metadata: authors: 0: author: Marcelo,Darwin
1: author: Saha,Deblina
2: author: Raina,Aditi
3: author: House,Ruth Schuyler
count: Sri Lanka
docna: 0: docna: Prioritizing water supply infrastructure
            investments in Sri Lanka : an application of the world bank
            infrastructure prioritization framework
docty: Policy Research Working Paper
abstracts: cdata!: Governments are challenged to balance
            multiple policy goals and make difficult choices when
            selecting infrastructure projects for public investment,
            particularly since available funds are often insufficient to
            implement the full suite of proposals. This paper presents
            the application of the Infrastructure Prioritization
            Framework, a systematic, multi-criteria approach to
            infrastructure project prioritization, to inform the
            selection of water supply investments in Sri Lanka. A set of
            28 proposed water supply projects was prioritized at the
            request of the National Planning Department of Sri Lanka,
            based on consideration of multiple goals, including improved
            water quality and service, network extension, service
            provision to poor communities, job creation, and sound
            financial performance. This paper reviews the Infrastructure
            Prioritization Framework methodology; presents the results
            of the prioritization exercise, including an expanded
            sensitivity analysis; and discusses the way forward to apply
            the Infrastructure Prioritization Framework to inform
            infrastructure investment decisions.
geo_reg_key: 517198,517191,517212
repnme: repnme: Prioritizing water supply infrastructure
            investments in Sri Lanka : an application of the world bank
            infrastructure prioritization framework
display_title: Prioritizing water supply
            infrastructure investments in Sri Lanka : an application of
            the world bank infrastructure prioritization framework
listing_relative_url: /research/2018/02/29565319/prioritizing-water-supply-infrastructure-investments-sri-lanka-application-world-bank-infrastructure-prioritization-framework
topicv3: Water m1326522 137,Poverty m1326687 695,Water Supply m1326961 138,Environment, Natural Resources and Blue
            Economy m1327391 566,Jobs m1503931 2670
publishtoextweb_dt: 2018-02-06T00:00:00Z
no_of_pages: 48
author_keys: 0: author_key: 1411823
1: author_key: 1555573
2: author_key: 1365991
model_extractions: WPS8331 Policy Research Working Paper 8331 Prioritizing Water Supply Infrastructure Investments in Sri Lanka An Application of the World Bank Infrastructure Prioritization Framework _Darwin Marcelo Deblina Saha Aditi Raina Schuyler House_ Infrastructure, PPPs and Guarantees Global Theme February 2018
Policy Research Working Paper 8331

# **Abstract**

Governments are challenged to balance multiple policy goals and make difficult choices when selecting infrastructure projects for public investment, particularly since available funds are often insufficient to implement the full suite of proposals. This paper presents the application of the Infrastructure Prioritization Framework, a systematic, multi-criteria approach to infrastructure project prioritization, to inform the selection of water supply investments in Sri Lanka. A set of 28 proposed water supply projects was prioritized at the request of the National Planning Department of Sri Lanka, based on consideration of multiple goals, including improved water quality and service, network extension, service provision to poor communities, job creation, and sound financial performance. This paper reviews the Infrastructure Prioritization Framework methodology; presents the results of the prioritization exercise, including an expanded sensitivity analysis; and discusses the way forward to apply the Infrastructure Prioritization Framework to inform infrastructure investment decisions.

This paper is a product of the Infrastructure, PPPs and Guarantees Global Theme. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at dmarcelo@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Prioritizing Water Supply Infrastructure Investments in Sri Lanka: An Application of the World Bank Infrastructure Prioritization Framework Darwin Marcelo, Deblina Saha, Aditi Raina, and Schuyler House Keywords : Infrastructure prioritization, composite indices, water, water supply, infrastructure planning, public investment, principal component analysis, multi‐criteria analysis JEL Classification Codes : O18, O21, O22, H54, C38.
# Table of Contents

|List of Abbreviations ........................................................................................................... 3|
|---|
|Acknowledgements ............................................................................................................ 4|
|1.<br>Introduction ........................................................................................................................ 5|
|2.<br>Infrastructure Prioritization Framework (IPF) ..................................................................... 6|
|2.1 The IPF Methodology ................................................................................................. 6|
|2.2 Rationale and Principles for an Approach to Infrastructure Prioritization ................ 7|
|3.<br>The Infrastructure Planning Process in Sri Lanka ................................................................ 8|
|4.<br>Project Prioritization Applied to Water Supply Investments in Sri Lanka ......................... 11|
|4.1.1. Step 1: Criteria Selection ....................................................................................... 13|
|4.1.2. Step 2: Data Consolidation and Preparation ........................................................ 14|
|4.1.3. Step 3: Calculation of the Indicators ..................................................................... 15|
|4.1.3.a. Input Criteria for Social and Environmental Index (SEI) ................................... 15|
|4.1.3.b. Input Criteria for Financial and Economic Index .............................................. 17|
|4.1.3.c. Combining Criteria into Composite Indicators .................................................. 19|
|4.1.4. Step 4: Plotting SEI and FEI Results ....................................................................... 23|
|4.1.5. Sensitivity Analysis ................................................................................................ 28|
|4.1.6. Step 5: Project Selection ....................................................................................... 30|
|5. Way Forward ..................................................................................................................... 30|
|References ....................................................................................................................... 33|
|Annexure‐I: NPD Criteria for funding water infrastructure ............................................ 34|
|Annexure‐II: Calculation of jobs created during construction ........................................ 35|
|Annexure‐III: Data Table for SEI Indicators ..................................................................... 38|
|Annexure‐IV: Data Table for FEI Indicators ..................................................................... 40|
|Annexure‐V: Weights under varying constraints to the SEI and FEI ............................... 42|
|Annexure‐VI: Final SEI and FEI Composite Scores for all projects .................................. 43|
|Annexure‐VII: SEI Project ranking using simple average‐based weights ........................ 44|
|Annexure‐VIII: SEI Project ranking using subjective‐based weights ............................... 45|
|Annexure‐IX: FEI Project ranking using subjective‐based weights ................................. 46|

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# List of Abbreviations

CBA Cost‐Benefit analysis DSD Divisional Secretariats FEI Financial‐Economic Index GND Grama Niladhari Division GoSL Government of Sri Lanka IPF Infrastructure Prioritization Framework NPD National Planning Department NWSDB National Water Supply and Drainage Board SEI Social‐Environmental Index 3
# Acknowledgements

This paper was prepared by a team of experts from the World Bank Group with inputs from the National Planning Department (NPD) of Government of Sri Lanka on the selection of projects, indicators as well as an alternative weighting scenario for the prioