative and technical staff
civil works and installations, materials, labour,
- Cost of obtaining and maintaining patents
etc.
- Energy, waste disposal and other utilities
- Energy, waste disposal and other utilities
- Promotional campaigns and other outreach
consumed during the construction period
expenditure targeted to the general public
- Road access
- Training courses connected to the infrastructure’s
- RDI equipment, including information
operation and management
technologies (particularly for data storage or
- Removal of potential pollutions / brownfield site
elaboration)
treatment at the end of the life cycle of the
- Intellectual property purchase costs
infrastructure
- Testing
- Start-up costs
Source: Authors
Cost savings in O&M or investment achieved through the project's implementation should also be
accounted for and included on the cost side of the analysis, as a negative, i.e. as decreasing costs in
respect of the counterfactual situation.
ABOUT IN-KIND CONTRIBUTIONS IN FINANCIAL AND ECONOMIC ANALYSES
The project promoter may not pay for goods, services and staff for the construction or operation of the project;
external parties may provide these in-kind. This is not unusual for investment projects promoted by public
research bodies and universities. In-kind contributions should be treated as follows:
- in the financial analysis, in-kind contributions are not to be included among the project’s costs because they
do not represent an actual cash flow for the project promoter;
- the corresponding economic value of in-kind contributions should be included on the cost side of the
economic analysis, where all project-related costs for society have to be considered;
- the residual value of in-kind material and equipment provisions should be considered in both the financial
and economic analyses.
7.7.2 Revenues and financing sources
RDI infrastructure projects can gain revenues from the provision of a variety of services to public and
private users. Services provided and revenues attained may vary greatly from one project to another.
Table 7.5 below shows a (non-exhaustive) list of typical inflows that shall be considered as operating
revenues.
As compared to other types of projects, RDI facilities are more often than not largely dependent on
public financing sources and these financing sources can be very diversified. Besides the
national/regional capital contributions that are common to all projects, there could be a variety of
other contributions to the research project, granted by European, national or regional public and
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private parties. Such financing mechanisms may vary widely across countries in their characteristics
depending on the country-specific institutional set-ups.
The project promoter should carefully assess whether a financial inflow, particularly if granted by a
public institution or agency, should be considered as either a source of financing or operating
revenues. In general, research contracts or contributions granted from the public sector, either
through competitive or non-competitive arrangements, should be considered operating revenues (and
therefore included in the financial profitability analysis and in the calculation of the discounted net
revenue, in line with Article 61 of Regulation 1303/2013) but only if they are payments against a
service directly rendered by the project promoter. This condition is often verified when the ownership
of the expected research output is transferred to the contracting public entity and does not remain
with the research institution. For example, a grant awarded by a regional public agency to a public
research body, directed to the development of a new software usable in the regional hospitals, or a
new type of railway signalling system to be installed on the regional railway lines, can be considered a
fully-fledged operating revenue for the research project.
Instead, public research funding schemes aimed at covering (part of) the operating cost born by the
project promoter, but without involving a transfer of the research output’s ownership, shall be
considered as sources of financing, but not operating revenues. Following the regulatory provisions 317
and in line with the general CBA methodology put forward in section 2.8.4 of this guide, these
financing sources shall be considered as 'transfers from state or regional budgets'. As such, they shall
not be included as revenues for the calculation of both the financial performance indicators and the
determination of the Union assistance. However, they account for the verification of the financial
sustainability. Examples of this category of financing sources include grants from European or national
research funding frameworks (such as Horizon 2020), regular or exceptional donations from the State,
contributions by the National Health Service to university hospitals, etc.
The degree of uncertainty attached to the acquisition of special public research funding, meant either
as operating revenues or sources of financing, over the project’s lifetime is often very high and this
could significantly affect the project’ sustainability and profitability indicators. In this regard, the
project promoter should avoid excessive optimism bias. The uncertainty attached to project inflows
should be duly discussed and analysed, even by means of the risk assessment set of procedures.
Table 7.5 Typical revenues and sources of financing of RDI infrastructures
Examples of operating revenues Examples of financing sources
- National/regional public contributions
- Licence revenues gained from patents’
- National/regional private contributions
commercialisation
- EU contribution
- Sale of consultancy services
- Other national/regional funding schemes
- Revenues from industrial research contracts and pre-
for RDI activities
commercial procurement contracts
- Public grants to research, e.g. under the
- Entry fees to the laboratory and for the use of research
Horizon 2020 framework
equipment charged to researchers and businesses
- Ordinary public transfers
- Student/master/PhD fees
- Spin-off equity realisations
- Research grants involving a transfer of ownership of a
specific research output
- Sale or rent of new buildings used for the project’s
objective
- Revenues from the target population using the research
outputs (e.g. patients receiving an innovative treatment)
- Revenues from outreach activities to the wider public
(e.g. bookshops’ sales, entry fees, etc.)
Source: Authors
317Article 16 (Determination of revenues) of Commission Delegated Regulation (EU) supplementing Regulation No 1303/2013, C(2014) 1207
final, Brussels, 3.3.2014.
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7.8 Economic analysis
7.8.1 Structure of the section
The main difficulty, which has often discouraged the use of a proper CBA in the context of RDI
infrastructures, is the estimation of the social benefits from a range of diverse projects, which may
span from research centres on climate change to scientific and technological parks, or from high-
energy physics research infrastructures to bio-molecular research facilities. Some guidance is offered
below about the practical estimation of social benefits. The perspective, as for the rest of the guide, is
ex ante, when uncertainty about the benefits of the RDI infrastructure is greatest.318
The presentation of the economic analysis is structured as follows. Having identified in the previous
sections the activities and services generally delivered by RDI infrastructures, as well as the main
categories of (user and non-user) stakeholders or target groups, a list of typical benefits can be
pointed out for each target group (section 7.8.2). For every benefit, in turn, possible approaches for
forecasting the quantities of benefit output over the project’s time horizon and giving them an
economic value are examined. Then, section 7.8.6 briefly deals with the special angle of impact on
regional development and competitiveness, and section 7.8.7 shows possible future methodological
development in the context of fundamental research projects.
7.8.2 Typical benefits
In order to value the social benefits of any project, as a first step the project proposer needs to
understand who is going to be targeted, either directly or indirectly, by the services provided by the
infrastructure. Typologies of actors targeted by the project should have already been identified for the
purpose of the demand analysis (see section 7.5). As a next step, the following questions need to be
addressed:
how is the benefit for each target group defined and how can it be measured in quantity terms?
how can the quantities of benefits be predicted over the time horizon of the project?
how is the marginal social value of the benefit estimated?
The total economic value of the expected benefits is then obtained as a benefit quantity times their
marginal social value. These basic notions of CBA are repeated here because they should be firmly and
consistently applied in the domain of RDI infrastructure, without being discouraged by the special,
various and challenging nature of their design and operation.
In what follows, typical benefits enjoyed by the three main categories of target groups related to RDI
projects and already listed in section 7.5 (businesses; researchers, young professionals and students;
target population and general public) are discussed. For the sake of clarity, it is useful to break down
the list of broad categories of target groups into more specific items.
Benefits for businesses319
This category of target group is particularly heterogeneous and could potentially include a large
variety of actors, either users or non-users of services offered by the project. A possible list of targeted
businesses is provided below.
New businesses, i.e. technological start-ups and spin-offs established via the project
implementation and/or those enjoying the services provided by the incubators and similar
infrastructures: these businesses could experience different kinds of benefits, such as
decreased business mortality, avoided cost due to the services provided by the RDI facilities,
and the development of new or improved products and processes.
318 Given the importance and novelty of CBA in this area, the managing authorities may also be interested in ex post CBA of existing RDI
infrastructures to learn from experience, but this is outside the scope of this guide.
319 In fact, as businesses are legal entities owned ultimately by investors, the true ultimate beneficiaries are the shareholders. For the sake of
simplicity, however, benefits are referred to the businesses.
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Already existing businesses, which can include the following:
o Large businesses involved in applied research infrastructures, or competence centres
shared with universities, other businesses and third parties: the potential benefits for
large businesses are the development of new products and processes, in some cases
leading to patents or other forms of protection of intellectual property.
o SMEs benefitting from activities and services offered by technological parks and other
collective infrastructures supporting R&D: potential benefits could be knowledge
spillovers and support to the development of new or improved products and processes.
Inventions by SMEs more often than not come from the adaptation of existing
knowledge to new fields, and they are not always protected through patents.
o Any other business, either SME or larger, either high-tech or not, which is able to avoid
some costs or increase sales because of the impact of new knowledge, spilling over
from the research infrastructure as a positive externality. This category comprises,
among others, high-tech businesses in the supply chain of the RDI infrastructure,
contributing to the development of innovative equipment, materials and software, and
benefitting from learning-by-doing effects.
Benefits for researchers, young professionals and students
Academics and researchers involved in the design, operation and use of experimental
machines of fundamental and applied research facilities, and other academics benefitting from
the new scientific literature created: the potential benefit enjoyed by academic researchers are
publications and citations in scholarly journals; less frequently the benefit could take the form
of registration of patents or other forms of intellectual property protection.
Young researchers within businesses or outside academia: an increase of human capital
benefit can be ascribed to this category of actors, particularly when young professionals, post-
doctoral researchers and early career researchers are involved; the increase of social capital
through networking with peers and established researchers can be another possible benefit.
Students, usually at graduate level, for example involved in training or the preparation of their
doctorate (PhD) dissertation with fieldwork at the research infrastructure, less frequently at
the technological development and innovation infrastructure. As with young researchers,
students could enjoy the human capital and social capital development effects.
Benefits for the target population and general public
Population in areas of environmental risk: Due to the new research or surveillance methods
developed in the RDI infrastructures, the population could benefit from the costs avoided and
lives saved in relation to major risks, such as the effects of climate change, earthquakes, floods,
fires, pollution, etc.
Population at health risk: This category includes patients associated with medical or
pharmacological research infrastructures in the field of new therapies, or other members of
the public targeted by the RDI project who experience health benefits in terms of avoided
mortality and increased quality of life. Other patients (non-users of the research
infrastructure) may also benefit from knowledge spillovers to other contexts.
General public interested in science and technology arising from onsite visits to the
infrastructure, virtual visits to the project’s websites and social networks, availability of
educational publications and information in the media as part of the outreach activities of the
team managing the RDI infrastructures. The related use-benefit is in terms of cultural effects,
valued through the marginal willingness-to-pay for this form of cultural activity.
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Browsing the above-mentioned types of benefits (listed in the Table below),320 it can be observed that
some of them recur for different types of target groups. For instance, the value of patents as a potential
benefit may accrue to large businesses, SMEs, academic scientists or inventors outside academia. Also,
it should be borne in mind that the intensity of each benefit may be highly variable across the different
typologies of RDI infrastructures. For example, the social benefit of human capital change is highly
relevant for applied research infrastructures, where students are often involved in research activities,
but is less relevant for technological development and innovation infrastructures. However, many
projects may combine some ingredients of the main types of RDI infrastructures (i.e. infrastructures
for research, technological development or innovation), and only a case-by-case appraisal can tell
which category of benefit is more or less important for a specific project.
Table 7.6 Target groups, benefits and related evaluation approach: an illustrative synopsis
Benefit Evaluation Target groups
approach
Businesses Researchers, young Target population and general
professionals and students public
Already Spin- Academi Research Student Target Target General
existing offs cs and ers within s populat populati public
busines and research businesse ion at on at
ses start- ers s or environ health
ups outside mental risk
academia risk
Establishment
of more
numerous or Shadow
++ + + +
more long-lived profit
start-ups and
spin-offs
Development of Shadow
new/improved profit or
++ ++ + +
products and value of
processes patents
Knowledge Shadow
spillovers to profit or
++ +
non-user avoided
businesses cost
Value of Marginal
scientific production ++ +
publications cost
Incrementa
Human capital
l lifelong ++ ++
development
salary
Social capital Qualitative
+ ++ ++
development analysis
Reduction of Avoided
environmental cost or + ++
risk WTP
Reduction of VOSL or
++
health risk QALY
Cultural effects WTP ++
Note: ++ very relevant; + moderately relevant; VOSL: value of statistical life; QALY: quality-adjusted life year. Source: Authors
320 There may be other benefits that the evaluator can discuss in the CBA of a specific project. For example, building a new, more energy-
efficient laboratory that substitutes an old one may produce benefits in terms of less CO 2 produced and avoided costs for the project
promoter. These benefits may be important in specific cases, but are not typical of RDI projects, and thus they are not discussed in this
chapter.
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7.8.3 Valuation of benefits to businesses
Businesses can experience a variety of benefits, depending on their relationship with the RDI project.
Benefits can be in the form of the establishment of spin-offs and start-ups, the development of new or
improved product and processes (possibly, but not necessarily, leading to patents), the provision of
special services to user-businesses and knowledge spillovers to non-user businesses.
Whatever the benefit experienced by businesses is, the general rule is that any change beneficial to a
business should be valued by incremental shadow profits, as compared to the without-the-project
situation. This is in line with the CBA concepts and methodology described in Chapter 2. For the sake
of simplicity, in what follows, the notion of ‘profit’ (instead of ‘shadow profit’) is used, with the
understanding that market distortions should be taken duly into account. For example, if targeted
businesses are located in areas characterised by high unemployment, the shadow profit will be higher
than the gross financial profit321 because the shadow wage will be lower than the market wage.
Forecasting expected profits may not be an easy task, mainly because of the confidentiality of
information. There are, however, different possible approaches to predict changes in a business's
profits, which the project proposer could consider.
For example, for most large businesses or certain categories of business (e.g. for pharmaceutical
research companies or enterprises in other specific NACE322 sectors) information about profitability,
average costs and sales is available. Databases in the public domain or granted by data providers offer
valuable information in this respect. Other useful information is anticipated from the European
Commission’s ongoing study of the average profitability and performance of selected economic
sectors.323 Also, in some cases, some disclosure is possible, particularly when compliance with the EU
State aid needs to be proven. Benchmarking with similar RDI infrastructures in other contexts could
also offer some input to forecast future profits.
Direct estimation of effects of a RDI infrastructure on future profits of SMEs could be even more
complex, as official data for micro and small enterprises are usually limited. However, interviews or
comparisons with other similar experiences can help to make a conjecture of possible changes in the
profitability of businesses, to be tested by the appropriate risk analysis, as discussed later.
Some more detail about estimating the typical benefits of RDI projects for businesses are presented.
Given the very specific nature of each RDI project, additional benefits, which do not precisely fit into
the list here indicated, may still exist. However, the evaluation methodology is not expected to be
significantly different: in general, the benefit to businesses can always be valued through incremental
shadow profit. When more relevant or practical, the avoided cost approach could also be applied, as
explained below.
Establishment of spin-offs and start-ups
Spin-offs and start-ups are companies engaged in activities with a strong high-tech and innovative
business component. While a spin-off is born from the split of an already existing entity into two or
more separate units, a start-up is a new entity created from the influence of an existing company or
research organisation (e.g. a university). For the purpose of the CBA, the creation of spin-offs and
start-ups are considered under the same typology of benefit, since the methodology of valuation is
very similar. The mission of spin-offs and start-ups is to develop and bring to the market new products
or services that originate from an initial knowledge input transferred from the parent company or
organisation. The establishment of spin-offs and start-ups can be one of the intended objectives of
321 Typically looking at earnings before interest, taxes, depreciation and amortisation (EBITDA).
322 Nomenclature Générale des Activités Économiques dans les Communautés Européennes.
323 'Study to determine flat-rate revenue percentages for the sectors or subsectors within the fields of (i) ICT, (ii) research, development and
innovation and (iii) energy efficiency to apply to net revenue generating operations co-financed by the European Structural and Investment
Funds (ESI Funds) in 2014-2020', implemented by CSIL, Centre for Industrial Studies, in association with T33, on behalf of the European
Commission, Directorate Regional and Urban Policy., Service contract No 2013CE160AT111.
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innovation infrastructures, as in the case of incubator centres, but is can also be a side effect of
fundamental and applied research infrastructures.
The economic benefit arising from the creation of new business units has often been valued, in past
project appraisals, by looking at the economic value of the jobs created. However, this approach is not
consistent with the CBA theoretical foundations. The economic value of spin-offs and start-ups should
be valued as the expected shadow profit gained by the business during its lifetime, as compared to
the counterfactual situation. In order not to commit double counting, the spin-off equity realisations
and the operating revenues from the sale of consultancy services leading to the establishment of spin-
offs and start-ups, which are included in the financial analysis, should not be considered in the
economic analysis.
If the RDI infrastructure contributes towards increasing the survival rate of start-ups, the benefit is
valued as the expected profit attained by newly created businesses, which survive longer than
businesses in the baseline scenario (see a worked example in the box below). Whenever it is
reasonable to believe that the main contribution of the RDI project would not be to increase the
survival rate of start-ups, but to increase the absolute number of start-ups in the region, then the total
expected profit gained by all newly created businesses during their expected lifetime should be
included in the analysis. The latter situation can be expected to occur in some circumstances and
typically in particularly deprived areas.
An ex ante estimate of the profit of spin-offs and start-ups should be based on the following:
the annual and total number of spin-offs/start-ups expected to be generated by the RDI
infrastructure;
the expected value of annual profits earned by spin-offs/start-ups in the considered country
and sector;
the average lifetime of spin-offs/start-ups in the considered country and sector.
Such variables can be inferred from official statistics (at regional, national or, where not available,
European level) or relevant literature. As far as possible, sector specificities should be taken into
account. Official data about similar RDI infrastructures and their own spin-offs/start-ups, located in
the same or other regions and countries, could be taken as reference where available.
The benefit for the establishment of any new business should be estimated for the overall expected
lifetime of such a business. It is thus very likely that some benefits would continue after the last year of
the RDI project’s time horizon. The project promoter should make sure that the residual value of the
benefit, properly discounted at the social discount rate, is imputed in the last year of the CBA time
horizon.
THE VALUE OF SPIN-OFF AND START-UP CREATIONS: EXAMPLE OF ESTIMATION
This box presents an example of the valuation of the benefit related to the creation of start-ups. All figures and
assumptions hereby reported have a purely illustrative purpose and should therefore not be taken as reference
values. The project proposer is invited to rely on project-specific assumptions and sources, and to duly justify the
choice of any input value.
In this example, a technological park, provided with an incubator centre for high-tech start-ups, is expected to
support 100 enterprises during its time horizon. It is assumed that the average profit of the assisted companies
for the first three years will be zero; it then increases to EUR 0.5 million per year (including taxes, interests and
the correction for the shadow wage). The social benefit is the difference between the baseline estimate of the
profits of the enterprises supported by the project and the counterfactual situation, where a higher mortality
rate of businesses is considered. Thus the profit on the additional surviving businesses should only be computed.
The literature and available studies can give indications about the survival rate of start-ups in specific countries
and sectors. The graph below shows some illustrative examples. For example, according to Eurostat business
demography statistics (Eurostat, 2009), 50 % of all enterprises started in 2001 survived to 2006. According to
the Innovation Union Competitiveness Report 2011 (European Commission, 2011), the survival rate of business
enterprises established in EU countries in 2003 was between 50 % and 85 % after five years, depending on the
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country. The European Investment Bank (EIB) (2013) assumes a probability/success rate of 50 % for the
average newly created businesses over 15 years.
Examples of start-ups survival rate curves
100%
90%
80%
70%
Survival rate
60%
50%
40%
30%
20%
10%
0%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Years after foundation
Source: Authors, drafted for purely illustrative purposes.
In the considered worked example, the standard survival curve for high-tech businesses in the region where the
RDI infrastructure is going to be located indicates that, on average, 30 % of newly established businesses survive
after ten years. Based on the evidence from other similar RDI facilities, the project promoter expects that 50 % of
newly born businesses, which will receive support by the RDI facility, will close within ten years: in other terms,
the support services provided by the project are expected to help reduce a business's death rate. At year 10,
there will be 50 surviving businesses in the incubator against 30 on average in the region. Thus the net effect is
20 more surviving businesses that will still be in operation ten years after their establishment.
The present value of the expected stream of profit for these additional 20 businesses must be computed as a
project benefit. It is clear that the benefit value would be highly sensitive to the expected profitability and the
survival rates of businesses assisted in the incubator. The appropriate risk analysis shall be implemented to test
the impact of these critical variables.
Development of new/improved products and processes
When the RDI infrastructure can be associated with the development of new or improved marketable
goods, the changes in shadow profit expected from the sale of such goods should provide the estimate
for the benefit. The general remarks made above still apply.
When patents are registered at national, European or other patent offices, the benefit can be estimated
by the economic value of patents, provided that double counting with the change of expected profit
from the sale of RDI outputs is avoided. In fact the expected value of a patent, in principle, already
incorporates the 'difference between the discounted stream of (shadow) profits since the grant of the
patent when the inventor holds the patent, and the equivalent discount stream of (shadow) profits
without the patent' (European Commission, 2006: 4).
Attention should also be paid to not including in the economic analysis the financial revenues coming
from licences, revenues from research contracts and grants, and entry fees paid by user companies
ultimately aimed at the development of new/improved products and processes.
When patents are expected as an output of the project, there are two distinct evaluation issues to
tackle.
First, the number of patents over time should be predicted. This forecasting exercise is obviously
difficult, but the project proposer may gather some indications from the beneficiary's track record on
patenting. As a next best option, the project proposer may refer to observable data related to other
regions, or other infrastructures if available. Statistics about the average number of patents registered
at the National or European Patent Offices (EPO) and about the number of scientists, possibly by
sector and at the relevant geographical level (either Nomenclature of Territorial Units for Statistics,
NUTS, level 0 or 2,), could be collected from Eurostat or national statistic institutes or other official
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sources324. These sources may suggest a range of possible forecasts for the number of project’s
patents, which should be tested with an appropriate risk analysis.
Second, the marginal value of the patent should be estimated. It is acknowledged that this value
changes greatly across sectors, but there are some empirical studies on this topic that could be taken
as reference. As an example, the 'Study on evaluating the knowledge economy. What are patents
actually worth? The value of patents for today’s economy and society', published by the European
Commission in 2006, analyses the distribution of patent values registered at the European Patent
Office between 1993 and 1997. The analysis relies on a questionnaire survey to almost 10 000
inventors in eight European countries. Patents belonging to different technology classes have been
considered. This study shows a very skewed distribution, with a median value of patents between
EUR 250 and EUR 300 000 and an average value equal to EUR 3 million.
The PatVal EU project (European Commission, 2005) estimates that the value of European patents is
usually between EUR 100 000 and EUR 300 000, with a small share of patents yielding to economic
returns that are higher than EUR 3 million, and an even smaller share that are valuing more than
EUR 10 million. As highlighted by the EIB (2013), patent brokers suggest lower average values of
marketable individual patents in the United States of America of between EUR 57 500 and
EUR 85 000.325
Other studies exist and the project promoter is invited to consider the one that provides the most up-
to-date and appropriate estimate for the value of patents. The expected value of patents in the country
or region where the RDI facility is going to be located and in the appropriate technological field should
be considered when available.
THE VALUE OF PATENTS: EXAMPLE OF ESTIMATION
This box presents an example of the valuation of the benefit related to the registration of new patents. All figures
and assumptions hereby reported have a purely illustrative purpose and should therefore not be taken as reference
values. The project proposer is invited to rely on project-specific assumptions and sources, and to duly justify the
choice of any input value.
The forecast of the number of patents registered every year by researchers working at the RDI facility under
appraisal can rely on their demonstrated ability to produce innovation and marketable patents. As an alternative,
the project promoter can consider existing statistics about the number of patents granted and the number of
research and development (R&D) personnel in a given area. A correlation can be assumed between the number
of patents and R&D personnel. For example, if statistics indicate that, in the considered region, it is granted, on
average, one patent for every 60 researchers, and the R&D infrastructure is envisaged to accommodate up to 180
researchers, the project can be expected to generate about three patents per year. Corrections by technological
sector shall be considered. Even when no historic region or country-specific data is available, a minimum and
maximum number of patents per RDI personnel per year can be conjectured based on evidence referred to from
other countries: the project promoter can then indicate the number of patents per researcher that is expected
from the RDI infrastructure within such a range.
For a purely illustrative purpose, the following graph shows the correlation pattern between patent applications
and R&D personnel as a share of total employment in selected countries in 2005. It is important to note that the
relevant variable to be considered for the CBA is the number of patents granted by the National Patent Office,
EPO or others, and not patent applications. When only the patent application statistics are available, an
assumption should be made about the number of applications that will eventually be registered. This correction
is aimed at only considering patents with a real commercial value and to discard possibly low-quality patents.
Reference to already existing studies on the commercial exploitation of patents can be made (e.g. European
Commission, 2005, European Patent office website326, etc.)
324 For example, the World Intellectual Property Organisation (WIPO): http://www.wipo.int/ipstats/en/
325 These minimum and maximum values have been used by JASPERS to value, respectively, the national and international patents (JASPERS,
2013).
326 http://www.epo.org/about-us/annual-reports-statistics/statistics/granted-patents.html
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Correlation between patent applications to the EPO per million inhabitants (log scale) and R&D
personnel as a share of total employment – 2005
Source: European Commission (2006)
The second step consists of providing an estimate of the patent portfolio that the RDI facilities will establish, as
compared to a benchmark patent value.
For example, if the project’s RDI personnel is expected to register an average number of three patents per year
and each of them is assumed to value EUR 100 000, the annual non-discounted benefit would be EUR 300 000.
Given the high variability (and ex ante uncertainty) of the possible number and value of patents, different
assumptions can be tested through the probabilistic risk analysis.
Knowledge spillovers to non-user businesses
RDI infrastructures can produce knowledge spillovers to non-user businesses. For example, if the RDI
infrastructure is committed to developing new technologies (or goods, software, etc.) and releases
them in the public domain without any form of intellectual property protection (e.g. because the RDI
project promoter is a public entity), external users that use such technologies for their own sake would
gain a benefit. The social benefit could be valued as the incremental shadow profit that the external
business can be expected to accumulate thanks to the transferred technology.
Alternatively, instead of looking at increased profitability, in some cases it could be more practical to
focus on avoided costs for businesses, which no longer need to develop the technology that has been
made available for free (or at a very low price) by the RDI infrastructure.
The same approach would apply in the case of learning-by-doing benefits, which are enjoyed by high-
tech suppliers involved in the design, construction or operation of infrastructures operating at the
forefront of science (usually fundamental or applied large research facilities). Businesses which have
the opportunity of acquiring new knowledge and technological skills spilling over as externalities from
the RDI facilities may use such knowledge to produce further technological advancement and increase
their sales performance and competitiveness. Even in these cases, the benefit could be captured by the
change in shadow profit of non-user businesses attributable to the RDI project, or avoided costs.
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KNOWLEDGE SPILLOVERS TO NON-USER BUSINESSES: EXAMPLE OF ESTIMATION
This box presents an example of the valuation of knowledge spillovers to non-user businesses. All figures and
assumptions hereby reported have a purely illustrative purpose and should therefore not be taken as reference
values. The project proposer is invited to rely on project-specific assumptions and sources, and to duly justify the
choice of any input value.
A public sector research project aims to find a new energy-saving process for the production of a given item and
the project promoter is committed not to patent the research results. Only ex post it will be known if the project
is successful; however, ex ante technologists may offer an estimate on the probability of the project being
successful and a range of energy-saving results achievable (for example, due to preliminary evidence available
through theoretical or pilot studies).
For instance, a RDI facility aims to investigate innovative combustion and gas turbine technology and offers open
access to academic researchers and businesses. The results of experimentations are public and the project
promoter envisages releasing information about the technological progress achieved through open conferences.
Businesses that have not been involved in the experimentation process as users of the facility could still enjoy
some benefit by absorbing the new knowledge produced by the RDI project that was released in the public
domain. The new technology allows the businesses to significantly improve their own production processes.
The related social benefit will then be the avoided cost for each business to develop the same new/improved
technology times the number of targeted businesses. In this case, if the application of the innovative technology
allows the energy savings in the businesses' production process to be achieved, then the benefit would be equal
to the avoided energy cost for each business over a certain time horizon.
7.8.4 Valuation of benefits to researchers and students
The value of scientific publications
For scientists and researchers, one of the main benefits of working within a research infrastructure,
either for applied or fundamental research, is the opportunity to access new experimental data, to
contribute to the creation of new knowledge and, ultimately, to publish scientific papers in scholarly
journals. Thus, the unit benefit is the marginal social value of the scientific publication.
The marginal value of the publication can be estimated by its marginal production cost. This
approach to account for benefits is entirely consistent with the standard approach described in
Chapter 2, when marginal cost is a proxy of the shadow price of goods for which market prices are not
appropriate.327
Thus the value of one paper in money terms may be estimated by the ratio of the salary of the author
scientist over the number of publications per year. Other knowledge outputs, such as working papers,
pre-prints and talks at conferences, can also be considered and valued according to the same marginal
production cost approach.
The salary of the academic researcher should be considered only for the time dedicated to research.
Data on the salaries of scientists and the average number of publications per year according to
different scientific fields can be found in various data sources. Predicting the number of papers
produced can be influenced by the standards of the personnel who are expected to be recruited for the
research infrastructure.328
327 As is the case with most of the scientific literature, which is available to readers for free at a very low price.
328 In some cases scientometric indicators may be used to state the track-record of a scientist. An example is the H-index, which is based on
the distribution of citations received by a given publications (Hirsch, 2005).
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VALUE OF PUBLICATIONS: EXAMPLE OF ESTIMATION
This box presents an example of the valuation of scientific publications. All figures and assumptions hereby reported
have a purely illustrative purpose and should therefore not be taken as reference values. The project proposer is
invited to rely on project-specific assumptions and sources, and to duly justify the choice of any input value.
In this example, the average gross salary of a scientist, who is a user of the RDI infrastructure, is EUR 60 000 per
year, the time devoted to research is 50 % (the remainder being for teaching and managerial duties) and the
number of published papers expected per year is three. The marginal cost per paper is then EUR 10 000:
60 000*50 %/3. For simplicity, a linear relationship between the value and the number of publications can be
assumed and the total value of publications produced over the project’s time horizon can be estimated.
Additionally, whenever deemed relevant to the specific project, the value of the papers can be
increased in proportion to the number of citations they receive by non-user academics who benefit
from the new scientific literature created by the project users. Different approaches can be proposed
by the project appraiser to forecast the dissemination process of scientific knowledge transfer through
citations (e.g. by resorting to scientometric techniques) and to attribute a value to citations, provided
that they are in line with the general principles of CBA. This additional effect could be important for
fundamental and applied research infrastructures, while it is more limited and often negligible for
innovation-focused infrastructures.
If scientists are expected to generate new patents, the same valuation methodology presented in the
previous section applies.
The benefit of human capital development
The main benefit that could possibly be expected for junior researchers and students involved in the
project is a ‘premium’ to their future salary, resulting from the acquisition of human capital that would
have not been accumulated without their participation in the project.
The premium is the incremental lifelong salary earned by young researchers and students over their
entire work career, as compared to the without-the-project scenario. The estimation of such a future
premium may require benefit transfer approaches from other contexts, interviews and expert opinion
by specialists in the labour market of interest.
It is also important to note that a relatively small premium may accumulate over the years (for
example during a researcher's 35-40-year career). For research infrastructures that attract many
students or junior researchers, the aggregate value of the benefit may be non-negligible. This benefit
would also be important for research and development laboratories of higher education institutions.
Note that benefits produced beyond the project’s time horizon should be included within the residual
value of the analysis.
An equivalent and alternative approach would be to estimate the WTP for junior researchers and
students to attend a training and study period at the RDI infrastructure. Similar to being admitted to
prestige universities, students may be willing to pay a fee to access a research infrastructure, on
account of the increased salary they expect to earn once they enter the labour market. The estimated
WTP must be included in the economic analysis, in place of the financial revenues from student fees.
THE VALUE OF HUMAN CAPITAL DEVELOPMENT: EXAMPLE OF ESTIMATION
This box presents an example of the valuation of human capital development. All figures and assumptions hereby
reported have a purely illustrative purpose and should therefore not be taken as reference values. The project
proposer is invited to rely on project-specific assumptions and sources, and to duly justify the choice of any input
value.
It is assumed that an applied research centre, operating for 20 years, hosts 100 students every year for a training
period, for a total of 2 000 students. After their training period, former students are expected to immediately
enter the labour market. Depending on the professional sector, the average gross annual salary can be easily
derived from available national statistics or benchmarks from other similar contexts. In this example it is
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assumed that former students will earn an average annual gross salary of EUR 50 000.
Interviews with students, professors and other experts suggest that participation in the training programme
offered by the research centre may generate a salary premium of, let’s say, 5 % over the total future salary as
compared to the project-specific counterfactual situation (e.g. a training programme in another research facility
or no on-the-job training at all). This corresponds to a non-discounted benefit of EUR 2 500 per year per student.
Assuming a work career of 40 years, the non-discounted benefit amounts to EUR 200 million: 100*20*2 500*40.
The total discounted benefit can be estimated as the present value of the total annual incremental salary gained
by all students trained during the project time horizon over their entire work career. Even after discounting, the
benefit could still remain very significant.
To be more rigorous, one may decide to consider, instead of an average salary, the salary curve associated with
students during their whole forthcoming work career. The graph below shows some examples for such salary
curves. They refer to the expected salaries of doctoral students in the United States of America (USA), depending
on the professional sectors of employment. Other sources may exist at European and national level. For example,
the Annual Survey of Hours and Earnings 329 of the United Kingdom's Office for National Statistics provides the
average pay for a large variety of professions.
Example of salary curve for USA workers in different professional sectors
100 000
100,000
90 000
90,000
80 000
80,000 Industry
Annual gross salary (EUR)
70 000
70,000
60 000
60,000
50 000
50,000 Others (computing,
40 000
40,000 financial, public
administration, etc.)
30 000
30,000
20 000
20,000
Academia and other
10 000
10,000 research centres
00
0 10 20 30 40
Years of career
Source: Authors’ elaboration based on PayScale data (www.payscale.com): the logarithmic function has been estimated from the expected
salaries at four different career level.
The benefit of social capital development
There is an increasingly important academic literature in applied economics about the socioeconomic
value of social capital, i.e. the dimension and depth of the network of relations among individuals. At
this stage the literature is still in its infancy,330 but this potential benefit can be analysed by the project
proposer in qualitative terms, without including its value in the calculation of the economic
performance indicators.
7.8.5 Valuation of benefits to target population and the general public
Reduction of environmental risks
Some research infrastructures are focused on programmes that are intended to monitor certain
classes of large-scale risk and to study mitigation measures. Different territorial risks may be in place.
329 http://www.ons.gov.uk/ons/rel/ashe/annual-survey-of-hours-and-earnings/index.html
330 See, for instance, Castiglione, van Deth and Wolleb (2008).
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For simplicity, they are grouped here under the same label of environmental risk, where the
‘environment’ concept is understood, in a broad sense, as the surroundings or conditions in which a
person lives and operates.
Currently, the most encompassing risk for the human kind is climate change, and researchers are
interested in understanding its dynamics and how to contain it. While this research may be conducted
by relatively small scientific stations or expeditions, in some cases it may require coordinated
networks of research facilities. Such networks can be considered as a unique major project if they are
fully integrated, as discussed in section 7.4. Other classes of natural risks are, for example, soil erosion,
floods, forest fires, earthquakes and volcanic activity. Technological risk for the environment is related
to major pollution episodes in certain classes of economic activities.
When teams of people work at an applied research facility to test new methods of studying data
related to potential environmental risks, to collect new evidence, elaborate forecasting models,
possibly develop prototypes of new technologies and products aimed at reducing such risks, the
ultimate beneficiaries of knowledge advances are potentially all the people at risk within the specific
class of environmental risks considered.
The benefit of new knowledge in this area is the per capita avoided cost of the population potentially
targeted or their willingness-to-pay for reduced environmental risk. There are some relatively well
developed CBA methods for specific classes of risk that can be found in the literature of environmental
economics (see section 4.3 on ‘Environmental remediation, protection and risk prevention’331 and
Annex VI), most of them based on the calculation of the economic value, either of risk prevention or of
the value of the damage arising from the occurrence of the accident and avoided thanks to the project.
Double counting with possible financial revenues provided by the target population should be avoided.
The special difficulty for CBA in the context of RDI infrastructures is that, ex ante, it is unknown as to
whether the project will be successful in providing new solutions over its time horizon. Two opposite
scenarios could occur: a pessimistic scenario where nothing new or nothing of practical relevance is
discovered, and an optimistic scenario in which the project entirely achieves its research objectives.
Particular attention should be paid to avoiding unfounded optimism, deriving, for example, from
imperfect information on unproven technology, a tendency of project developers to be over-optimistic
and political incentives to be more optimistic to promote the project (see Table 7.8 at the end of this
chapter for further examples of typical risks).
It is suggested that, as a baseline, the social benefits of the (carefully) optimistic scenario are
calculated in the first place. In other terms, the project promoter should identify the measurable
benefit to the target population of discovering what the infrastructure is reasonably intended to do. As
mentioned, this can be done by relatively well-known techniques, at least for common environmental
risks. Then the evaluator should consider the probability that the project is only partially successful
and examine the risk affecting the ENPV through a fully-fledged risk assessment, including the risk of
failure to discover anything applicable.
Reduction of health risks
One of the most important areas of contemporary research is related to human health, in such fields
as, for example, the discovery and testing of new drugs, new advanced forms of surgery assisted by
robotics, radiotherapy with non-conventional beams, genetics, etc. Research on the safety of the food
chain or the safety of transport modes is also important to the perspective of human health.
In some cases such research can deliver results that are internalised by businesses (e.g. in the
pharmaceutical industry, or in the production of electro medical equipment), by means of patents or
other intellectual property protection systems. When benefits are fully internalised, then the
businesses would be the main direct target group of the RDI project and the related benefit should be
valued with the methods discussed in section 7.8.3 above.
331 Particularly sections 4.3.7.1 on the valuation of improved health conditions and section 4.3.7.5 on reduced damages to property.
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In other cases, however, knowledge produced by applied research infrastructures is not appropriated
by any specific business but it affects, directly or indirectly, the target population; for example, hospital
research laboratories or other medical research facilities developing and administering a new type of
treatment to their patients.
As with standard health projects, the project’s marginal benefit is the reduction of mortality or
morbidity rates or improved health conditions. They can be valued through the value of statistical
life (VOSL), as discussed in Chapter 3 with reference to the economic cost of fatalities and accidents in
the transport sector, of the quality adjusted life year (QALY) measuring the value of a change in both
life expectancy and quality of life, or other statistical measures well known in health economics.332 In
order to avoid double counting, any financial revenue coming from the targeted population should not
be included in the economic analysis.
The evaluator will need to have the following:
a forecast of the number of patients over the time horizon of the project;
an empirical estimation of the marginal benefit (VOSL, QALY or others) for the target
population that will be treated;
a forecast of the success rate of the therapy.
The latter is obviously the most challenging aspect of the analysis, as, by definition, in medical research
it is unknown whether a new treatment will work or not on a certain pathology and for a certain
sample of patients. As with benefits to populations at environmental risk (see above), health benefits
generated by the RDI infrastructure have to be forecasted and valued under a pessimistic and a
(carefully) optimistic scenario. The probabilities of success, as well as the possible impact on the target
population, can be inferred from relatively similar but more established medical treatments, and can
rely on expert opinion collected through focus groups, interviews, Delphi methods and other
techniques. This evidence, where it is necessary to get the patients’ approval for experimentation, is
likely to be available to the project promoter.
The economic benefit to the target population shall be estimated under the (carefully) optimistic
scenario, but the risk that the research is not fully or partially successful should be assessed through
the risk analysis.
Additional to the direct benefit of the population targeted by the RDI project, there could be another
important benefit, which has to do with the public good nature of knowledge in medicine and related
fields. While the treatment of each patient is not a public good per se (the individual therapy is to a
certain extent rival and excludable), the knowledge acquired in a health research infrastructure can
spill over to the world's medical community in various way: by publishing results, organising scientific
congresses, hosting medical teams from other research centres, signing formal agreements for
knowledge transfer (both for free or against a payment), etc. In these cases, there could be other
indirect target groups, i.e. patients not treated at the research infrastructure, but who will be treated
elsewhere due to the experience and discoveries cumulated by the initial project.
The marginal benefit and the evaluation approach is the same as for directly targeted populations. The
scope of analysis, however, needs to be enlarged. This implies estimating the size of the wider target
population, the possible impact on the wider population and the probability that knowledge transfer
will occur. As usual, a probabilistic risk analysis will help to assess the overall variability of the
resulting ENPV.
Cultural effects for visitors
Some RDI infrastructures attract the interest of the general public and their management may have an
outreach strategy to this end. The reasons to design outreach activities for science and technology
332 The evaluation approach is generally based on the hedonic wage method. For the evaluation of changes in mortality rates, see section
3.8.4. For the reduction of morbidity rates, see section 4.1.7.6.
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ventures could be related to increasing the social acceptance of large-scale projects that may
otherwise be misunderstood by the general public and/or to ‘educate’ people about what is carried out
within the RDI facility. Examples of outreach activities could include the organisation of guided tours
for visitors, for example, by the science park, or agreements between a research competence centre
and schools and universities, aimed at arranging onsite educational programmes. There are many
examples in Europe and in the USA of research infrastructures with large numbers of visitors per year,
and project promoters may consider whether they want to develop such outreach programmes as part
of their strategy.
The ultimate beneficiaries of these activities are the visitors to the infrastructure. Since visits are often
free or at minimal prices, the marginal social value of the benefit is the visitors’ implicit willingness-
to-pay for a visit. As with other recreational activities, the most common way to estimate the WTP is
through the travel cost method or benefit transfer approach (see the discussion in Annex VI). This
means the evaluator would need to forecast the number of visitors in the time horizon of the project
and to estimate the appropriate WTP. The WTP approach can also be used to value the sale of
educational books or other publications aimed at disseminating knowledge to the general public. In
the economic analysis, the WTP replaces the revenues from visitors included in the financial analysis.
Besides personal visits, there could be a number of virtual visitors, who will possibly visit the project’s
website or join social networks related to the project’s activities. Some projects may also have some
exposure in the media. When relevant, the project promoter shall attempt to evaluate the cultural
benefits enjoyed by virtual visitors through appropriate CBA techniques, drawing from the increasing
literature in cultural economics or, at least, in qualitative terms.
THE VALUE OF CULTURAL EFFECTS: EXAMPLE OF ESTIMATION
This box presents an example of the valuation of cultural effects for visitors to a RDI infrastructure. All figures and
assumptions hereby reported have a purely illustrative purpose and should therefore not be taken as reference
values. The project proposer is invited to rely on project-specific assumptions and sources, and to duly justify the
choice of any input value.
In this example, the RDI infrastructure under appraisal is a competence centre specialising in developing
technologies applicable to aircraft. The facility, besides being used by researchers, gives the general public the
possibility to visit the laboratory on selected days of the month and to arrange demo flights for free.
Approximately 100 000 visitors are expected to come every year during the project operation phase. No revenue
from the visitors is recorded in the financial analysis, but their willingness-to-pay (WTP) should be accounted in
the economic analysis to reflect the cultural benefit to the public. In line with the valuation of benefits associated
with recreational goods (see section 4.3.7.3), the travel cost method 333 is applied to estimate the WTP for a visit
to the RDI centre.
Interviews with a sample of experts allows identification of where visitors possibly originate: in particular, 80 %
of visitors are likely to come from an area within a radius distance below 150km, and 20 % from a longer
distance. A further assumption needs to be made about the transport mode used by visitors. The WTP is
reflected by the sum of the cost of a return ticket if travelling by train, bus or plane, or the cost of fuel, tolls and
other operating costs if travelling by car, the value of time spent in traveling (e.g. using the HEATCO reference
values for leisure trips, see section 3.8.1), the cost of meals and, for the share of visitors coming from a distance
greater than 150 km, the possible cost of accommodation in a hotel. Only costs imputable to the visit at the RDI
infrastructure should be included in the estimation of the WTP.
The average WTP for the different classes of visitors (coming from a shorter or longer distance and by different
transport modes) is then multiplied to give the expected number of visitors per year in order to obtain a
valuation of the economic benefit. For further details about the travel cost method, see Annex VI.
333 Developed by Clawson and Knetsch, 1966.
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7.8.6 Benefit and costs of RDI infrastructures in a regional perspective
The above discussion about the valuation of benefits has not paid yet specific attention to the regional
dimension of the possible impacts of the RDI infrastructures. This issue, which is obviously important
in the context of cohesion policy, is discussed in this section.
In principle, all the benefits mentioned above can be given a spatial dimension, which is related to the
location of identified target groups. The ubiquitous nature of research knowledge, however, implies
that, in some cases, tracing the geographical boundaries of its impact has limited meaning. In other
cases, however, it makes sense to ask the following question: to what extent is the region, where the
RDI infrastructure is going to be located, expected to capture benefits from the project?
It is not suggested to break down in quantitative terms the project's net present value into local,
regional, national or trans-boundary impacts. This is also not done for any other major projects
discussed in this guide, and it would be an unnecessary analytical burden. However, the project
proposer may consider offering some quali-quantitative evidence about the benefits and costs for the
regions, at the appropriate scale (e.g. at NUTS 2, NUTS 1 or NUTS 0 levels). In some cases, the project
could be expected to produce displacement effects in neighbouring regions, for example if it aims at
attracting researchers previously employed in another existing RDI facility. It is suggested that the
project proposer discusses significant displacement effects in at least qualitative terms.
The possible benefits and costs to be considered in a regional perspective are non-pecuniary and
pecuniary externalities, the direct impact on regional competitiveness and other wider regional
effects. The approach to evaluate them is discussed below. In general, the project proposer should be
very careful to avoid double counting in the CBA.
Externalities
It is worth mentioning that there may be some social cost related to the infrastructure that is not
captured by the financial analysis. These may be mainly environmental impacts during the
construction, operation and decommissioning phases, such as air/soil/water pollution, GHG emissions
and noise. Air pollution can be produced, for instance, by the increased number of vehicles coming to
the RDI infrastructure. Another example is the release of some toxic substances, which can be expected
from some infrastructures at the end of their lifetime.
Savings in energy consumption due to the building refurbishment and the implementation of energy
efficiency measures could also be generated as a side effect of the project.334
While it is difficult to make general statements about the intensity and direction of environmental
effects arising from RDI projects, if they are important to specific cases they must be valued and
included in the CBA, following the methods discussed in other chapters of this guide (particularly
Chapters 3 and 4 on the transport and environment sectors). In other cases, it is sufficient to mention
and discuss them qualitatively in the project appraisal dossier.
The RDI infrastructure could also produce some (positive or negative) pecuniary externalities,
particularly as regards the price of real estate and services, by affecting the demand for them. As
suggested elsewhere in this guide, the change in property values can be assessed by hedonic prices
(see methodological approaches in Annex VI and examples of application in Chapter 4). Since
pecuniary externalities are to some extent captured by market price mechanisms, special care should
be taken to avoid any double counting of benefits.
Direct impact on regional competitiveness
The direct impact on regional competitiveness is particularly appropriate for RDI infrastructures
benefitting, in different ways, the enterprises operating in the region. From the CBA's perspective, as
previously discussed, benefits are ultimately captured by increased profitability for the businesses,
estimated in an appropriate way, including, when relevant, the expected value of patents. Clearly, from
334 However, as stated in section 7.4, increasing energy efficiency should not be the main objective of the RDI infrastructure project.
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the regional perspective, the more these effects are captured by businesses located in the region the
greater the impact on regional competitiveness.
Beyond a business's profitability, there may be other mechanisms that, albeit difficult to quantify, may
be at least identified qualitatively. These include the attraction of scientists, technological experts
and skilled personnel in general. The increase in the quality of a resident workforce has a long-term
beneficial effect, by contributing to the cumulative process of building a favourable business
environment. It is, however, difficult to give a monetary value without committing double counting
with other benefits that are already quantified.
Personnel who were originally involved in the RDI project may, after some years, move to an
occupation in one of the local businesses or start a spin-off company. In turn, this would reinforce the
competitiveness of businesses and potentially attract other qualified personnel from elsewhere. From
this perspective, it would be important for the project proposer to describe to what extent the project
is expected to recruit personnel from other regions and other countries: a high rate of attraction to
outsiders may be seen as an advantage for stimulating regional growth, but at the same time a social
loss for other regions. As mentioned above, any significant displacement effect among regions should
be duly accounted for in qualitative terms.
In a similar vein, the project may help to counteract the brain drain often suffered by some regions, by
giving young local researchers or technical staff more employment opportunities. As usual, it is
important to avoid double counting: the employment effects should be accounted for by the shadow
wage of personnel recruited by the RDI project and no additional benefits need to be considered in the
CBA. Thus, the number of jobs created or preserved for skilled personnel resident in the region should
be provided as additional qualitative information.
A similar reasoning applies to the attraction of capital or of other businesses. Successful RDI
infrastructures may be instrumental in conveying fresh capital from outside investors, which will find
better investment opportunities in the region, more qualified personnel, and research and
development facilities that are of interest to certain industrial sectors. This effect may also contribute
towards increasing regional competitiveness. If some reliable forecasts about this possible effect exist,
they should be provided, without having been accommodated in the CBA. For this reason, this
particular effect should be discussed qualitatively and not considered for the computation of the ENPV.
Wider regional effects
The RDI infrastructure may have wider local effects on the regional context, which – as discussed in
section 2.2 - shall not be included in the quantitative analysis, but better described in qualitative
terms.
First, there may be demonstration effects on the general population, particularly the young, about
the role of science and technology. While some of these effects may be captured by the cultural effects
on the general public, included in the CBA, as mentioned above, others may be more subtle. For
example, the proximity of schools and universities to a RDI project may convince a larger share of
students to study engineering or to achieve a degree in sciences and this, in turn, could be somewhat
correlated to the long-term regional growth rate.
Second, as science parks, laboratories, competence centres in the high-tech sector, etc. attract high
quality personnel, possibly from other regions or abroad, these may contribute to opening the cultural
horizon of the local society. This in turn contributes to an increase in local social capital and in some
particularly beneficial cases, even to the improvement of the overall quality of institutions. Academic
research in this area is still not sufficiently mature for practical applications. However, if the project
promoter guesses that there will be such future effects, caused by an inflow of international, highly
qualified migrants, this may be stated in qualitative terms. Some supporting evidence about the likely
numbers and origins of the new residents shall be provided.
7.8.7 Future methodological developments
While the focus of this chapter is on applied research, development and innovation infrastructures, it
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is briefly mentioned here that the previously examined benefits may not be the core ones from the
perspective of fundamental research infrastructures. Discovery per se (e.g. the discovery of a new
elementary particle, a new biotype or natural species, a new exoplanet, etc.) is often the primary
objective of a fundamental research infrastructure. However, the social value of pure discovery is an
entirely new field for CBA and its possible valuation methodology still represents a challenge.
One possible evaluation approach could resort to concepts gathered from the CBA of environmental
projects, which may also be relevant to fundamental research projects. For example, the notion of
quasi-option value, i.e. the social value of future potential applications stemming from fundamental
research which at present are not yet well identified,335 could be relevant in the fundamental research
context.
There is much more experience in estimating the existence value of environmental and cultural goods
(Annex VI). This refers to the benefit for an individual from just knowing that a certain good is
preserved for future generations or, in the case of research, that something new is discovered.
Empirically, the existence value of goods can be estimated by contingent valuation. In 1993, the USA's
National Oceanographic and Atmospheric Administration released a very influential guideline on
contingent valuation of the existence value, based on the recommendations of a panel of high-profile
experts. In the EU, there is no extended CBA experience in this area yet, but research on the topic is
ongoing.336
7.9 Risk assessment
The probability of error related to each estimate included in the above analysis could be particularly
high from an ex ante perspective. While this is true in general terms for any infrastructural project, in
the case of RDI infrastructures the overall uncertainty of CBA results can be even larger.
In order to deal with the intrinsic project riskiness and uncertainty about some input variables, a fully-
fledged quantitative risk assessment is required. With reference to section 2.10, this should comprise a
sensitivity analysis (completed with a scenario analysis), a qualitative risk analysis, a probabilistic risk
analysis, and the definition of a risk prevention and mitigation strategy.
The following list shows the variables that are likely to be critical and which should be tested in the
sensitivity analysis, as well as duly considered in the qualitative analysis through the risk matrix:
number of years necessary for the construction of the infrastructure;
investment and operating cost items;
licence revenues gained from patents’ commercialisation;
revenues from the target population using the research outputs (e.g. patients receiving an
innovative treatment);
revenues from outreach activities to the wider public (e.g. bookshop sales, entry fees, etc.)
national/regional funding schemes for RDI activities;
public grants to research;
number of spin-offs and start-ups expected to be established;
spin-off equity realisations;
expected annual incremental profit earned by spin-offs and start-ups;
survival rate of spin-offs/start-ups;
expected incremental shadow profit;
335 As reference, see Arrow and Fisher (1974), Conrad (1980) and Atkinson et al. (2006).
336 See http://www.eiburs.unimi.it/
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number of patents expected to be registered over the project time horizon;
economic value of patents;
number of non-user businesses benefitting from technological spillovers;
expected incremental profit earned by businesses that benefit from technological spillovers or
avoided costs;
number of scientific publications expected to be produced over the project time horizon;
estimate of the unit economic value of scientific publications;
average number of citations received by scientific publications;
number of young researchers and students benefiting from human capital development;
expected incremental salary obtained by students as a result of human capital development
over their professional career;
size of targeted population at environmental risk;
avoided cost or WTP for reduced environmental risk;
forecast of the success rate of the project;
size of targeted population at health risk;
VOSL or QALY;
forecast of the success rate of the project;
estimated WTP of visitors;
estimated WTP for educational publications;
value of environmental impacts;
hedonic prices.
The sensitivity analyses allow for the identification of the most critical variables of the CBA model. The
probability of change for the CBA results (in terms of net present value and internal rate of return)
against simultaneous changes of the critical variables, according to their own probability distribution
functions, should be tested.337 Unlike the major projects that fall under other sectors, where the
implementation of the probabilistic risk analysis is only recommended in some cases, this type of
analysis should be regularly included in the appraisal report of RDI infrastructures. Monte Carlo
simulation techniques should be employed in order to judge the project risk in probabilistic terms.
As described in section 2.10.4, the final step of risk assessment procedures consists of defining a risk
prevention and mitigation strategy for the proposed project. The typical risks affecting RDI
infrastructure projects, and which should be explicitly taken into account, are listed in the table below.
Table 7.8 Typical risks in RDI projects
Stage Risk
- Evolutions in the labour market (demand for university graduates and an impact on the
demand for education services in the area)
- Insufficient qualified human resources for research activity
Demand analysis
- Demand of students different than predicted
- Demand of industrial users different than predicted
- Interest of the general public different than predicted
337 In order to perform a sound risk analysis by means of Monte Carlo simulation techniques, critical variables should be independent among
each other, meaning that any given value of one critical variable should not be affected by the occurrence of any value of any other critical
variable. When the marginal distribution of variables cannot be assumed to be ‘truly’ independent, some statistical techniques may be
adopted to account for correlation among variables (Florio, 2014).
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- Inadequate site selection
- Inadequate design cost estimates
Design - Delays in completing the project design
- Invention of a new RDI technology making the infrastructure’s technology obsolete
- Lack of well-established technical engineering expertise
- Delays in obtaining building permits
- Unresolved property ownership rights
Administrative and - Delays in the acquisition of intellectual property rights or higher-than-expected costs for
procurement their acquisition
- Procedural delays to select the supplier and sign the procurement contract
- Supply bottlenecks
- Lack of ready-made solutions to meet the needs arisen during the construction or
operation of the infrastructure
- Project cost overruns
Construction
- Delays in complementary works outside the project promoter’s control
- Project delays and cost overruns during installation of scientific equipment
- Accidents
- Unexpected complication connected with the installation of specialised equipment
- Delays in making the equipment fully and reliably running
Operation - Insufficient production of research results
- Unexpected environmental impacts/accidents
- Lack of academic staff/researchers
- Inadequate estimate of financial revenues
- Insufficient success in obtaining national and international competitive funding
Financial - Failure to meet the demand of users
- Inadequate system for protection and exploitation of intellectual property
- Loss of existing clients/users due to competition from other RDI centres
Source: Authors
AN EXAMPLE OF PROBABILISTIC RISK ANALYSIS FOR A RDI PROJECT
This box presents an example of probabilistic risk analysis. All figures and assumptions hereby reported have a
purely illustrative purpose and should therefore not be taken as reference values. The project proposer is invited to
rely on project-specific assumptions and sources, and to duly justify the choice of any input value.
This example assumes that a RDI infrastructure project, consisting of the construction of a technology park for
applied research and innovation, has an economic net present value of EUR 400 million over a 15-year horizon
(baseline scenario). The main economic benefits come from the generation of start-ups and the value of new
products developed by user companies, which are ready for commercialisation. High uncertainty, however,
affects the assumptions at the basis of the benefit valuation, which mainly rely on interviews with future user
businesses and benchmarking with similar facilities in the same country.
A sensitivity analysis is carried out to identify the critical variables of the model, with particular reference to the
economic analysis. A 1 % change in the value of the majority of the CBA inputs (related to investment costs,
revenues, operating costs and economic benefits) is considered. Those variables that lead to a greater than 1 %
change in the ENPV are:
- on the cost side, the construction cost;
- on the benefit side, the number of new start-ups generated;
- the shadow profit expected to be produced by existing businesses from the commercialisation of the
innovation products.
In parallel to a qualitative risk analysis, carried out by means of a project risk matrix (not discussed here but see
Chapter 2), a probabilistic risk analysis is implemented.
As a first step, a probability distribution is assigned to each of the critical variables identified through the
sensitivity analysis. Three different distributions are assumed for each variable.
In the baseline scenario construction, costs have been estimated at EUR 80 million, split over five years.
Acknowledging that a number of factors may intervene to change the total construction costs, after consulting
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with experts the project promoter assumes that the construction cost could change according to a normal
distribution with a standard deviation equal to 1 (but different assumptions could have been made in this regard,
see figure below).
Construction costs
mean = EUR 80 million
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
2 4 6 8 10 12 14
sd = 1 sd = 1.5 sd = 2
As to the number of start-ups generated by the incubator available in the technology park, the baseline scenario
considers that a total number of 20 businesses are established over ten years, but this variable is critical for the
model. Benchmarking with other technology parks in other regions suggests that, while it would be possible for
the project to support up to 25 new businesses, given a number of factors (e.g. uncertain availability of venture
capital, limited number of entrepreneurs, etc.) it is more probable that a lower number of start-ups will be
established, but anyway not lower than five. Hence, the project promoter has been quite optimistic in the
baseline scenario. To simplify the computation, the discrete distribution of the number of start-ups has been
taken as continuous, and reflected in a left-skewed triangular distribution.
Number of start-ups
min = 5, mode = 20, max = 25
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0 5 10 15 20 25 30
The RDI project allows already-existing businesses to benefit from the use of testing and prototyping
laboratories, which eventually lead to the development of new marketable products. Due to some unemployment
in the region, the conversion factor for labour is estimated at 0.8; thus the shadow profit gained by businesses for
selling the innovation products differs from the financial profit.
Expected annual shadow profit is highly variable. In principle, other variables are likely to be critical, such as the
number of user businesses, or the time at which new products are actually developed, or the number of
innovative products developed. Here for the sake of simplicity and example, only the annual shadow profits are
tested. Given the high uncertainty about this variable, the project promoter assumes that profits may take any
value between EUR 5 million and EUR 20 million per year, while in the baseline scenario a EUR 15 million annual
shadow profit has been assumed for any new product brought to the market. Thus, a rectangular distribution can
be hypothesised.
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Annual shadow profits
min = EUR 5 million, max = EUR 20
million
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0 0.5 1 1.5 2 2.5
Information about the probability distribution of critical variables is entered in computation software for a
Monte Carlo simulation. Through the software, a set of values for the three above-mentioned critical variables
are randomly extracted within their respective defined intervals and probability distribution functions. A total
of, let’s say, 1 000 extractions are made. The economic net present value resulting from each set of extracted
values is estimated, so as to obtain a probability distribution of the performance indicator, shown in the graph
below.
Due to a certain optimism bias in the assumptions behind the number of start-ups and the annual shadow profit
enjoyed by existing user companies, once considering the probability distribution functions of critical variables,
the mean ENPV can be expected to be lower than the value obtained in the baseline scenario (EUR 400 million).
Actually, in this example there is an almost 70 % probability that the ENPV will be lower than what was initially
estimated and a 10 % probability that it will be negative. The risk analysis suggests that proper mitigation
measures, focused on specific variables, should be taken to ease the materialisation of benefits.
ENPV
(thousand EUR)
0.12
0.1
Discrete probability
0.08
0.06
0.04
0.02
0
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Annex I. The financial discount rate
Theoretical background
When investors, either private or public, commit capital to a project, they have an implicit cost
deriving from sacrificing a return to another project. In other terms, the resources employed have an
opportunity cost. Thus, to induce the investment, the expected return should be at least as high as the
opportunity cost of funding. This is why inflows and outflows of a project are discounted by means of a
financial discount rate (FDR).
The FDR is the opportunity cost of capital and is valued as the loss of income from an alternative
investment with a similar risk profile. It takes into account the time value of money, for example the
idea that money available now is worth more than the same amount of money in the future because it
could be earning interest (in a non-risk deposit), and the risk of the anticipated future cash flow being
less than expected.
Approaches for empirical estimation
Different approaches exist in the practice of calculating the financial discount rate.
A commonly used approach consists of estimating the actual cost of capital. A proxy for this
estimation is represented by the real return on government bonds (the marginal direct cost of
public funds) or the long-term real interest rate on commercial loans (if the project needs
private finance), or a weighted average of the two rates (Weighted Average Capital Cost –
WACC). The latter case is applied, particularly, when a project needs the financing both of
public and private funds. Although being very practical and widespread, this approach does
not reflect the actual opportunity cost of capital, because the best alternative investment
should, in principle, produce higher earnings than the interest rate paid on public or private
loans.
A second, more accurate, approach is to consider the return lost from the best alternative
investment in order to determine the maximum limit value for the discount rate. In this case,
the alternative investment is not the buying back of public or private debt but is the return on
an appropriate portfolio of financial assets.
Finally, the FDR is determined by using a specific interest rate or a rate of return from a well-
established issuer of securities in a widely traded currency and then applying a multiplier to
this minimum benchmark. Given the volatility of the international financial markets (including
the risk of asset bubbles), however, this approach can lead to unstable and frequently changing
values.
Example of estimation
In the following, an empirical example for the calculation of the FDR in a small open economy is
proposed by following the second approach. The calculation, made for illustrative purposes, deviates
from the 4 % proposed in the main text as reference for the 2014-2020 programming period (which
remains, as mentioned, an indicative benchmark value to be used for EU Member States in general).
The main underlying assumption is that the project proposer is an experienced investor and is able to
obtain a return from his/her investment that is at least equal to the average value of a portfolio of
different securities. The starting point for the estimation of the opportunity cost should be, therefore,
the rate of return on the most common assets from which an investor can earn interest, namely
government bonds, cash equivalents and stocks. This approach assumes that domestic and
international security markets are integrated, meaning that there are no barriers to financial flows and
that assets with the same levels of risk command the same return no matter the country. This is
particularly suitable for small open economies, where the domestic returns on capital are less relevant
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than a diversified portfolio available on the international capital market338. As a consequence, even if
the project is related to its country context, the estimation of the opportunity cost of capital can rely on
an international portfolio of assets on the basis that the investor might commit his/her resources
elsewhere.
In this example, one rating agency's estimates of long-term returns of an international portfolio of
investments have been considered (see table below). The FDR is calculated as the mean339 of the
returns from the assets included in the portfolio. The Fisher Formula340 is then used to get the real
return estimates. Adopting these estimates, the calculated FDR is 2.9 % in real terms or 5.1 % in
nominal terms.
Table I.1 Nominal and real return estimates
Asset class Nominal annual Real annual
return estimates % return estimates %
Large-cap stocks 6.5 4.3
Mid-/small-cap stocks 8.0 5.8
International stocks 6.3 4.1
Bonds 2.6 0.4
Cash investments 2.2 0.0
Simple average 5.1
Long-term inflation rate 2.2
Simple average 2.9
Source: www.schwab.com
338 In fact, if investments only available in the domestic economy are considered, the opportunity cost for the investor can often be
comparatively lower than the value observed in the international market.
339 As an alternative, an average weighted on the relative volume of each asset within the portfolio could be computed.
340 𝑟 = 𝑖 − 𝜋, where: r is the real rate, i the nominal rate and π the inflation, (when i the nominal rate and π are low).
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Annex II. The social discount rate
Theoretical background
The social discount rate (SDR) is used in the economic analysis of investment projects to discount
economic costs and benefits, and reflects the opportunity cost of capital from an inter-temporal
perspective for society as a whole. In other words, it reflects the social view of how future benefits and
costs are to be valued against present ones. In this sense, every discount rate entails a judgement
concerning the future and it affects the weight attributed to future benefits or costs.
A zero social rate of time preference derives from the assumption that equal weights are given to the
utilities occurring at any moment, i.e. that today’s and future consumptions are indifferent to the
utility point of view. A positive discount rate, on the other hand, indicates a preference for current over
future consumption, whereas the opposite is true if the discount rate is negative.
In a perfectly competitive economy and under equilibrium, the social discount rate coincides with the
financial discount rate, which would correspond to the financial market interest rate. However, this
does not apply in the practice, since capital markets are in fact distorted.
Approaches for empirical estimation
Different approaches have been proposed by the literature to estimate the SDR. The most popular ones
are provided here.
The social rate of return on private investments (SRRI) is based on the idea that public
investments displace private investments. Therefore, according to this approach, the return
from the public investment should be at least as big as the one that could be obtained from a
private investment. As a result, the SDR is considered equal to the marginal social opportunity
cost of funds in the private sector. As mentioned by many economists (Boardman et al., 2006,
Barrett et al., 1999, Arrow and Lind, 1997), the SRRI approach is generally biased toward high
estimates of the SDR. There are two main causes of this bias: first, externalities and market
failures distort private investment returns and may generate private investment returns
higher than the social ones; secondly, the observed private return on investments usually
includes a risk premium. This is however not to be included in the SDR because society as a
whole, or the government, has a much larger portfolio than any private investor has and
consequently is able to exploit risk pooling. As an empirical estimation of the SRRI is typically
based on observed returns in the private financial markets, one additional concern here is
market volatility and the role of asset bubbles.
The social rate of time preference (SRTP) is the rate at which society is willing to postpone
a unit of current consumption in exchange for more future consumption. The logic of this
approach is that the government should consider the welfare of both the current and future
generations and solve an optimal planning programme based on individual preferences for
consumption. Different methods exist to estimate the SRTP. First, it can be estimated by
looking at the return on holding government bonds or other low risk marketable securities.
Another way is based on a formula obtained from the Ramsey growth model (see below). A
possible limit of the SRTP approach is that, by focusing on the consumption side, it disregards
the displacement effect that public projects might have on private investment. Lind (1990),
however, maintains that, because of international capital mobility, the crowding out effect of
private investment by public investment does not appear to be very important to the analysis
of the social discount rate.
Other approaches exist and could be used for inter-temporal discounting, although they are
rarely applied in practice. Among these are the weighted average approach and the shadow
price of capital approach. The former implies that, when public investment is considered to
have a displacement impact on both private investment and future consumption, the SDR could
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be estimated by a weighted average of the investment rate of return and the rate of time
preferences. The latter entails the conversion of investment flows into ‘consumption
equivalents’ through an appropriate shadow price of capital; these flows are then discounted
at the social rate of time preference.
The following table synthetically presents the SDR approaches currently used in selected countries
worldwide. It can be noted that the social rate of time preference method is widely used in developed
countries, especially European ones. Indeed, according to most economists (e.g. Feldstein, 1972, Evans
and Sezer, 2003, 2004 and 2005, Florio, 2007, Evans, 2007, Kula, 2002 and 2006), this approach is
grounded on a robust theoretical basis, as it does not rely merely on financial data but, above all, on
social preferences.
Table II.1 Social discount rate methods as adopted in selected countries
Theoretical basis Country Source
Denmark Hepburn (2007)
France Quinet (2007)
Germany Florio (2006)
Italy Florio (2006)
Portugal Florio (2006)
SRTP
Slovakia Hepburn (2007)
Spain Florio (2006)
Sweden Hagen et al. (2012)
United Kingdom HM Treasury (2003)
USA (Environmental protection Agency) Zhuang et al. (2007)
Australia Harrison (2010)
Canada Guidelines of the Treasury Board secretary (2007)
India Zhuang et al. (2007)
SRRI Ireland Florio (2006)
Netherlands Florio (2006)
New Zealand Zhuang et al. (2007)
USA (Office Management and Budget) Zhuang et al. (2007)
Weighted average
People’s Republic of China Zhuang et al. (2007)
approach
Government’s Czech Republic Hepburn (2007)
borrowing rate Hungary Hepburn (2007)
Source: Authors
The social rate of time preference
A relatively easy and largely used way to estimate the SRTP is based on the following formula, which is
obtained from the Ramsey economic growth model (1928):
SRTP = 𝑝 + 𝑒 ∗ 𝑔
where p is the pure time preference, e is the elasticity of the marginal utility of consumption, i.e. the
percentage change in individuals’ marginal utility corresponding to each percentage change in
consumption; g is the expected growth rate of per capita consumption.341 The two components of this
formula (the one related to time preference and the other related to consumption growth) reflect the
two possible reasons why future consumption may have a lower value than in the present. First,
present income or consumption is usually preferred because of uncertainty about the future and
impatience. Second, future consumption may be valued at less than the present one because of the
probability of people becoming richer in the future. Indeed, if per capita consumption is growing, then
the value of additional consumption for each year in the future is declining at a rate related to the rate
of growth of per capita consumption and the elasticity of diminishing marginal utility of consumption.
Each term in the formula is discussed in more detail below.
The pure time preference term (p) can be decomposed into two elements, one related to
341 The algebra of this equation was set out by Feldstein (1965).
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individuals’ impatience and myopia, and the other one related to the risk of death or human race
extinction. This latter component reflects the life chance and it is often simply measured as the ratio of
total deaths to total population. The former component instead refers to the observation that
individuals favour the present over future consumption and this is reflected in a positive value of p.
However, as put forward by Ramsey and others, from a social perspective it is 'ethical indefensible' to
set this term different from zero (Ramsey, 1928, page 543). A positive value, actually, would signify
that future generations are made worse off but only due to the fact that they are born later, which
would be unacceptable from the point of view of society as a whole.
The economic empirical literature generally estimates a value for p of between 1 % (e.g. Newbery,
1992, Arrow, 1995, Evans, 2007) and 3 % (Nordhaus, 1993). However, in the Stern Review a 0.1 %
rate is considered due to the assumption about a nil impatience or myopia component, in line with the
above-mentioned Ramsey’s argument.342 As a result, an easy way to proxy p could be to set the
impatience or myopia component equal to zero and the risk of death or human race extinction equal to
the annual crude death rate of the population (number of deaths over population).
The elasticity of the marginal utility with respect to consumption (e) captures the dynamics of
consumption over time. This parameter captures the fact that if tomorrow consumers are a bit richer,
marginal utility is decreasing. In other terms, it reflects how consumption should be transferred across
different generations; it can be seen as a planning parameter for the social planner in that it reveals his
preference for income inequality aversion.
An approach to estimate the elasticity term is to consider the social judgement about how
consumption should be transferred across people at different times. In this case, the elasticity tells us
how much more worthwhile it is to transfer income from a rich person to a poor one. This can be
revealed by analysing the progressivity of national personal income tax rates. Stern (1977), Cowell and
Gardiner (1999) and Evans (2006) propose the following formula of elasticity:
e = ln(1 − 𝑡 ′ ) / ln(1 − 𝑡)
where t’ and t are respectively the marginal and average income tax rates for an average taxpayer.
One is the neutral value of the parameter: when e = 1, then EUR 1 of additional future consumption
adds EUR 1 to social welfare. If instead e < 1, consumers are not so interested in future growth. If e > 1
consumers are interested in it.
The expected per-capita consumption growth (𝐠) or other welfare-related variable (e.g. income, as
stressed by Spackman, 2007 and Kula, 2012). From the point of view of inter-generational equity, this
term implies that if future generations are expected to be wealthier that the ones of today, and thus if
consumption rises over time, this would result in an increase of the discount rate in order to shift the
priority to the poorer current generation. Usually very long-run growth rates of real per capita
consumption are used to estimate future growth, in order to smooth out possible short-term
distortions.
Empirical estimates for the rate of growth of per capita consumption are usually based on growth
models, which take into account both the past long-term development path and the expected future
growth. A way to estimate g is to consider another welfare correlated indicator as proxy for
consumption growth, such as real per capita GDP growth, consumption growth or personal income
growth.
As far as empirical estimation is concerned, the most recent evidence estimating the SDR for 20
European countries is presented in Florio, 2014 (see Bibliography).
342The same approach was followed, for example, in the Stern Review (HM Treasury 2006).
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Annex III. Approaches for empirical
estimation of conversion factors
Theoretical background
For the purpose of the financial analysis, market prices represent a relevant signal for both the private
and public investor when assessing the project's financial performance. However, they are no longer
relevant when the aim is to assess the project contribution to economic welfare. For this purpose, all
revenues and costs considered when appraising the financial performance (in particular those
included in the tables for the assessment of the financial return on investment) and valued at prices
observed on the market, have to be valued at the so-called ‘shadow prices’. A shadow price is the social
marginal value of an output or input change, i.e. the opportunity cost to the society of producing or
consuming more or less of any good.
Market prices and shadow prices are the same in perfectly competitive and efficient markets or under
optimal planning. In reality, however, the markets may be distorted by taxes, duties, subsidies, rigid
exchange rates, rations on production or consumption, regulated tariffs, oligopoly or monopoly price
setting and imperfect information. These are elements that drive a wedge between the observed price
and the marginal social value of resources.
PRICE DISTORTION: EXAMPLES
- A land-intensive project, e.g. an industrial site, where land is made available free of charge by a public body,
while it may otherwise earn a rent.
- An agricultural project that depends upon a water supply at a very low tariff, which is heavily subsidised by the
public sector and where output prices are affected by special policy regimes (e.g. under some provisions of the
EU's Common Agricultural Policy).
- An energy intensive project that depends upon the supply of electricity under a regime of regulated tariffs,
when these tariffs are below long run marginal costs.
- A power plant under a collusive oligopoly regime, which determines a substantial price divergence of electricity
prices from long term marginal costs, the former being higher than the latter; in this case economic benefits
could be less than financial profits.
The general theoretical framework of cost-benefit analysis is provided by Drèze and Stern (1987,
1990343), who estimate shadow prices as the net impact on the social welfare function of a unit
increase of an input or output.344
Empirical approaches for the estimation of the conversion factors
There is no unique way to calculate the shadow price, which fits all types of market and non-market
goods. Instead, several approaches exist, and each of them could be more or less suitable for certain
typologies of goods and sectors (see Figure 2.2 in Chapter 2).
In order to apply the most appropriate method, a first important discrimination is whether the good is
an input or an output of the project. For the latter, the willingness-to-pay approach described in Annex
VI can be followed. As far as inputs are concerned, they can be regarded as tradable or not in
international markets. The general rule for internationally tradable goods, such as most manufactured
343
Drèze, J. and Stern N. (1987) ‘The Theory of Cost-Benefit Analysis’, Chapter 14 in Auerbach A.J. and Feldstein M. (eds), Handbook of Public
Economics, North-Holland: Elsevier Science Publishers. Drèze, J. and Stern N. (1990) ‘Policy reform, shadow prices and market prices’, Journal
of Public Economics, 42 (1): 1-45.
344 See Florio (2014) for a simplified presentation of the Drèze-Stern theory: Florio, M. (2014) Applied Welfare Economics, London: Routledge.
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commodities, is to use their border price. As far as non-tradable goods are concerned, a different
approach is followed, depending on the event of considering minor items or major items. For minor
items, a special parameter called standard conversion factor (SCF) can be used.
Shadow prices for major non-tradable inputs depend on the effect that a demand or supply change for
that good has on social welfare; these effects, in turn, depend on how the markets adjust to those
demand or supply changes. In particular, the opportunity cost of project inputs whose use would lead
to an increase in production must be estimated through the long term marginal cost345 of producing
one additional unit of that input. Instead, when the use of an input will not result in increased
production but in a reduction of consumption by alternative users, the willingness-to-pay must be
estimated by reference to their social value, rather than to their cost. The shadow price in these cases
is the price that alternative users would be willing to pay to consume that good.346
Labour cost represents an exception. Even if labour is characterised by freedom of movement across
the EU, it cannot be considered a tradable good in the strictest sense. It is also valued differently to
other non-tradable inputs: a specific shadow price (i.e. the shadow wage), which accounts for local
distortions in the labour market, must be computed to determine its opportunity cost.
The different approaches for the empirical estimation of conversion factors to move from observed to
shadow prices are presented in more detail below.
The border price rule for tradable inputs
The border price rule is generally used to estimate shadow prices of internationally marketable goods
entering as inputs in the project. It is gathered from the Little and Mirrlees (1974)347 approach to
project evaluation. This approach, derived from research commissioned by the OECD, the United
National International Development Organisation (UNIDO) and the World Bank, has been conceived
for evaluating investment projects in distorted markets, such as those in developing countries.
However, the same rules are relevant to any open economy, regardless of the degree of price
distortion.
The border price method is based on the estimation of the trade opportunity cost of goods, under the
assumption that international prices reflect the economic value of imported goods better than
domestic prices. According to the border price rule, the shadow price of a tradable good is given by its
CIF (cost, insurance and freight) price at the national border, thus including the cost of production,
insurance and freight borne to bring the good as far as the national border, but excluding any custom
duties, taxes or subsidies applied once the good enters the national market. These can be a percentage
of the price of the good, a fixed amount per unit or a minimum price applied as the good passes the
border.
The Little-Mirrlees rule applies to goods that are tradable by nature, for which an international market
exists: these are typically most raw and semi-raw materials, manufactured goods but also some public
utilities (e.g. natural gas supply). Conversely, transport services, civil works, maintenance costs, land,
local transport and some other public utilities (e.g. water supply) can be considered non-tradable
goods and for them the border price rule cannot be used.
In general terms, it can be stated that the border price rule can be applied whenever the next best
alternative of domestic production is importing it. Hence, whenever international trade represents a
feasible opportunity, border prices can be taken as shadow prices in the economic analysis of
investment projects. This means that the rule can also be applied to goods that, in spite of being
potentially tradable on the international market, are currently not traded in practice, for example
because of low domestic attitude towards foreign trade.
345 Net of the social value of profit.
346 The willingness-to-pay/accept approach is also applied to value non-tradable outputs, both actually sold or non-sold ones, like
externalities (see Annex VI).
347Little, I.M.D. and Mirrlees, J.A. (1974), Project appraisal and planning for developing countries, London: Heinemann Educational Books.
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For example, assume that a given good is produced in country A at a certain cost and in country B at a
lower cost. A could decide to continue producing the good in spite of having the possibility of
importing the good from B at a relatively lower price. Its shadow price will be the price of the next best
alternative of self-producing the good. Since trading in principle is possible (e.g. a road linking country
A and B exists) and would be financially more convenient (the import price would be lower than the
production costs in A), importing the same good from B would represent the next best alternative for
country A. Hence the shadow price of this good would be its border price.
Another main assumption for using the border price as the shadow price of a commodity in a country
is that the world price of that commodity is fixed, i.e. it is not affected by significant variations in
demand and supply in the national market. This assumption can be considered to hold in relatively
small countries, whose domestic market changes cannot directly affect international markets, and
when no particularly large investment projects are under implementation. In fact, ‘economically
significant’ or ‘mega’ projects are such that they could influence national trade flows and, thus, relative
prices. When these conditions are not met, shadow prices of imported items could be better proxied by
following alternative approaches (see below).
The long run marginal cost
The economic value of non-tradable inputs, for which an increase in demand results in increased
production, can be measured by the marginal social cost of production. This method can be applied
when the cost structure is known or can be easily identified, otherwise the standard conversion factor
could be applied as a shortcut.
The marginal social cost of a good is the market price of the inputs required to increase the production
of a good by one unit, less the social value of the extra profit for selling the extra good, holding the
production levels of all other goods constant.
Variations in the long run marginal cost (LRMC) can capture changes in both operating and capital
costs. By reflecting the marginal costs involved in providing an additional good, which enters as an
input of the project under assessment, the LRMCs can be taken as a good proxy of the economic value
of that good and, thus, can be used as the shadow price.
In calculating the LRMC, the project appraiser should consider, in principle, not only the incremental
financial operational and capital costs involved when increasing marginal production, but also other
environmental and non-market costs contributing at forming the total economic value of the good.
Estimating the LRMC can be arduous, as it requires detailed information on the structure of production
costs, which could not be available to the project appraiser. Two general rules for marginal cost
estimation can be provided. First, the LRMC should include on the operating and capital side only the
actual extra cost of creating increased capacity required to meet the needs of the project. It is possible
that not all costs necessary for production will need to be incurred to allow increased supply; for
instance, some existing capital facilities may be able to cope with new productive capacity. Second, it
should be considered that marginal cost pricing is a forward-looking concept, meaning that it should
be based on the expected development in the cost structure. Furthermore, it could be useful to have in
mind that LRMCs are generally lower than average total costs due to fixed costs and economies of
scale, which characterise many businesses.
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EXAMPLE: LONG RUN MARGINAL COST OF WATER
The LRMC of water should take into account the increase in costs led by an increase in water consumption
(because of the project's construction and operation activities), as well as the costs associated with the provision
of new water resources, treatment capacity and any other costs that may occur in the long run. These include
costs sustained to avoid or mitigate potential negative externalities, such as pollution, and the opportunity cost
of the resource, in compliance with Article 9 of Directive 2000/60/EC.
More specifically, in the case of the economic cost of water, the LRMC can be computed as the sum of the cost
categories listed below.
- Supply costs: they are based on the unit cost of the resource required by the investment project, calculated as
the annualised capital and operating costs associated with the provision of water (from groundwater, surface
water, desalinisation, etc.) divided by the volume of water consumed. Capital costs should also include any
investment costs aimed at improving the water quality and the water supply system performance (e.g. by
reducing losses and pollution, improving reliability, etc.).
- Treatment costs: they can be estimated through the annualised unit cost of the relevant sanitation and
treatment process.
- Distribution costs: they include the annual unit costs (total distribution costs over the total volume of water
distributed) of installing and maintaining the connection from the customer’s property to the mains and the
specific costs related, e.g. to the pumping head, dams, the lengths of mains required, the soil types, desalination
(depending on how water is gathered). These costs are generally differentiated by type of users, namely
industry, households and agriculture.
- Other annual costs of service management, which include the cost of meter-reading, billing, keeping customer
records and dealing with enquiries and other administrative costs.
- Any environmental costs associated with water supply and treatment, such as the social cost of pollution
generated by the electricity used for pumping water, noise and environmental damages provoked during the
construction phase, etc.
- Finally, the resource costs, i.e. the opportunity cost of using water for the project, to be valued in terms of the
best alternative use of the resource.
Directive 2000/60/EC recommends water-pricing policies to take account of the principle of recovery of all the
costs of water services, including financial, environmental and resources costs. Hence, whenever there is a
guarantee that the water tariff is set in such a way as to ensure the full recovery of costs, particularly in
accordance with the 'polluter pays' principle, the water tariff would equal its LRMC and can thus be taken as the
proper shadow price of water.
The standard conversion factor
Minor non-tradable items are inputs that do not represent a significant share of the project total costs
and for which no sufficient information on their cost structure is generally available, thus impeding an
estimate of their long term marginal cost. An adjustment method to estimate shadow prices of these
items consists of computing the so-called standard conversion factor (SCF). The SCF is a proxy of the
average distance between world prices and domestic prices, under the assumption that the former
reflects the opportunity cost of the good and that the latter is distorted compared to international
prices (in line with the border price rule). The lower the distortion of the domestic market, the closer
the SCF is to unity.
Even if the gap between domestic and international prices can be determined by a wide variety of
distortions, the most widely used formula to estimate the SCF takes into account only taxes and
subsidies on trade as factors driving a wedge between market and shadow (i.e. international) prices.
This is clearly a simplification, but it guarantees an easy applicability of the method.
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The full formula generally used to estimate the SCF is:
M+X
SCF =
(M + TM − SM ) + (X − TX + SX )
where:
M is the total value of import at shadow prices, i.e. CIF prices;
X is the total value of export at shadow prices, i.e. free on board (FOB) prices;
TM and TX are the value of duties on import and export respectively;
SM and SX are the value of subsidies on import and export respectively.
Like the border price rule applying for estimating the shadow prices of tradable goods, the CIF prices
at the national border are taken as a proxy of the international value of imported good. The FOB prices
are taken as a proxy of the international value of exported goods, including the cost of production of
the goods and their transport up to the border, before any subsidies or taxes are applied for them
being exported.
In a multi-level government such as the European Union, observed prices should also be free of custom
duties (and any subsidy) levied by the EU imports entering each Member State from third countries.
Additionally, in Member States that have both central and sub-central levels of governments, taxes and
subsidies imposed by each of these levels should be taken into account.
The general formula for the SCF can be simplified if no taxes or subsides are levied either on imports
or exports. In computing the SCF for the EU Member States, in particular, some considerations can be
made:
some taxes and duties are generally levied by the national governments (at both central and
sub-central level) on imports from other countries and by the institutions of the European
Union for imports from non-EU countries;
import subsidies are usually not a practiced measure by either EU institutions or national
governments;
exports to other Member States and third countries are generally free of taxes;
subsidies linked to the volume and value of exports are, in principle, not granted by both the
EU institutions and national governments, in line with the 1994 World Trade Organization
(WTO) agreement. However, in spite of an actual fall of export subsidies in the last decades,
they still have not completely disappeared, particularly in the agriculture and food sectors. For
the purpose of the SCF estimation, export subsidies can be assumed to be equal to zero
because:
o still existing subsidies are put mainly on agricultural and food products, which are usually
neither inputs or outputs of public infrastructure projects;
o export subsidies throughout the EU are expected to be completely eliminated soon, in
compliance with the WTO agreement;
o the value of subsidies still in place is not particularly high compared to the total value of
export.
When all these considerations apply, the formula for the estimation of the SCF can be simplified into:
M+X
SCF = .
M+X+TM
Willingness-to-pay for non-tradable inputs
As illustrated in the main text, the concept of willingness-to-pay (WTP) is primarily used for the
valuation of project outputs. Annex VI discusses in detail the WTP approach and the different methods
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that can be used to evaluate the project's direct and external effects. However, in some specific cases,
WTP can also be used to proxy the opportunity cost of inputs entering the project's production
process, whose use in the project leads to an adjustment in the net demand of other consumers of that
good. In these cases, the WTP provides a reference estimate of the total economic value of the good
that is better than the long run marginal cost, because in fact there have been no effects on marginal
production which the LRMC could capture. For this reason, a brief excursus is presented here.
When it is not possible or reasonable to increase the supply of a good to meet the increase in its
demand, it could be alternatively obtained through market bargaining. The maximum amount of
money the buyer is willing to pay to get the needed good well reflects its total economic value.
As an alternative approach, taking the opposite perspective, the minimum amount of money the seller
would be willing to accept to give away the good, which is the willingness-to-accept (WTA), could be
considered. In principle, the concepts of WTP and WTA are equivalent. Yet, it has been empirically
shown that the not full rationality of individuals leads to estimates of WTA that are higher than the
equivalent WTP. This is because people tend to demand higher monetary compensations to give up
goods they have, than the price they say they would be willing to pay to buy the same good they do not
have. As a result of this, it is recommended to preferably use the WTP approach.
EXAMPLE: THE CONVERSION FACTOR OF LAND
Land is a type of input whose use by one individual reduces availability to others, because its supply cannot be
extended at liberty. In many cases it is reasonable to assume that market prices capture considerations about
land’s utility, desirability and scarcity, thus fully reflecting their opportunity cost. This would imply the
application of a conversion factor equal to 1.
However, there may be situations in which the rental, purchase or expropriation cost of the land by the public
authorities are made at prices different to market prices. In order to properly estimate the opportunity cost of
land, the WTP of its potential users should be valued, by either implementing a contingent valuation or through
the revealed preference approaches.348
Whenever it is known that the price actually paid for land is lower or higher than its opportunity costs by a
certain amount, the project appraiser could simply compute a conversion factor defined as follows:
CF=1±d,
where d is the distortion expressed as a share of the observed price. If, for example, the price paid is 20 % lower
than the land’s opportunity cost, the CF for land will be 1.2 (1+0.2); if is the price paid is 20 % higher than the
land’s opportunity cost, the CF of land is 0.8 (1-0.2).
Estimation of weighted conversion factors: example
When appraising a project, it could be not self-evident which of the approaches above described
should be applied to estimate shadow prices. Equipment349 and replacement and renewal costs, for
example, are a mix of tradable and non-tradable inputs; civil works,350 which could be regarded as
non-tradable, are usually costs that are too aggregated to allow the estimation of their LRMC; the same
argument could be raised for maintenance351 costs.
In these cases, the item’s value could be taken as the aggregation of the values of its own production
inputs. In other words, one could try to break down the value of these goods and services into their
inputs, and these inputs into their respective inputs, so on and so forth, in order to identify tradable
and non-tradable sub-components to which the most appropriate estimation approaches more easily
apply.
348 See Annex VI for more details on these methodologies.
349 Finished products, including both installed machineries for permanent use and tools used during works. They could be either purchased
or rented.
350 Construction of new civil structures (such as masonry, concrete and/or metal structures, etc.) or the modification of existing ones.
351 Ordinary periodic and planned maintenance, including interventions to fix broken parts.
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The shadow price of any of these more complex or 'derived' items, whose value is made of the
combination of other 'primary' inputs, can be valued by means of ad hoc conversion factors. These are
computed as the average of the CFs of the inputs, suitably weighted by the share to which each input
item contributes to the total value of the derived item. Primary inputs could include labour, project
design and construction supervision, energy, materials and some other minor services. Derived items
can be referred to equipment, civil works, ordinary maintenance, and replacement and renewal costs.
More specifically, the following steps could be taken to estimate the CFs of derived project inputs.
Computation of primary CFs. The CFs for transforming the observed price of an input into its total
economic value are computed for those tradable and non-tradable items to which the border price, the
LRMC or the WTP approach can be easily applied. By definition, the CF will be computed as the share
between the shadow price and the observed price. In some case, for minor items, the national standard
conversion factor can be used.
Identification of the weights of primary inputs in derived items. The weights to which primary
inputs enter the production of each derived item can be determined based on the opinion of experts
with knowledge about the average proportions of primary items composing the derived ones
(engineering judgment; for alternative methods, see the box below). In principle, sector CFs for each
derived item could be computed because of the way the different input factors entering the
composition of the derived items vary depending on the investment sector considered. It must be
noted that the cost of some derived items may be determined not only by primary items, but also by
other derived costs: e.g. the cost of maintenance can be regarded as made up of the cost of labour,
energy, materials, but also equipment, which, in turn, could be disaggregated into its input factors.
Computation of derived CFs. Once the weights have been identified, the CFs applying to derived
items can be computed as a weighted average of the CFs of its primary input factors. Therefore,
assuming, for example, a CF of 0.75 for labour, 0.8 for energy and 0.9 for materials and that these items
represents respectively 50 %, 10 % and 40 % of the value of equipment costs, the CF for equipment
will be computed as (0.75*0.5)+(0.8*0.1)+(0.9*0.4), and it will result in 0.79.
ALTERNATIVE METHODS FOR IDENTIFYING PRIMARY CFs’ WEIGHTS
In order to reduce the risk of subjectivity in the determination of the weights, an alternative approach is to
derive such a composition by looking at the national Use Table produced by the national statistical offices. The
Use Table shows the use of goods and services by products and by types of use (i.e. as intermediate consumption
by industry, final consumption, gross capital formation or exports). The table can be exploited to derive a good
approximation of the percentage weight to which different types of goods enter the composition cost of derived
items. Taking the example of equipment costs, the percentage share of each category of product used for the
manufacturing of equipment, over the total value of equipment produced in the economy, can be estimated by
considering the columns of the Use Table that correspond to the manufacturing activities of equipment goods
(machinery, electronic products, vehicles, etc.), and the rows of products (materials, energy, high-skilled
services, labour, etc.) that are used for the manufacturing of such equipment.
The relative composition could be re-assessed every time a more up-to-date Use Table is made available, even if
this event might not occur frequently. In fact, it is reasonable to assume that the overall composition of derived
items is quite stable over time and not subject to frequent variations 352.
352This methodology has been developed by CSIL, Centre for Industrial Studies, (Milan) and BGI consulting (Vilnius), and is being tested by
the Lithuanian Ministry of Finance to compute the CFs for all the categories of project inputs, distinguishing by investment sector.
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Annex IV. The shadow wage
Theoretical background
Due to structural characteristics of local labour markets, including the existence of a legal minimum
wage, the presence of real wage rigidities, the existence of taxes and social contributions, subsidies,
monopsony conditions and the role of unions, the opportunity cost of labour may differ from the price
that is paid for its use, represented by the market wage. In a cost-benefit analysis (CBA) setting, this
implies that, while in the financial analysis the labour input is valued by means of the market wage, a
shadow wage (SW), reflecting labour’s social opportunity cost, should be computed and used in the
economic analysis. The difference between the market and shadow wage is related to the peculiarities
of the labour market that may overrate (or, less frequently, underrate) the opportunity cost of labour.
Conversion factors (CF) are coefficients that translate the observed market wages into shadow wages
and are the main input for economic analyses.
Empirical approaches for estimation
In earlier empirical approaches, the value of the labour input to a project was considered as its market
wage and its social opportunity cost in financial and economic analysis, respectively. To obtain an
empirical value for the shadow wage, the marginal product of labour or the disutility of effort were
typically considered. Focusing on the marginal product of labour, this can be obtained by specifying a
project-specific production function and estimating the labour supply of workers employed by the
project. Empirical applications of this methodology were used, especially for projects in the
agricultural sector in developing countries, for example by Jakoby (1993), Skoufias (1994) and Adbulai
and Regmi’s (2000) for Perù, India and Nepal, respectively. Empirical estimations of shadow wages in
industrialised countries also considered the role of the migration of workers induced by the project
and the presence of different categories of workers. For example, Picazo-Tadeo and Reig-Martinez
(2005) compute shadow wages for family labour in the Spanish agricultural sector exploiting the
properties of input and cost functions. Honohan (1998) estimates the shadow wage rate for the Irish
economy, characterised by high unemployment and inter-regional migration rates, by considering the
opportunity cost of an extra job as being equal to the loss of output of these migrants. Guillermo-Peon
and Harberger (2012) present a methodology based on dualism and migration with an application to
Mexico and derive estimates of the social opportunity cost of labour for 21 different occupations in 32
labour market areas.
The main shortcomings of earlier methodologies, especially those for developing countries in the
agricultural sector, are related to the need for very detailed project-specific data, which may be
difficult to obtain and which may lead to results lacking external validity. Applications to more
advanced countries and sectors, while overcoming this issue by considering regional data on
unemployment and migration, are still very data-demanding and involve complex estimation
procedures, which may be difficult to replicate and hamper cross-country analyses due to data
availability and comparability issues.
In order to overcome these potential problems, following Del Bo et al. (2011), an empirical
methodology to determine the value of the SW in the EU and the corresponding CF at regional level353
is proposed. This methodology, grounded in CBA theory, is based on the identification of four labour
market conditions at regional level based on the structural characteristics, which may impact on the
economic value, or social opportunity cost, of the labour input. For each labour market condition,
which differ in terms of per-capita GDP, short- and long-term unemployment, migratory movements
and the role of agriculture in the regional economy, an empirical formula for the computation of the
353 EU funds are typically aimed and allocated at the NUTS 2 level, suggesting this level of administrative and spatial disaggregation. If
projects are instead evaluated and funded at different levels (e.g. NUTS 3), the methodology can be easily adapted by using further
disaggregated data. http://epp.eurostat.ec.europa.eu/portal/page/portal/nuts_nomenclature/introduction
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SW is suggested, derived from a common theoretical framework. The value of the SW, and
corresponding CF, in each region is thus based on easily available regional and national data from
official statistical sources and does not rely on project-specific information, which may be difficult to
obtain and may lack external validity.
An applied methodology
In more detail, each region (the analysis can be carried out at the EU level or at a single country level)
is assigned to one of the four labour market conditions by means of a cluster analysis (see the box
below for more details on the methodology), and the corresponding regional SW and CF are calculated.
The four labour market conditions are: fairly socially efficient (FSE), quasi-Keynesian unemployment
(QKU), urban labour dualism (ULD) and rural labour dualism (RLD).
In FSE labour markets, unemployment is frictional and labour is paid at its marginal value, apart from
a distributional factor. Regions characterised by this type of labour market will typically be high
income, highly urbanised, with relevant incoming migration flows and low unemployment rates. QKU
labour markets are instead characterised by significant wage rigidities, which are reflected in high
official unemployment rates, both in the short and long term. These conditions will be found in high
unemployment, relatively low-income regions. Dual labour markets, characterised by a formal and
informal labour market, can be predominantly urban (ULD), where the presence of an informal labour
market attracts workers from the rural areas, or rural (RLD), where the excess labour is absorbed by
the agricultural sector and there are high net emigration rates.
The corresponding empirical formulae to be used to estimate the regional Shadow Wage Rate (SWR)
are laid out below.
Underlying the specific formulae corresponding to the four labour market conditions, is the idea that
“the net social cost of labour in the regional economy is a welfare-weighted linear combination of the
previous (ex-ante) and of the current (post-project) social value of the new job opportunity”. 354 This
translates in the following baseline equation:
SWR R R m1, R bw2,R
where subscript R refers to regions, m1 is the marginal productivity of the worker displaced by the
project in his/her previous sector of activity, w2 is a proxy of wages in a competitive labour market
where the worker can be employed thanks to the project, β is the regional welfare weight and b, the
marginal social value of a lump-sum transfer to consumers. The suggested proxy for b is represented
by b=(1-β) as the underlying simplifying assumption is that all workers’ income is spent in
consumption goods. In what follows the regional subscript is dropped and the appropriate sectors and
variables are considered depending on the region’s corresponding labour market condition.
In the FSE labour market, the social opportunity cost of labour can be found as:
w2
SWRFSE
Eq. 1 NPC ,
where: w2 represents the market wage rate in the FSE manufacturing sector, and NPC is a nominal
protection factor to account for country-wide price distortions355:
GVA1 GVA GVA1
NPC NPCEU
GVA GVA
with GVA and GVA1 representing gross value added in the whole economy and in agriculture,
respectively. The 1/NPC factor is a shortcut way to express wages in terms of shadow prices, and w2 is
354 Florio, 2014, p.161
355NPC
EU is the EU-27 average producer nominal protection coefficient (NPC) provided by OECD (2010), which accounts for price distortions
that are especially relevant in the agricultural sector, for example due to the EU Common Agricultural Policy.
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a proxy of wages in a competitive labour market. In regions characterised by a QKU labour market, the
SWR is instead computed as follows:
w2
SWRQKU rw (1 )
Eq. 2 NPC
where β is the regional welfare weights and rw the reservation wage.
In dual labour markets, if the region is predominantly urban (ULD case), the SWR is:
w 1 t w
SWRULD 2 1 2
Eq. 3 NPC NPC
where: w1 is the average regional agricultural wage rate, and (1-t) represents the benefit/tax wedge on
wages in the sector.
Finally, the SWR in rural dual labour markets (RLD case) is:
w 1 t w
SWRRLD 1 1 2
NPC1 NPC
Eq. 4
where: NPC1 is defined as NPC weighted by the ratio of the gross value added in agriculture over the
gross value added in the whole economy:
GVA1
NPC1 NPCEU
GVA .
As an illustration of the empirical methodology, using data from Eurostat and Cambridge
Econometrics, at the NUTS 2 level for the year 2007, regions from the EU-27 countries were classified
as belonging to one of the four labour market conditions considered by means of a robust cluster
analysis. Then the value of the shadow wage rate was computed for each region, according to the
empirical formulae presented above. The resulting conversion factors were then computed by using
data on regional market wages. The following map shows the results of the clustering procedure.
Figure IV.1 Results of cluster analysis: regional labour market conditions
Clustered on GDP, unemployment rate,
long term unemployment rate, rurality and migration rate
Legend
FSE: cluster 1
ULD: cluster 2
QKU: cluster 3
RLD: cluster 4
Source: Authors’ elaboration on Eurostat and Cambridge Econometrics’s data.
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Empirical results are summarised in the following table.
What is evident from the values of SW and CF, both from a visual inspection of the map representing
the different clusters and from reading the summary results per cluster, is that EU regions are
characterised by wide variability, both within and across countries. The highest CFs are found, as
expected, in FSE regions, followed by those in regions characterised by a ULD labour market. The
lowest CF, which reflects the highest wedge between SW and market wages, are detected in regions
with QKU characteristics, suggesting that the distortions here are relevant.
This empirical exercise has thus highlighted the presence of rather heterogeneous labour market
conditions in EU regions and suggests the need for taking these into account properly when evaluating
the desirability, in a CBA perspective, of projects funded by EU funds.
Table IV.1 Results of the empirical analysis: shadow wages and conversion factors
Regional labour market conditions Hourly shadow wage Conversion factor
Rate
FSE (fairly socially efficient) 45.239 0.99
QKU (quasi-Keynesian unemployment) 12.111 0.54
ULD (urban labour dualism) 27.143 0.80
RLD (rural labour dualism) 5.217 0.62
Source: Del Bo et al. (2011).
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Annex V. Tariff setting, polluter-pays
principle and affordability analysis
Projects may generate revenues from the sale of public services to citizens, for example water and
sanitation services, or solid waste management services. These revenues are determined by the
quantities of service provided and by their price, usually determined in the form of tariffs.
In setting the tariff level, compliance with the full-cost-recovery and the polluter-pays principles shall
be fulfilled.
According to the full-cost-recovery principle, the tariff level shall be fixed so as to recover the capital
costs of the investment before public subsidies and the operating and maintenance costs, including
costs for the replacement of short-life equipment during the reference period.
The application of the polluter-pays principle requires that the tariff structure also includes
environmental and resource costs. The tariff should be modulated to encourage the introduction of
charging systems when the environmental costs of pollution and preventive measures are borne by
those who cause pollution. Also, the resource costs associated with depletion of an environmental
asset (e.g. water) should be reflected (see box).
THE POLLUTER PAYS PRINCIPLE
A fundamental principle for the evaluation of EU projects is the polluter-pays principle, which, according to
regulations, should be used for the modulation of the co-financing rate. Article 61 (Operations generating net
revenue after completion) states that: 'The net revenue generated after the completion of an operation over a
specific reference period shall be determined taking into account […] the application of the polluter-pays
principle and, if appropriate, considerations of equity linked to the relative prosperity of the Member State or
region concerned.’
The compliance with the polluter-pays principle requires that charging systems are proportional to the social
marginal production costs of production, which include:
- the long run marginal cost of environmental services;
- the environmental costs of pollution and of the preventive measures implemented;
- the costs linked to the scarcity of the resources used.
Source: European Commission (2013)
Although the introduction of tariffs in line with the full-cost-recovery and polluter-pays principles may
imply a lower contribution from the EU356, an appropriate charging system has a positive effect on the
project's financial sustainability.
On the other hand, a trade-off discussion between the policy of fully cost-reflective tariffs and
affordability concerns may arise in some sectors that provide public services, such as environment
or energy. Traditionally in public service sectors there are cross-subsidies from the intensive (rich)
users and the low (poor) users and from taxpayers to users, and the solution of the trade-off is usually
the responsibility of the regulators of the Member States. Project promoters in these sectors should
adequately present and discuss the criteria used for tariff setting and the relative affordability issues
that may influence the project’s success and performance.
356 When the method of the calculation of the discounted net revenue is applied to determine the EU assistance.
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Affordability analysis
The concept of affordability refers to the ability of particular consumer groups to pay for a minimum
level of a certain service357. In literature different approaches to measure affordability have been
identified; however, the most common way is to calculate the so-called 'affordability ratio', i.e. the
crude ratio between the expenditure on a given utility service and the household's total income. The
following table provides an example of expenditure ratios for some selected EU and non-EU countries
for illustrative purpose.
Table V.1 Expenditure over income (%) for all households
Source: Florio, 2013, Network Industries and Social Welfare, based on Lampietti et al. (2007).
The following list of principles should be respected while carrying out an affordability analysis.
The establishment of general affordability limits is a prerogative of each Member State and,
where considered necessary, they should be set and communicated by the responsible national
authority(ies) at the country level for each relevant service/sector and applied to all projects
developed for that service/sector without distinction.
When establishing the affordability limits for a certain service/sector, the national authorities
should take into consideration the affordability limits defined for other services/sectors as
well. Member States are encouraged to develop a general affordability policy and, based on
this, distinguish between individual sectors.
Affordability limits, generally, should only apply to the tariffs paid by residential users (i.e.
households) and not by companies (industrial and commercial users) or institutional
users/consumers, unless there is a good justification for it.
The general affordability limit is to be expressed as an affordability ratio based on household
income data (e.g. net disposable household income), so as to allow a differentiation of absolute
affordability limits among different regions or areas in a country. The referential income group
for which affordability limits are established should be clearly defined.
In the absence of household income surveys for the project area, income estimates should be
taken from available regional official statistics for the last three to five years. Forecasts should
be carried out by adopting the same national/regional macroeconomic forecasts (including
GDP growth, development of employment and unemployment, gross/net salaries) that were
discussed in the presentation of the project’s context (see Chapter 2).
In sectors for which affordability limits have been established, service tariffs should generally
not go beyond the defined affordability ratio358. Wherever required, the social planner must
357 See, for example, Fankhauser and Tepic, 2007.
358In justified cases, however, i.e. to ensure the financial sustainability of an appropriately sized investment, there could still be the
need/possibility to temporarily raise tariffs above the affordability limit.
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identify possible remedies (including, for example, progressive tariffs, vouchers or
subsidies359) so as to ensure social affordability for the poorest household incomes on the one
hand, and the project’s financial sustainability on the other. In general, limitations to the
application of the polluter-pays and full-cost-recovery principles due to affordability concerns
should, however, be seen as temporary restrictions and maintained only as long as the
affordability limitation of users exists.
Where tariffs paid by residential users (households) before the project are lower than the
defined affordability limit, the project promoter should make a proposal for their gradual
adjustment up to the defined limit. An appropriate pace and timing for such adjustments
should be duly considered as well, i.e. paired with visible signs of work progress and/or
service quality improvements, in order to increase the acceptability of users. Once the project
is completed and the start of the new service/service improvements is tangible for users,
residential tariffs should, in principle, not be lower than the affordability limit.
In the long-term, the target is to reach full cost recovery of the tariff, including capital and O&M
costs, in accordance with the polluter-pays principle and the related full-cost-recovery
principle. This should be implemented gradually over the reference period, as soon as the
affordability analysis allows. In practice, tariffs should be continuously adjusted following the
predicted household income growth. For users for which no affordability limits exist, the
appropriate tariff should be applied from the first year of project operations.
Adequate indicators can be used to express the level of cost recovery of service fees/tariffs
paid by users (e.g. percentage of 'levelised unit costs'360, calculated by including total O&M and
capital costs).
Evaluation of distributive impact
The affordability analysis is a short-cut approach to include distribution considerations in project
evaluation. Since shadow prices do not capture the distribution of project costs and benefits across
users and other stakeholders well, there is a need for a distinct analysis of the project impact on the
welfare of specific target groups.
As illustrated in section 2.9.11, the recommended approach by this guide for the analysis of
distributional issues is the use of the Stakeholder Matrix, adopted from the RALIPAG Guide.
Nevertheless, another method, which consists of deriving welfare weights from social inequality
aversion estimates to be attached to the project winners and losers, can be possibly used. This method
is discussed below.
To define welfare weights, we can refer to the declining marginal utility of consumption: utility
increases with a rise in consumption but the increments get smaller the more we consume361. The
elasticity of marginal utility of income – already dealt with in Annex II in regard to the social discount
rate – measures this particular effect.
Under some assumptions362 the welfare weights normalised to the average household are structured
as follows:
359 Policy-makers considering new subsidies should, however, assess their impact on the underlying economic and environmental reality in
order to ensure consistency with existing policies on reducing Environmentally Harmful Subsidies (see:
http://ec.europa.eu/environment/enveco/taxation/pdf/Harmful%20Subsidies%20Report.pdf).
360 The 'levelised cost' is calculated as the present value of life-cycle (capital and operating) costs divided by the present value of the project
output (in physical units) over the reference period.
361 In the case of the commonly assumed iso-elastic social utility function, the expression for marginal utility is as follows: MUy = Y-e.
If e were to take a unitary value, for which there is some empirical support, then we have: MUy = Y-1 = 1/Y.
362 The most important assumption is that an iso-elastic social utility function applies and is relevant across the complete range of incomes,
so that the same value of e holds for all income classes.
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e
C
W
Ci
where: C is the average consumption level, Ci is the per capita consumption in the group, and e is the
elasticity of marginal utility of income363.
Thus, expressing the effect of adopting welfare weights with an example, let us suppose there are in a
region the following per capita income groups: 3 000, 2 500 and 1 250 with an average of 2 250 (see
the table below).
Table V.2 Example of welfare weights
Classes Consumption e=0 e=0.3 e=0.7 e=1.2
(C / Ci )
High income 3 000 0.75 1 0.9173 0.8176 0.7081
Medium income 2 500 0.90 1 0.9689 0.9289 0.8812
Low income 1 250 1.80 1 1.1928 1.5090 2.0245
Average 2 250 1 1 1 1 1
From the tax schedule, we can obtain an estimate of the elasticity of marginal utility of income with the
same method that is explained in Annex II. We can easily see from the table that with the same
revenue distribution, weights differ greatly depending on the value of e.
The elasticity parameter is a planning signal that, in principle, should be given to the project analyst by
the managing authority at national level. Roughly speaking, we can say that zero elasticity implies
unitary welfare weights; hence, EUR 1 is EUR 1 in welfare terms, whoever the ‘winner’ or ‘loser’ of the
project adoption. Values between zero and one will fit with moderate inequality-aversion; e above one
will be adopted by more egalitarian social planners.
Let us suppose, as in the table below, that the marginal utility of income is equal to 1.2 and the total net
benefits of a project reach ENPV=300. These benefits would mainly be for the disadvantaged
households and the use of welfare weights allows us to give more importance to these benefits. In
particular, the amount of net benefits (140) obtained by the low-income class is, with our weights,
worth 283.43 and the entire project is worth 414.04. This effect is obtained by applying a progressive
tariff structure so that the charge rate increases as the consumption amount increases.
Table V.3 Example of weights for progressive distributional impact
Classes Net benefits Elasticity 1.2 Distributional impact
High income 60 0.7081 42.49
Medium income 100 0.8812 88.12
Low income 140 2.0245 283.43
Total 300 414.04
In other situations, however, as in the table below, welfare weights may reduce the social value of the
project. This effect is obtained when a regressive tariff structure is in place so that the charge rate
decreases as the amount of consumption increases.
Table V.4 Example of weights for regressive distributional impact
Classes Net benefits Elasticity 1.2 Distributional impact
High income 160 0.7081 113.29
Medium income 100 0.8812 88.12
Low income 40 2.0245 80.98
Total 300 282.39
363 See Evans, Kula and Sezer (2005) for further elaboration and the measurement of welfare weights in a regional context.
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Annex VI. Willingness-to-pay approach to
evaluate direct and external impacts
Use of the willingness-to-pay approach
As illustrated both in the main text and in Annex III, the willingness-to-pay (WTP) approach, together
with that of the willingness-to-accept (WTA), can be usefully applied to quantify both the direct
benefits and the impacts, negative or positive, of the external effects of the project364.
Table VI.1 below schematically shows the general paradigm of the use of the WTP/WTA concept in the
CBA of the investment projects.
Table VI.1 Diagram of the paradigmatic approach of the WTP/WTA in the CBA
Project Project Quantification
Target of the evaluation Tradable/non tradable
effect outcome approach
Traded on distorted market Conversion factors*
Input
Market Non tradable Border prices
prices Traded on distorted market
Total value of benefits Output Willingness to pay
and costs Non tradable (or willingness to
accept)
Non tradable
Positive/
Externalities Environmental service market Actual related market
negative
available price**
* Willingness to pay only in special cases, see Annex III. **Where appropriate, i.e the market price reflects the marginal
damage cost of pollutions.
The WTP measures the maximum amount people would be willing to pay to gain outcomes that they
view as desirable or, alternatively, the maximum amount that people would be willing to pay to avoid
outcomes they view as undesirable. The WTA measures the minimum amount of money the seller
would be willing to accept to give away the good. In the economic theory, the equilibrium value of
WTP and WTA are, in principle, equivalent so that the choice between the WTP and WTA measures
reflects a choice between alternative Hicksian welfare measures (i.e. compensating versus equivalent
variation). Yet, it has been empirically shown that individuals tend to give higher estimates of WTA
than of WTP. This is because people tend to demand higher monetary compensations to give up goods
they have, than the price they say they would be willing to pay to buy the same good they do not have.
For this reason, the literature recommends the preferable use of WTP365. Thus, the next sections will
mainly refer to the concept of WTP, which is that more widely used in the practice of CBA.
As underlined above, the outputs may include both goods and services actually sold onto the market
and externalities. In the former case, even if a tariff, a fee or duty is paid by users, this could be
distorted and not reflect either the total cost of production or any additional social benefit and cost
entailed in the production of that good or service366. In similar situations, the monetary level of the
financial income is not the ‘true’ socioeconomic value of the output, but is the WTP that provides a
better estimate for the social value of the good or service than the observed tariffs.
The importance of using the WTP approach is even equally evident when externalities, for which no
monetary compensation is paid, are produced by the project. The externalities have to be
‘internalised’, i.e. valued in monetary terms and brought into the economic analysis of the project. For
364 WTP can also be used when valuing inputs entering the project's production process, whose use in the project leads to an adjustment in
the net demand of other consumers of that good. This latter methodological scope of the use of WTP has been already discussed in Annex III.
365
See also Annex III about the same theme.
366
The various causes of distortion of the prices observed in the market have been discussed in the main text of this guide.
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both positive and negative externalities, the WTP provides, in most cases, a reference estimate of their
social value. This enables valuing the total welfare improvement, taking into account welfare changes
in all gainers and losers of the project.
Valuing environmental impacts
External impacts of a project are mainly due to its effects on the environment during all phases of its
life367. Most public infrastructure projects have negative or positive impacts on the local and global
environment368. Typical environmental impacts are associated with noise, local air quality, GHG
emissions, water quality, soil and groundwater quality, biodiversity and landscape degradation, and
technological and natural risks. A decrease or increase in the quality or the quantity of environmental
goods and services will produce some changes, gains or losses in social benefits associated with their
consumption.
For example, a road infrastructure will be expected to reduce the availability of useful rural land, will
change rural landscape, will increase pressures on biodiversity and negatively affect air quality due to
increased traffic flows, locally, in the areas adjacent to the new road. Each of these impacts will reduce
the provision of ecosystem services and will lower economic benefits. On the contrary, the effect
(planetary scale) of the new road on greenhouse gases can result in lowering them, due to the reduced
unit travel time, and the lower consumption of fuel and of the vehicles transporting passengers and
goods. Looking at these effects, the project has a marginally positive impact on the environment, in
comparison to the situation without the project, because it limits the reduction on the provision of
environmental services by the ecosystems and will thus increase economic benefits.
As another example, investments in waste treatment facilities will decrease environmental negative
local impacts on soil, water and air. Similarly, investments in wastewater treatment systems reduce
the pollutants discharged at the local level into the natural aquatic environment (rivers, lakes, sea,
transitional waters and estuaries). In both examples above, implementing the project, in addition to
allowing to supply the proper service (disposal of waste in the first case and wastewater treatment in
the second) in favour of the users (consumers), will result in an external environmental effect, which
will increase economic benefits related to the provision of high-quality environmental services to
economic agents (consumers and producers).
In other cases, the effect on the environment of the project can be more indirect, but no less important.
This is the case, for example, of the investments to reduce water losses in water networks. Although
the main objectives of these projects are, in general, savings in operating costs and improving the
quality of service for users, these projects also result in reduced amounts of water derived from
natural sources and therefore can result in a safeguard and even in an improvement of the affected
aquatic environment.
Not taking into account environmental impacts will result in an over- or underestimation of the social
benefits of the project and will lead to bad economic decisions. In other words, the economic
evaluation of the environment helps decision-makers to integrate into the decision-making process
the value of environmental services provided by ecosystems. Direct and external environmental
effects must be expressed in monetary terms in order to integrate them into the calculation of
homogenous aggregate CBA indicators of net benefits (see box below).
When environmental service markets are available, the easiest way to measure economic value is to
use the actual related market price. For example, when marine pollution reduces fish catches, market
values for the lost harvest are easily observed in the fish market. When there is no market, the price
can be derived through non-market evaluation procedures. This is the case, for example, of air
367 Externalities may also include non-environmental effects, such as the effects on urban functions during the construction phase of the
infrastructure or the impacts on the same functions in the medium-to-long run due to new services made possible by the project (e.g.
congested traffic during the events held in a new exhibition structure). In most cases these externalities can be treated as well as those that
are environmental, i.e. introducing appropriate WTPs in the socioeconomic analysis.
368 These impacts include those directly affecting the environment (physical and biological), and those of an anthropogenic nature, i.e. on
human health, at all levels (local, regional and global), if that is the case.
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pollution since no market value can be associated with clean air. The recommended approach is
therefore to evaluate a proper WTP (or WTA) to quantify the cost/benefit for the environment (see
Figure VI.1).
In the next sections, the main methods available to value environmental effects are outlined.
Figure VI.1 Main evaluation methods
Source: Pearce, Atkinson, and Mourato (2006).
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TOTAL ECONOMIC VALUE
The monetary measure of a change in an individual’s well-being due to a change in environmental quality is
called the total economic value of the change. The total economic value of a resource can be divided into use
values and non-use values; i.e. total economic value = use values + non-use values.
- Use value. This refers to the social value people have from actually using a good or potentially using it in the
future (e.g. recreational activities, productive activities such as agriculture and forestry, etc.), as well the benefits
derived from the goods and services provided by the ecosystem that are used indirectly by an economic agent
(e.g. the purification of drinking water filtered by the soil). They are called, respectively, 'actual', 'option' and
'indirect' values. In this context, uncertainty stems from a combination of the individual’s uncertainty about
future demand for the resource and uncertainty about its future availability.
- Non-use value. Each individual could be assumed to place a value not only on the well-being produced by the
good’s existence per se on himself/herself (existence value), but also on the well-being caused to other
individuals by the availability of that good, either in the same generation (altruist value) or future generations
(bequest value). Non-use values are less tangible than use values since they do not refer to a physical
consumption of goods and services.
Values are directly linked to the ecological services produced by the ecosystems, which support them. A
reduction in the provision of ecological services (by a pollution, for example) is likely to depreciate the values
expressed by people on environmental quality with, as a final result, a decrease in social benefits associated with
it. It is important to understand that economic value does not measure environmental quality per se; rather it
reflects people’s preferences for that quality. Evaluation is ‘anthropocentric’ in that it relates to preferences held
by people.
Source: EU (2013) The Economic benefits of the Natura 2000Network
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Dose-response functions
The dose-response technique aims to establish a relationship between environmental impacts (the
response) and physical environmental impacts such as pollution (the dose). The technique is used
when the dose-response relationship between the cause of environmental damage, such as air or
water pollution, and the impacts, for example morbidity due to air pollution or water contamination
by chemical products, is well known. The technique takes natural science information on the physical
effects of pollution and uses this in an economic model of evaluation. The economic evaluation will be
performed by estimation, through a production or a utility function of the profit variations of
businesses or the revenue gains or losses of individuals.
The two steps of the method are:
the calculation of the pollutant dose and receptor function, and
the economic evaluation by the choice of an economic model.
To assess the monetary gain or loss of benefits due to the variation in environmental quality requires
the analysis of biological and physical processes, their interactions with economic agents’ decisions
(consumer or producer) and the final effect on welfare.
The major fields of application of the methodology are the evaluation of losses (in crops, for example)
due to pollution, the pollution effects on ecosystems, vegetation and soil erosion, and the impacts of
urban air pollution on health, materials and buildings. The approach cannot estimate the non-use
value.
Estimating the willingness to pay
Different methods can be adopted to empirically estimate the WTP as a welfare measure. Three main
methodological categories (i.e. revealed preference methods; stated preference methods; benefit
transfer method) are discussed below, which are well established and consolidated in both the theory
and practice of CBA. That said, research in this area is ongoing and novel approaches are being
developed369. The methodology is still evolving and existing valuations are not robust enough yet for
use in value transfer for CBA, but due consideration will be given to future developments.
Revealed preference methods
This approach implies that the valuation of non-market impacts is based on the observation of the
actual behaviour and, especially, on the purchases made in actual markets. Consequently, the focus is
on real choices and implied willingness to pay. The strength of these approaches is that they are based
on actual decisions made by individuals. The main weakness is the difficulty of testing the behavioural
assumptions upon which the methods rely. The main specific methods are:
hedonic pricing/wage method;
travel cost method;
averting or defensive behaviour method.
Hedonic pricing/wage method
The focus of this method is in the observation of behaviour in markets for goods related to the ones
the analyst is evaluating. The starting point is the fact that the prices of many market goods are
369 For instance, the UK Treasury has recently published new supplementary guidance on valuation techniques for cost-benefit analysis that
adds the subjective well-being approach to the standard revealed and stated preference methods: 'the subjective well-being approach has
been gaining popularity in recent years, which attempts to measure people‘s experiences rather than expose their preferences. The Life
Satisfaction Approach uses reported life satisfaction in surveys such as the ONS‘s Integrated Household Survey, which began including
questions on respondents‘ subjective well-being in April 2011, to value non-market impacts. The approach uses econometric methods to
estimate the life satisfaction provided by non-market goods, and this is then converted into a monetary figure by also estimating the effect of
income on life satisfaction. The approach therefore assesses the impact of policies on how people think and feel about their lives as a whole,
instead of assessing impact based on what people say they want and what they choose.' (Fujiwara and Campbell, 2011, p. 7).
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functions of a bundle of characteristics. For example, the price of a washing machine usually depends
on the variety of washing programmes, its energy efficiency and its reliability. Through statistical
techniques the method tries to isolate the implicit price of each of these characteristics.
In non-market evaluation the method uses two types of markets:
property market,
labour market.
With regard to the property market, houses can be described through their structural characteristics
(e.g. number of rooms), locational characteristics (e.g. proximity to schools), neighbourhood
characteristics (e.g. crime rates) and environmental characteristics (e.g. road traffic noise). The
hedonic pricing method should identify the contribution of each significant determinant of house
prices in order to estimate the marginal willingness to pay for each characteristic. Hedonic studies of
the property market have been used to identify the value of non-market goods, such as traffic noise,
aircraft noise, air pollution, water quality and proximity to landfill sites. A house near an airport, for
example, will be purchased at a lower price than a house located in a quiet area, everything else being
equal. The difference in values can be viewed as the value attached to noise. The creation of an urban
park in a disused industrial area or the urban improvement of a neighbourhood result in an increase in
the market value of the properties in the project area. The total increase of the estate value is a good
proxy of the socioeconomic benefit of the project.
In the labour markets, the observation of wage differentials between jobs with different exposure to
physical risk is used in order to estimate the value of avoiding risk of death or injury.
Specific problems with this approach could be a lack of information on household data and the fact
that market characteristics tend to move in tandem; it is often hard to ‘tease out’ the independent
effect of a single characteristic. For further information on how to conduct the hedonic price analysis
with one of the methods, see the relevant bibliography.
EXAMPLE: HEDONIC PRICE TO QUANTIFY THE BENEFIT OF AN URBAN AMELIORATION
The project concerns a small neighbourhood that includes residential and commercial areas and services in a
medium-sized town. The socioeconomic benefit of the intervention can be valued by the expected increase in the
real estate prices of buildings in the neighbourhood due to the improved urban functions. This is the hedonic
price, regardless of whether the properties will be actually traded.
The used surfaces of the buildings amount to 535 500 square meters. Taking into account the different
destinations of use, the average price on the real estate market in the neighbourhood is currently EUR 1 110/m2.
Looking at the real estate market in other districts of the same city and at other cities with similar
characteristics, analysts have concluded that the average price in the areas already rehabilitated, which is
obviously higher, may be set at EUR 1 385/m2. The potential increase in the price of the real estate is therefore
1 385 – 1 110 = EUR 275/m2. Therefore the total benefit of the project amounts to 535 500 x 275 =
EUR 147 262 500.
Given that the positive impact of the project on the neighbourhood does not develop in a single moment, but will
take some time, the total benefit, as calculated above, should be appropriately divided into a proper number of
years of the time horizon of the analysis. For example, if the urban rehabilitation works take two years, and
assuming that the effects will develop in the next three years, it will be appropriate to allocate three equal inputs,
each of EUR 49 087 500, over the third, fourth and fifth years of the analysis horizon.
Source: Authors
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Travel cost method
The travel cost approach seeks to put a value on individuals WTP for access to environmental
resources, for instance outdoor recreation areas, by looking at the costs incurred to access them.
The basis of the method is the observation that travel and outdoor recreation areas are complements
such that the value of the recreation areas can be measured with reference to values expressed in the
markets for trips to those areas. For zones located too far from the area the number of visits is zero
because the cost of the trip exceeds the benefit derived from the trip. Therefore it is important to know
the following:
the number of trips to the outdoor recreation areas over a given time period;
the costs of the trips to these from different zones, split into different components:
o the monetary costs; including travel costs, admission price (if relevant), on-site
expenditures, expenditure on capital equipment necessary for consumption;
o the time spent travelling and its value.
Specific problems with this approach are related to 'multiple purpose trips'; because many trips have
more than one destination, it is difficult to identify which part of the total travel cost is related to one
specific destination. Another problem is that the travel cost method allows an estimation of the WTP
for the entire site, rather than a specific feature of it and this may make it problematic to estimate the
value of a change in one attribute of a multi-dimensional good.
Since only the benefits of the direct consumption of the environmental services are considered in this
approach, non-use (existence, altruist and bequest) values cannot be considered.
EMPIRICAL ESTIMATION OF THE RECREATION VALUE OF ECOSYSTEMS
Mendes and Proença (2005) provided an example of empirical estimation on the recreation value of ecosystems.
They proved that the Portuguese Peneda-Gerê National Park is able to produce a significant social benefit, which
could justify the allocation of more public resources to eco-tourism activities.
Starting from the generic economic definition that the marginal recreation value of an ecosystem is equal to the
amount visitors would pay to enjoy recreation and leisure activities, the authors estimated the relationship
between the costs incurred by travellers to a site and the number of trips taken. During the 1994 summer peak-
period months, questionnaires were distributed to Portuguese citizens’ over 18 years old who were visiting the
park at that time for visits equal or longer than 24 hours. Information was gathered about the number of days of
stay, income, the geographical origin, the cost of the trip, transportation mode and various demographic
characteristics. The demand of recreation per trip has been modelled as a function of the cost incurred, available
income and individual characteristics (plus an independent error term). The consumer surplus of the
representative visitor per each average day of stay has been derived by integrating the recreation demand
function over the relevant cost change. From here, the value of the willingness to pay has been estimated through
the formula proposed by Grogger and Carson (1991) and Englin and Shonkwiler (1995).
Results show one recreation day was valued EUR 124 (2005 prices) for the average representative visitor of the
sample. Considered that approximately 12 000 visitors camp in the park every year, this generates a benefit of
EUR 1 488 000.
Source: Florio (2014)
Averting or defensive behaviour method
The main assumption of the averting evaluation method is that individuals can insulate themselves
from a non-market good by adopting more costly behaviours to avoid it. The cost these behaviours
require can be represented by extra time or by the restrictions they impose on what individuals would
otherwise wish to do.
Another way to avoid exposure to a specific non-market good is the purchase of a market good to
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‘defend’ the consumer from the ‘bad’ (defensive expenditures). The value of each of these purchases
can be considered the implicit price for the non-market good that individuals want to avoid.
An example could be the installation of double-glazed windows to decrease exposure to road traffic
noise. Double-glazing is a market good that can be seen as a substitute for a non-market good (absence
of road traffic noise) and so the cost of purchasing it can be considered as the price of the non-market
good. Specific problems with these approaches could be:
defensive expenditures often represent a partial estimate of the value of the non-market good
individuals want to avoid;
many averting behaviours or defensive expenditures are related to joint products (e.g. heating
and insulation from noise);
individuals or businesses may undertake more than one form of averting behaviour in
response to any environmental change.
Stated preference methods
Stated preference approaches are survey-based and elicit people’s intended future behaviour in the
markets. Through an appropriately designed questionnaire, a hypothetical market is described where
the good in question can be traded. A random sample of people is then asked to express their
maximum willingness to pay for (or willingness to accept) a supposed change in the good’s provision
level.
The main strength of the methods based on this approach is represented by the flexibility they can
assure. Indeed, they allow the evaluation of almost all non-market goods, both from an ex ante and
from an ex post point of view. Moreover, this methodology is able to capture all types of benefits from a
non-market good or service, including the so-called non-use values.
The main specific methods are:
contingent valuation method,
choice modelling method.
Contingent valuation method
The aim of the contingent valuation method is to elicit individual preferences, in monetary terms, for
changes in the quantity or quality of a non-market good or service.
The key element in any contingent valuation study is a properly designed questionnaire. The
questionnaire aims to determine individuals’ estimates of how much having or avoiding the change in
question is worth to them. In order to conduct a contingent valuation it is worthwhile:
investigating the attitudes and behaviour related to the goods to be valued in preparation for
answering the valuation question and in order to reveal the most important underlying factors
driving respondents’ attitude towards the public good;
presenting respondents with a contingent scenario that provides a description of the
commodity and the terms under which it is to be hypothetically offered. The final questions
should aim to determine how much they would value the good if confronted with the
opportunity to obtain it under the specified terms and conditions;
asking questions about the socioeconomic and demographic characteristics of the respondents
in order to check the extent to which the survey sample is representative of the population
involved;
asking respondents whether they would be willing to pay a specified amount for the good; if
the answer is affirmative, the interviewer would repeat the questions by slightly increasing the
price until the respondent expresses an unwillingness to pay the amount specified.
At the end of the survey process, analysts use appropriate econometric techniques to derive welfare
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measures, such as mean or median willingness to pay and also to identify the most important
determinants of willingness to pay. With regard to the statistical indicators to be used, the median
could be the best predictor of what the majority of people would actually be willing to pay because,
unlike the mean, it does not give much weight to outliers.
Problems with contingent valuation are associated with the probability that respondents do not fully
understand the scenario or what the good in question is, or that they are not willing to attach a
monetary value to certain goods (such as, for example, the value of a human life). Additionally, Carson
and Groves (2007) point out that an increase in the provision of a public good for which only voluntary
contribution is asked, is generally overvalued: this is because respondents have an incentive to free-
ride in order to increase the chances of provision of the desired good without having to pay for it.
Choice modelling method
Choice modelling (CM) is a survey-based method for modelling preferences for goods, when goods are
described in terms of their attributes and of the level of these attributes. Respondents have various
alternative descriptions of a good, differentiated by their attributes and levels, and are requested to
rank the alternatives, to rate them or to choose their preferred option. By including price/cost as one
of the attributes of the good, willingness to pay can be directly recovered from people’s rankings,
ratings or choices. Also, in this case, the method allows the measurement of non-use values.
The main variants proposed in specialist literature are described in the following table.
Main variants of the CM method Tasks
Choice experiments Choose between two or more alternatives (where one is the status quo)
Contingent ranking Rank a series of alternatives
Contingent rating Score alternative scenarios on a scale of 1 to 10
Paired comparison Score pairs of scenarios on a similar scale
The main strengths of the method are:
the capacity to deal with situations where changes are multi-dimensional, thanks to its ability
to separately identify the value of the specific attributes of a good;
the possibility for respondents to use multiple choices (for example variants in choice
experiments), to express their preference for a valued good over a range of payment amounts;
by relying on ratings, rankings and choices, and deriving indirectly from the willingness to pay
of respondents, the method overcomes some problems associated with the contingent
valuation method.
The main weaknesses are:
the difficulties respondents experience in dealing with multiple complex choices or rankings;
the inefficiency in deriving values for a sequence of elements implemented by a policy or
project. For these types of evaluations contingent methods should be preferred;
the willingness-to-pay estimate is sensitive to study design. For example, the choice of
attributes and levels to present to the respondents and the way in which choices are relayed to
respondents (use of photographs, text description, etc.) may impact on the values of estimates.
Benefit transfer method
Developments in policy behaviour have stressed the relevance of the so-called benefit transfer
approach (or method) in the appraisal of non-market goods, specifically environmental goods and
services (Pearce, Atkinson and Mourato, 2006). This method consists of taking a unit value for a non-
market good estimated in an original study and using this estimate, after some adjustments, to value
benefits (or costs) that arise when a policy or project is implemented elsewhere.
The benefit transfer method can be defined as the use of a good estimate in one site, the ‘study site’ as
a proxy for values of the same good in another site, the ‘policy site’. For example, the provision of a
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non-market good at a policy site could refer to a lake at a particular geographical location. If sufficient
data is not available for that country, analysts can use values for similar conditions in data-rich
countries.
The interest shown in this approach is due to the opportunity to reduce the need for costly and time–
consuming original studies of non-market goods values. Moreover, benefit transfer could be used to
assess whether or not a more in-depth analysis is worthwhile.
Clearly, the main obstacle in using this approach is that benefit transfer can give rise to seriously
biased estimates, though obviously judgement and insight are required for all the basic steps entailed
in undertaking a benefit transfer exercise. For example, information needs to be obtained on baseline
environmental quality, changes and relevant socioeconomic data.
Benefit transfer is usually performed in three steps:
compilation of the existing literature on the subject under investigation (recreational activity,
human health, air and water pollution, etc.);
assessment of the selected studies for their comparability (similarity of the environmental
services or benefits valued, difference in revenue, education, age and other socioeconomic
characteristics which can affect the evaluation);
calculation of values and their transfer in the new context of evaluation.
The most crucial stage is where existing estimates or models are selected and the estimated effects are
obtained for the policy site. In addition, the population at the relevant policy site must be determined.
Adjustments are usually advisable in order to reflect differences at the original study sites and the new
policy sites. The analyst may choose from three main types of adjustment of increasing sophistication:
unadjusted willingness-to-pay transfer. This procedure implies a simple ‘borrowing’ of the
estimates made in the study site and the use of those estimates in the policy site, with an
obvious advantage in terms of simplicity;
willingness-to-pay transfer with adjustment (value transfer). It could be useful to modify the
values from the study site data to reflect the difference in a particular variable that
characterises the sites; for example, the values can be adjusted through multiplication using
the ratio between the income level of the study case and the income level of the policy case;
willingness-to-pay function transfer. A more sophisticated approach is to transfer the benefit
or value function from the study site to the policy site. Thus, if it is known that the willingness
to pay for a good at the study site is a function of, first, a range of physical features on the site,
second, of its use, and third, of a set of socioeconomic characteristics of the population at the
site, then this information itself can be used as part of the transfer process.
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EXAMPLE: BENEFIT TRANSFER METHOD TO VALUE THE WTP FOR WASTEWATER TREATMENT
The benefit transfer method was used by the European Commission to value the willingness to pay (WTP) for the
construction of nine waste water treatment plants in eight municipalities of Ría de Vigo (Spain). Implemented
between 1995 and 2000, the infrastructure project was addressed to improve the quality of life of beneficiaries,
thanks to the possibility of enjoying cleaner water and more numerous bathing beaches. The reference studies to
estimate the WTP for the waste water treatment of Ría de Vigo were selected from a database of 40 cases (US
Environmental Protection Agency 2000a, 2000b, 2000c; Källstrøm 2010) on the basis of two criteria: the type of
project and the socioeconomic context of the country. With regard to the former, only waste water treatment
projects that were effective in improving the quality of the water basin and in which the sewerage system was
already in place, as in the municipalities of Ría de Vigo, were selected. For the selection of the most similar
socioeconomic context, evaluators considered projects in those countries falling under the classification of very
high and highly developed countries, according to the UNDP Human Development Index 2011. These first two
steps enabled the identification of 28 projects in different countries of the world. The WTP values that referred
to each of the 28 selected projects were divided by the national per capita GDP, which was taken as a proxy of the
differences in the per capita income.
The WTP for the project in Ría de Vigo was then calculated as the average WTP for the 28 projects considered,
weighted by GDP, and in turn weighted by Spanish per capita GDP. This amounted to EUR 88.11 per household
(2011 prices). The described methodology implicitly assumes the income elasticity of WTP as being equal to 1,
meaning that the ratio of WTP valued in each of the 28 reference countries and in Ría de Vigo is equivalent to the
ratio of per capita GDP at the different sites.
Source: European Commission (2012)
For all types of adjustments, the quality of the original study is of paramount importance for the
validity of the method.
Some databases have been set up to facilitate benefit transfer. This is the case with the EVRI
database370 developed by Environment Canada and the US Environment Protection Agency. More than
700 studies are currently available in the database, but only a minority are of European origin and this
fact reduces the usability of the database in a European context. GEVAD is an online European
database, which was co-funded by the European Social Fund and Greek government resources. The
aim of the project was to create a free online environmental valuation database, by gathering a critical
mass of European valuation studies. About 1 400 studies were reviewed, focusing on the ones that
were spatially more relevant to Europe. Emphasis was also placed on the most recent research results.
So far, more than 310 studies have been included in the GEVAD database. These studies are classified
according to the environmental asset, good or service, which is valued (e.g. amenities, water and air
quality, land contamination, etc.), the valuation method used, the main author and the country of the
‘study site’.371
370
The database is accessible through the following link: http://www.evri.ca/
371
The database is accessible through the following link: http://www.gevad.minetech.metal.ntua.gr/
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SOME ESTIMATES OF VOSL IN UK
As explained in the main text, the WTP for mortality risk reductions is normally expressed in terms of the value
of statistical life (VOSL). The following table has a variety of estimates on the VOSL, mostly for the UK. There is
some unease about using the value of statistical life in contexts where remaining years may be few for the
affected individuals and this has led to the use of ‘life year’ valuations derived from VOSL. For example, the
concern is that estimates of VOSL from studies of workplace accidents (which tend to affect healthy, middle-aged
adults) and road accidents (which tend to affect median-aged individuals) are ‘too high’ when transferred to
environmental contexts where mortality-related air pollution impacts tend to mostly affect the very elderly or
those with serious respiratory problems.
VOSL $Million
Study Type of study Risk Context
(year prices)
Markandya et al. Contingent valuation Context-free reduction in mortality risk 1.2 - 2.8
2004 between ages of 70 and 80 0.7 – 0.8
0.9 – 1.9
(2002)3
Chilton et al. 2004 Contingent valuation Mortality impacts from air pollution 0.3 – 1.5
(2002)3,4
Chilton et al. 2002 Contingent valuation Roads (R), Rail (Ra) Ratios:
Ra/R=1.0036
Beattie et al.1998 Contingent valuation Roads (R) and domestic fires (F) 5.73
Carthy et al. 1999 Contingent Roads 1.4 – 2.3
valuation/standard gamble (2002)3,5
Siebert and Wie 1994 Wage risk Occupational risk 13.5
(2002)3
Elliott and Sandy Wage risk Occupational risk 1996: 1.2
1996 (2000)3
Arabsheibani and Wage risk Occupational risk 1994: 10.7
Marin 2000 (2000)3
Note: 1: median of the studies reviewed; 2: range varies with risk reduction level; lower VOSLs for larger risk reductions. 3:
Gross national income in GBP converted to USD using purchasing power parity rates per capita ratio between UK and US.
Range reflects different risk reductions. 4: based on WTP to extend life by one month assuming 40 years of remaining life. 5:
based on trimmed means. 6: this study sought respondents’ relative valuations of a risk relative to a risk of death from a road
accident. Numbers reported here are for the 2000 sample rather than the 1998 sample. Between the two sample periods
there was a major rail crash in London.
Source: Pearce, Atkinson and Mourato (2006).
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Annex VII. Project performance indicators
This annex explains how to use the main project performance indicators for CBA analysis: net present
value, internal rate of return (IRR) and the benefit-cost (B/C) ratio.
The net present value
The net present value of a project is the sum of the discounted net flows of a project. The net present
value is a very concise performance indicator of an investment project: it represents the present
amount of the net benefits (i.e. benefits less costs) flow generated by the investment expressed in one
single value with the same unit of measurement used in the accounting tables.
It is important to note that the balance of costs and benefits in the early years of a project is usually
negative and it only becomes positive after some years. As at decreases with time, negative values in
the early years are weighted more than the positive ones occurring in the later years of a project’s life.
The value of the discount rate and the choice of the time horizon are crucial for the determination of
the net present value of a project.
Net present value is a very simple and precise performance indicator. A positive net present value, net
present value>0, means that the project generates a net benefit (because the sum of the weighted
flows of costs and benefits is positive) and it is generally desirable either in financial terms or in
economic terms. When different options are considered, the ranking of the net present values of the
alternatives indicates the best one. For instance in Figure VII.1, project 1 is more desirable than project
2 because it shows a higher net present value for all the discount rates (i) applied.
There are cases in which the net present value of one alternative is not greater than the other or for
every i value. This is due to a phenomenon referred to as ‘switching’. Switching occurs when the net
present value curves of two projects intersect one another, as in Figure VII.2. With a discount rate
above x, project 1 has a higher net present value; with a discount rate below x, project 2 will perform
better. In order to select the best option, the definition of the discount rate is crucial for the selection
of the best option (and IRR cannot be used as a decision rule).
Figure VII.1 Project ranking by net present Figure VII.2 A case of switching
values
Project 1
NPV NPV
Project 1
Project 2
i x i
Project 2
The internal rate of return
The internal rate of return (IRR) is defined as the discount rate that zeroes out the net present value of
flows of costs and benefits of an investment. The IRR is an indicator of the relative efficiency of an
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investment, and should be used with caution. The relationship between net present value and IRR is
shown in the graph below.
Figure VII.3 The internal rate of return Figure VIII.4 Multiple IRRs
NPV
NPV
IRR
i i
IRR’ IRR’’ IRR’’’
If the “sign” of the net benefits changes in the different years of the project’s lifespan (for example: - + -
+ -, etc. ), there may be multiple IRRs for a single project. In these cases the IRR decision rule is
impossible to implement. Examples of this type of project are mines and nuclear power plants, where
there is usually a large cash outflow at the end of the project because of decommissioning costs.
As IRR rankings can be misleading, and given that the informational requirements for computing a
proper net present value and IRR are the same except for the discount rate, it is always worth
calculating the net present value of a project. There are many reasons in favour of the net present
value decision rule (see Ley, 2007).
The IRR contains no useful information about the overall economic value of a project. This can be
illustrated by graphing the net present value as a function of the discount rate (r). Consider Figure
VII.5, which displays the net present value schedule for two alternative projects. Project A has a
substantially higher net present value for any discount rate in the economically relevant range (i.e. for
any r less than 30 %), yet it crosses the axis to the left of project B, and consequently has a lower IRR –
i.e. IRRA = 40 % < IRRB = 70 %.
Figure VII.5 IRR and net present value of two mutually exclusive alternatives
Source: Ley (2007).
Since welfare depends on net present value, not IRR, it is apparent that project A dominates B. For
instance net present value A(r) exceeds net present value B(r) by about USD 1.6 million for a discount
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rate in the region of 10 %.
Other shortcomings of the internal rate of return are:
the sensitivity to economic life: when projects with different economic lives are to be
compared, the IRR approach inflates the deliverability of a short-life project because IRR is a
function both of the time period and of the size of capital outlay;
the sensitivity to the timing of benefits: when there are projects that fail to yield benefits for
many years, the IRR tends to be lower compared to projects with a fairly even distribution of
benefits over time, even though the net present value of the former may be higher;
the IRR indicator cannot deal with cases in which time-varying discount rates are used. In
these cases, the net present value rule allows discount rate changes to be incorporated easily
into the calculation.
One advantage of the IRR (under reasonable assumptions) is that it is a pure number and this makes it
easier to compare projects that are similar, apart from their size.
Benefit-cost (B/C) ratio
The benefit-cost ratio is the present value of project benefits divided by the present value of project
costs. If B/C >1, the project is suitable because the benefits, measured by the present value of the total
inflows, are greater than the costs, measured by the present value of the total outflows.
Like the IRR, this ratio is independent of the size of the investment, but in contrast to IRR it does not
generate ambiguous cases and for this reason it can complement the net present value in ranking
projects where budget constraints apply. In these cases, the B/C ratio can be used to assess a project’s
efficiency.
The main problems with this indicator are:
it is sensitive to the classification of the project effects as benefits rather than costs. It is
relatively common to have project effects that can be treated both as benefits and as cost
reductions and vice versa. Since the benefit-cost ratio rewards projects with low costs,
considering a positive effect as a cost-reduction rather than a benefit would only result in an
artificial improvement of the indicator;
it is not appropriate for mutually exclusive projects. Being a ratio, the indicator does not
consider the total amount of net benefits and therefore the ranking can reward more projects
that contribute less to the overall increase in public welfare.
The appropriate case for using the B/C ratio is under capital budget constraints. The following table
provides an example of project ranking given a budget constraint of 100.
Table VII.1 Benefit-cost ratio under budget constraints
PV (O) PV (I) Net present value PV(I) / PV(O)
Project A 100 200 100 2.0
Project B 50 110 60 2.2
Project C 50 120 70 2.4
Looking at net present value, the preferred project is A and the ranking is A, C, B. But looking at the
ratios between PV(I) and PV(O), C is the favourite project. Since the budget constraint is 100 and the
PV(O) of project C is 50, project B, the second in the ranking, could also be undertaken. The resulting
net present value (net present value(B)+net present value(C)) is 130, which is higher than the net
present value of project A.
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Annex VIII. Probabilistic risk analysis
Uncertainty is inherent in the CBA
Forecasting the future value of variables, an exercise needed in the ex ante project analysis, involves an
unavoidable degree of uncertainty. Uncertainty is inherent both in the factors internal to the CBA
model (as, for example, the value of time savings, the hedonic pricing in an urban area, the timing of
the completion of the investment, the value of the CO2 added or avoided, etc.) and in the factors
external to the CBA model (for example, the future prices of inputs and outputs of the project, the
actual cost of the investment, the actual number of the future users of the service held by a project
infrastructure, etc.). In the former case, the uncertainty arises from the analyst estimate of the most
appropriate values to set for the model parameters, regardless of the predictions on the running of the
project; in the latter case, the uncertainty relates to the expected values of input and output variables
that will materialise over the life of the project.
The uncertainty of the variables results in an uncertainty in the results of the cost-benefit analysis. In
other words the actual values of the performance parameters may be different, even very different,
from those calculated in the ex ante exercise: the project could show a contribution to a social welfare
minor compared to what is expected, and even a default.
Risk assessment is aimed at evaluating this uncertainty and moving towards the adoption of measures
for risk prevention and mitigation of adverse effects. As stated in Chapter 2, risk assessment, in the
broad sense, requires:
sensitivity analysis,
qualitative risk analysis,
probabilistic risk analysis underpinned on the probability distribution of critical variables372,
assessment of acceptable levels of risk,
risk prevention.
The overall risk assessment methodology is set out in section 2.10. The next sections of this annex deal
with the probabilistic risk analysis and give additional information on risk assessment and mitigation.
Probability distribution of critical variables
Once the critical variables have been identified, then, in order to determine the nature of their
uncertainty, probability distributions should be defined for each variable. A distribution describes the
likelihood of occurrence of values of a given variable within a range of possible values around the best
estimate, used as the base case.
There are two main categories of probability distribution in literature:
‘discrete probability distribution’, when only a finite number of values can occur;
‘continuous probability distribution’, when any value within the range can occur.
Discrete distributions
If a variable can assume a set of discrete values, each of them associated with a probability, then it is
defined as discrete distribution. This kind of distribution may be used when the analyst has enough
information about the variable to be studied, so as to believe that it can assume only some specific
values.
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Chapter 2 sets out the approach for choosing the most appropriate use of the quantitative (probabilistic) risk analysis.
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Figure VIII. 1 Discrete distribution
0.20
0.15
0.10
0.05
0.00
4 6 8 10 12 14 16
Continuous distribution
Gaussian (or Normal) distribution is perhaps the most important and the most frequently used
probability distribution. This distribution (see Figure VIII. 2) is completely defined by two parameters:
the mean (μ)
the standard deviation (σ).
The degree of dispersion of the possible values around the mean is measured by the standard
deviation373.
Figure VIII. 2 Gaussian distribution
1.00
0.75
0.50
0.25
0.00
0.20% 0.30% 0.40% 0.50% 0.60% 0.70%
Normal distributions occur in many different situations374. When there is reason to suspect the
presence of a large number of small effects acting additively and independently, it is reasonable to
assume that observations will be normally distributed.
Triangular or three-point distributions are often used when there is no detailed information on the
variable’s past behaviour. This simple distribution is completely described by a ‘high value’, a ‘low
value’ and the ‘best-guess value’, which, respectively, provide the maximum, the minimum and the
modal values of the probability distribution.
Triangular distribution is typically used as a subjective description of a population for which there is
only limited sample data, and especially in cases where the relationship between variables is known
but data is scarce (possibly because of the high cost of collection). The precise analytical and graphical
(t t ) 2
1
f ( x) e 2 2
with x
373 2
374
With the restriction that the normal distributions model variables with symmetrical probability with respect to the mean value.
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specification of a triangular distribution varies a great deal, depending on the weight given to the
modal value in relation to the extreme point values.
Figure VIII. 3 Symmetric and asymmetric triangular distributions
0.15
0.10
0.05
0.00
0 5 10 15 20 25
Productivity index
The diagrams in Figure VIII. 3 show two types of triangular distributions.
The first one is symmetric, with the high value as likely as the low ones and with the same
range between the modal value and the low value, and between the modal value and the high
value.
The second one is asymmetric, with the high value more likely than the low ones, and with a
larger range between the modal value and the high value than the range between the modal
value and the low value (or vice-versa).
If there is no reason to believe that within a range a given value is more likely to materialise than
others, the distribution obtained is called 'uniform', i.e. a distribution for which all intervals of the
same length on the distribution’s support are equally probable.
Reference forecasting
The question of where to look for relevant distributions arises. As set out in section 2.1.3, the
probability distribution for each variable may be derived from different sources, such as experimental
data, distributions found in the literature for similar cases and consultations with experts. One
possible approach is ‘reference forecasting’, i.e. taking an ‘outside view’ of the project by placing it in a
statistical distribution of outcomes from a class of similar projects. It requires the following three
steps:
the identification of a relevant reference class of past projects, sufficiently broad to be
statistically meaningful without becoming too generic;
the determination of a probability distribution of the outcomes for the selected reference class
of project;
a comparison of the specific project with the reference class distribution and a derivation of
the expected outcome.
According to Flyvberg (2005) ‘The comparative advantage of the outside view is most pronounced for
non-routine projects. It is in planning such new efforts that the biases toward optimism and strategic
misrepresentation are likely to be largest.’
How to obtain the probability distributions of the performance indices
Having established the probability distributions for the critical variables, it is possible to proceed with
the calculation of the probability distribution of the project’s net present value (or the IRR or the B/C
ratio). The following table shows a simple calculation procedure that uses a tree development of the
independent variables. In the sample reported in the table, given the underlying assumptions, there is
95 % probability that the net present value is positive.
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Table VIII.1 Probability calculation for net present value conditional to the distribution of critical variables in
millions EUR
Critical variables Result
Investment Other costs Benefit Net present value
Value Value Probability Value Probability Value Probability
74.0 0.15 5.0 0.03
77.7 0.30 8.7 0.06
-13.0 0.20
81.6 0.40 12.6 0.08
85.7 0.15 16.7 0.03
74.0 0.15 2.4 0.08
77.7 0.30 6.1 0.15
-56.0 -15.6 0.50
81.6 0.40 10.0 0.20
85.7 0.15 14.1 0.08
74.0 0.15 -0.7 0.05
77.7 0.30 3.0 0.09
-18.7 0.30
81.6 0.40 6.9 0.12
85.7 0.15 10.9 0.05
The more general approach to the calculation of the conditional probability of project performance is
the Monte Carlo method (already presented in section 2.10. See also references in the bibliography). In
a nutshell, the repeated extraction of a random set of values for the critical variables, taken in their
respective intervals, allow the calculation of the performance indices for the project (IRR or net
present value) that result from each set of values extracted. By repeating this procedure for a large
enough number of extractions one can obtain the probability distributions of the IRR or net present
value.
Assessment of acceptable levels of risk
Risk acceptance criteria
Often the net present values and IRRs reported in project appraisal reports refer to best or baseline
estimates, perhaps meaning 'most likely' values (or mode). However, the criterion for project
acceptability should be that of the expected value (or mean) of such indicators, calculated from the
underlying probability distributions.
For instance, if a project has an ERR of 10 % but also the probability risk analysis tells us that the ERR
has a value between 4 and 10 with a probability of 70 % and a value between 10 and 13 with a
probability of 30 %, then the expected value of ERR for that project is only 8.35 % (average (4,10)*0.7
+ average(10,13)*0.3).
Whether a more thorough risk assessment is deemed necessary, risk scores or indices, based on
processing the results of Monte Carlo simulations in a more or less sophisticated way, may be found in
the literature.
In conclusion, the procedure described in this annex allows for the selection of projects not only on the
basis of the best estimate, but also based on the risk associated with it, simply by weighting the
performance with the risk. The expected performance, and not the modal one, is the value that should
be reported in the application form for major projects requiring EU assistance, whenever a
probabilistic risk analysis is carried out. In order to evaluate the result, one very important aspect is
the compromise to be made between high-risk projects with high social benefits on the one hand, and
low-risk projects with low social benefits on the other.
Generally, a neutral attitude towards risks is recommended because the public sector might be able to
pool the risks of a large number of projects. In such cases, the expected value of the ERR could
summarise the risk assessment. In some cases, however, the evaluator or the proposer can deviate
from neutrality and prefer to risk more or less for the expected rate of return; there must, however, be
a clear justification of this choice.
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Risk averse behaviour and risk neutrality
When individuals attach greater importance to the possibility of losing a sum of money than to the
possibility of gaining the same sum, with a 50 % probability of each outcome occurring, there is ‘risk
averse behaviour’.
Risk aversion follows from the proposition that the utility derived from wealth rises as wealth rises,
but at a decreasing rate. This, in turn, comes from the theory of diminishing marginal utility of wealth.
In microeconomic theory, it is generally assumed that the utility of the marginal quantity of a good is
lower than the utility of the same quantity obtained before the marginal one.
Figure VIII.4 Relationship between utility and wealth for a risk averse society
Utility
U(W+h)
U(W)
E(U(W1))
U(W-h)
W-h W1 W W+h Wealth
In Figure VIII.4, the utilities associated with the wealth levels W+h, W and W-h are indicated on the
vertical axis. The expected utility of wealth for the society if the investment is realised is indicated on
the vertical axis as well (E(U(W1)). Since there is a 50 % chance of gaining and a 50 % chance of losing,
the value is exactly in the middle between (U(W+h) and U(W-h): E(U(W1)=0.5U(W-h) + 0.5U(W+h).
But, because of the shape of the utility function (deriving from diminishing marginal utility of wealth
assumption), the expected utility of wealth E(U(W1)) will be lower than the utility associated with the
initial level of wealth W, i.e. E(U(W1)) < U(W). Consequently, the risk averse decision-maker will
decide to reject the project. However, for the public sector, risk neutrality is to be assumed in general
for a risk pooling (and spreading) argument. Under risk neutrality, the expected value of the net
present value (the mean of probabilities) replaces the baseline or modal estimate of the net present
value as a performance indicator.
Risk prevention and/or mitigation
As mentioned in section 2.10, the measures of risk prevention and/or mitigation should be tailored to
the specific project and its level of risk. In this regard, an extensive analysis of adverse events and their
causes, as well as of their potential negative effects on the project running, could help to outline the
more effective and appropriate actions of risk prevention (see section 2.10.2).
However, the investment projects show some common and general features of their risk profiles,
which are discussed below.
The degree of risk is not always the same over the time horizon of the project realisation. It has been
\326
demonstrated by past experience and is generally accepted in literature that the riskiest phase of a
project is the start-up. At that time most of the investment costs have been incurred but there may not
yet be any feedback from an operational point of view. When the investment enters into the operations
phase, the risk involved diminishes because the feedback becomes increasingly evident.
The above justifies why the importance of correlating the proposed prevention/mitigation measures
with the project phases in which the adverse events might occur has been underlined in section 2.10.2.
Figure VIII.5 Levels of risks in different phases of a given infrastructure project
Moreover ‘there is a demonstrated, systematic tendency for project appraisers to be overly optimistic.
To reduce this tendency, appraisers should make explicit, empirically based adjustments to the
estimates of a project’s costs, benefits and duration. It is recommended that these adjustments be
based on data from past projects or similar projects elsewhere, and adjusted for the unique
characteristics of the project in hand. In the absence of a more specific evidence base, departments are
encouraged to collect data to inform future estimates of optimism, and in the meantime use the best
available data.’375
According to Flyvbjerg and Cowi (2004) cost overruns and/or benefit shortfalls, i.e. optimism bias, are
the results of a number of different factors:
multi-actor decision-making and planning;
non-standard technologies;
long planning horizons and complex interfaces;
changes in project scope and ambition;
unplanned events.
As a result, cost overruns and benefit shortfalls lead to an inefficient allocation of resources, delays and
further cost overruns and benefit shortfalls.
In addition to carrying out a full risk assessment, which represents a major step ahead in mitigating
inaccuracy and bias, other measures recommended in order to reduce optimism are:
better forecasting methods through the use of ‘reference class’ forecasting;
375
See Aymerich, M. & Turró, M. (2010), 'Risk analysis, risk management and implementation performance in transport infrastructure
projects' in Nocera, Silvio ed. Feasibility Decisions in Transportation Engineering. Strategies for Transport Evaluation, McGraw-Hill.
\327
changed incentives in order to reward better projects;
transparency and public control to improve accountability;
involvement of private risk capital.
Table VIII.2 provides some examples of mitigation measures of identified risks extrapolated from the
World Bank Project Appraisal Documents for different countries.
Table VIII.2 Risk mitigation measures
Country Project Risk Rating Risk mitigation measure
Azerbaijan Power Project implementation S Local financing requirement minimised. Project
transmission delays due to lack of local Implementation Unit to be assisted by technical
financing and poor project assistance for project management during
management implementation.
Kyrgyzstan Water Counterpart funds are not N Project design minimises the need for counterpart
management available in timely manner funds, except for taxes. The Ministry of Economy
improvement and Finance has developed a satisfactory track record
of support to ongoing International Development
Association-funded irrigation projects.
Russia Municipal heating Potential corruption may M Commercial and financial management systems for
erode project benefits the project will provide more transparency and
improve possibilities for adequate audit and control.
Turkey Railway Social resistance to change H Close cooperation between the government, General
reconstruction Directorate of State Railways Administration
(TCDD) management and the trade unions; early
definition of an appropriate social plan; expeditious
payment of the severance benefits and assistance to
staff.
Source: World Bank Project Appraisal Documents. Note: Risk rating: H (high risk), S (substantial risk), M (modest risk), N
(negligible or low risk).
\328
Annex IX. Other appraisal tools
While cost-benefit analysis is the most commonly used technique in appraising public investment and
is the one required by the Funds' regulations for major projects, other kinds of project analysis exist
and are used. In this section, the main features and fields of application of cost-effectiveness analysis
(CEA) and multi-criteria analysis (MCA) are reviewed.
Cost-effectiveness analysis
Cost-effectiveness analysis (CEA) is a comparison of alternative projects with a unique common effect,
which may differ in magnitude. It aims to select the project that, for a given output level, minimises the
net present value of costs or, alternatively, for a given cost, maximises the output level. CEA results are
useful for those projects whose benefits are very difficult, if not impossible, to evaluate, while costs can
be predicted more confidently. This methodology is often used in the economic evaluation of health-
care programmes, but it can also be used to assess some education and environmental projects. For
these examples, simple CEA ratios are used, such as the cost of education per student, the cost per unit
of emission reduction, and so on. CEA is less helpful when a money value can be given to the benefits
and not just to the costs.
Generally, CEA solves a problem of optimisation of resources that is usually presented in the following
two forms:
given a fixed budget and a number (n) of alternative projects, decision-makers aim to
maximise the outcomes achievable, measured in terms of effectiveness (E);
given a fixed level of E that must be achieved, decision-makers aim to minimise the cost (C).
While the measurement of costs is the same as in the financial analysis of CBA, the measurement of the
effectiveness depends on the type of outcome chosen. Some examples of measures of effectiveness
used in CEA are: number of life-years gained, days of disability avoided, test scores, etc. The box below
briefly reviews the methodological approach of the CEA for project selection.
COST-EFFECTIVENESS ANALYSIS
When the alternative projects are competitors and mutually exclusive, an incremental analysis is required in
order to rank the projects and single out the one that is most cost-effective.
Generally cost-effectiveness analysis is pursued to test the null hypothesis that the mean cost-effectiveness of
one project (a) is different from the mean cost-effectiveness of some competing intervention (b). It is calculated
as the ratio (R):
R = (Ca – Cb) / (Ea – Eb) = ΔC / ΔE
defining the incremental cost per unit of additional outcome.
When a strategy is both more effective and less costly than the alternative (Ca – Cb < 0 and Ea – Eb > 0), it is said
to ‘dominate’ the alternative: in this situation there is no need to calculate cost-effectiveness ratios, because the
decision on the strategy to choose is obvious.
However, in most circumstances, the project under examination is contemporaneously more (or less) costly and
more (or less) effective than the alternative(s) (Ca–Cb > 0 and Ea – Eb > 0 or, alternatively, Ca – Cb < 0 and Ea –
Eb < 0). In this situation, the incremental cost-effectiveness ratios allow appraisers to rank the projects under
examination and to identify, and then eliminate, cases of ‘extended dominance’. This can be defined as the state
when a strategy is both less effective and more costly than a linear combination of two other strategies with
which it is mutually exclusive. More operationally, extended dominance is where the incremental cost-
effectiveness ratio for a given project is higher than that of the next more effective alternative.
In practice, CEA allows appraisers to exclude those project options that are not technically efficient
(because of dominance), while for the remaining projects, the choice will depend on the size of the
budget. The treatment with the lowest incremental cost-effectiveness ratio should be the first to be
implemented and then other strategies should be added until the budget is exhausted.
\329
There are also technical problems in aggregating outcomes that appear over different years, because it
is not obvious what the specific discount factor should be (clearly neither the FDR nor the SDR apply
to discounting numbers of students, patents or emissions).
In conclusion, cost-effectiveness analysis is a practical tool for project comparison when:
the project produces only one output which is homogenous and easily measurable;
this output is a crucial supply, entailing that action to secure it is essential;
the aim of the major project is achieving the output at minimal cost;
costs can be completely assessed for each alternative, i.e. hidden costs are more or less
irrelevant;
there are no relevant externalities;
there is a wide evidence of benchmarks to verify that the chosen technology meets the
minimum required cost performance criteria.
Multi-criteria analysis
Multi-criteria analysis (MCA) is a family of algorithms used to select alternatives according to a set of
different criteria and their relative ‘weights’. In contrast to CBA, which focuses on a unique criterion
(the maximisation of social welfare), MCA is a tool for dealing with a set of different objectives that
cannot be aggregated through shadow prices and welfare weights, as in standard CBA. MCA is
appropriate for development programmes, pursuing simultaneously different policy objectives (e.g.
equity, environmental sustainability, improved quality of life, etc.), rather than for the appraisal of a
single investment project. There are many ways to design an MCA exercise. One possible approach is
as follows:
objectives should be expressed in measurable variables. They should not be redundant but
could be alternative (the achievement of a bit more of one objective could partly preclude the
achievement of the other);
once the ‘objectives vector’ has been determined, a technique should be found to aggregate
information and to make a choice; the objectives should have assigned weights reflecting the
relative importance given to them by the policy-maker;
definition of the appraisal criteria; these criteria could refer to the priorities pursued by the
different parties involved or they could refer to particular evaluation aspects;
impact analysis: this activity involves describing, for each of the chosen criteria, the effects it
produces. Results could be quantitative or qualitative;
forecast of the effects of the intervention in terms of the selected criteria; from the results
coming from the previous stage (both in qualitative and in quantitative terms), a score, or a
normalised value, is assigned (this is the equivalent of ‘money’ in CBA);
identification of the typology of subjects involved in the intervention and the determination of
respective preference functions (weights) accorded to different criteria;
scores under each criterion are then aggregated (simply with a sum or with a non-linear
formula) to give a numerical evaluation of the intervention; the result can then be compared
with the result for other similar interventions.
The project examiner should then verify if:
forecasts for non-monetary aspects have been quantified in a realistic way in the ex ante
evaluation;
there is in any case a CBA for the standard objectives (financial and economic analysis);
the additional criteria under the MCA have a reasonable political weight, so as to determine
\330
significant changes in the financial and economic results.
When the benefits are not just non-monetary, but also physically not measurable, a qualitative analysis
should still be conducted. A set of criteria relevant for the project appraisal (equity, environmental
impact, equal opportunity) is collected in a matrix, together with the impacts (measured with scores or
percentages) of the project on the relevant criteria. Another matrix should then assign weights to each
relevant criterion. By multiplying scores and weights, the total impact of the project is obtained: this
allows the selection of the best alternative.
If it is difficult to reflect the outcomes and/or costs of a project in measurable terms so that these
measures can be aggregated in a CBA, it is recommendable to switch to a MCA with its
multidimensional characteristics instead of forcing heterogeneous and diverse data into a quantitative
economic calculus.
\331
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\341
2000 2001 2002 2003 2004
SKP jooksevhindades (mld €) 6,2 7,0 7,8 8,7 9,7
SKP reaalkasv, % v.e.a. 6,2 6,1 7,5 6,5
Tarbijahinnaindeksi kasv, % v.e.a. 4,0 5,8 3,6 1,3 3,0
Hõive (tuh inimest) 585 590 589,9 602,9 601,9
Tööpuudus, % tööjõust 14,6 13,0 11,2 10,3 10,1
Euroopa Komisjoni pikaajalise prognoosi põhjal (2014 sügis)
2005 2006 2007 2008 2009 2010 2011 2012 2013
11,3 13,5 16,2 16,5 14,1 14,7 16,4 17,6 18,7
9,5 10,4 7,9 -5,3 -14,7 2,5 8,3 4,7 1,6
4,1 4,4 6,6 10,4 -0,1 3,0 5,0 3,9 2,8
615,6 651,7 657,6 656 593,9 568 603,2 614,9 621,4
8,0 5,9 4,6 5,4 13,6 16,7 12,3 10,0 8,6
2014 2015 2016 2017 2018 2019 2020 2021 2022
19,6 20,9 22,0 23,0 23,9 24,9 25,9 26,9 27,8
1,9 3,0 2,3 2,0 2,1 2,2 2,0 1,8 1,6
0,0 1,9 2,5 2,8 2,8 2,8 2,8 2,8 2,8
624,2 623,1 617,3 611,2 604,5 597,2 589,6 581,8 574,2
7,9 7,3 7,3 7,3 7,3 7,4 7,6 7,8 8,0
2023 2024 2025 2026 2027 2028 2029 2030 2031
28,8 29,9 31,0 32,1 33,3 34,5 35,7 37,0 38,3
1,6 1,7 1,7 1,6 1,6 1,6 1,5 1,5 1,5
2,7 2,7 2,7 2,6 2,6 2,6 2,6 2,6 2,5
566,7 561,6 556,9 552,5 548,7 545,3 542,2 539,2 536,6
8,2 8,1 8,1 8,0 7,9 7,9 7,8 7,8 7,7
2032 2033 2034 2035 2036 2037 2038 2039 2040
39,6 41,0 42,4 43,8 45,3 46,8 48,4 50,0 51,6
1,5 1,5 1,4 1,4 1,4 1,4 1,3 1,3 1,2
2,4 2,4 2,3 2,3 2,3 2,3 2,2 2,2 2,2
533,7 530,9 528,1 525,4 522,7 519,9 517,0 514,0 510,6
7,7 7,6 7,5 7,5 7,4 7,4 7,3 7,3 7,3
2041 2042 2043 2044 2045 2046 2047 2048 2049
53,3 55,0 56,7 58,5 60,3 62,1 64,0 65,9 67,8
1,2 1,2 1,2 1,1 1,1 1,0 1,0 1,0 0,9
2,2 2,2 2,2 2,2 2,2 2,1 2,1 2,1 2,1
507,2 503,5 499,8 495,9 491,8 487,7 483,5 479,4 475,2
7,3 7,3 7,3 7,3 7,3 7,3 7,3 7,3 7,3
2050 2051 2052 2053 2054 2055 2056 2057 2058
69,8 71,8 73,9 76,1 78,4 80,8 83,3 85,9 88,7
0,9 0,9 0,9 0,9 1,0 1,0 1,1 1,2 1,2
2,1 2,1 2,1 2,1 2,0 2,0 2,0 2,0 2,0
471,1 467,2 463,5 459,9 456,7 453,9 451,4 449,4 447,8
7,3 7,2 7,2 7,2 7,2 7,2 7,2 7,2 7,2
2059 2060
91,7 94,8
1,3 1,4
2,0 2,0
446,7 446,0
7,2 7,2
-------- Edastatud kiri --------
Teema:
Perioodi 2014-2020 CBA juhend tasuvusanal��si teostamiseks
Kuup�ev:
Mon, 16 Mar 2015 13:08:22 +0000
Saatja:
Kertu Sepp <
[email protected]>
Lugupeetud perioodi 2014-2020 toetuse saajad
Tulenevalt toetuse andmise tingimuste �21 lg 3 peab toetuse taotlus
sisaldama ka tasuvusanal��si. Euroopa Komisjon on kinnitanud uue
perioodi 2014-2020 CBA juhendi (Guide to cost-benefit analysis), mis on
aluseks tasuvusanal��si koostamisel uuel perioodil. Samuti on vahepeal
muutunud Riigi raamatupidamise �ldeeskiri, mille kohaselt kasutatakse
perioodi 2014-2020 tasuvusanal��sides diskontom��ra 4% (varasema 6%
asemel).
Palun edastage juhend ning info diskontom��ra kohta ka teistele
asjakohastele isikutele.
Parimatega
Kertu Sepp
Tehnilise J�relevalve Amet
66 72 073|
[email protected] | www.tja.ee
Attachments:
CBA_Guide_Final_Report_2014_2020(Dec2014).pdf 5.9 MB
EE pikaajaline prognoos_2014_dets.xlsx 12.8 KB
Saatja: "Keiu Leopard" <
[email protected]>
Saaja: "Aire Jõeloo" <
[email protected]>
Teema: Fwd: FW: Perioodi 2014-2020 CBA juhend tasuvusanalüüsi teostamiseks
Kuupäev: 2015-03-17 08:19
-------- Forwarded Message --------
Subject: FW: Perioodi 2014-2020 CBA juhend tasuvusanalüüsi teostamiseks
Date: Tue, 17 Mar 2015 08:45:46 +0200
From: Rando Sirak <
[email protected]>
To: 'Keiu Leopard' <
[email protected]>
Tere Keiu!
Palun registreeri antud e-mail.
Ette tänades,
Rando
*From:*Urmas Ehrlich [mailto:
[email protected]]
*Sent:* Monday, March 16, 2015 3:15 PM
*To:* Rando Sirak
*Subject:* Fwd: Perioodi 2014-2020 CBA juhend tasuvusanalüüsi teostamiseks
-------- Edastatud kiri --------
*Teema: ***
Perioodi 2014-2020 CBA juhend tasuvusanalüüsi teostamiseks
*Kuupäev: ***
Mon, 16 Mar 2015 13:08:22 +0000
*Saatja: ***
Kertu Sepp <
[email protected]> <mailto:
[email protected]>
Lugupeetud perioodi 2014-2020 toetuse saajad
Tulenevalt toetuse andmise tingimuste §21 lg 3 <https://www.riigiteataja.ee/akt/107102014016> peab toetuse taotlus sisaldama ka tasuvusanalüüsi. Euroopa Komisjon on kinnitanud uue perioodi 2014-2020 CBA juhendi (Guide to cost-benefit analysis), mis on aluseks tasuvusanalüüsi koostamisel uuel perioodil. Samuti on vahepeal muutunud Riigi raamatupidamise üldeeskiri <https://www.riigiteataja.ee/akt/121112014020>, mille kohaselt kasutatakse perioodi 2014-2020 tasuvusanalüüsides diskontomäära 4% (varasema 6% asemel).
Palun edastage juhend ning info diskontomäära kohta ka teistele asjakohastele isikutele.
Parimatega
*Kertu Sepp*
Tehnilise Järelevalve Amet
66 72 073|
[email protected] <mailto:
[email protected]>__| www.tja.ee <http://www.tja.ee/>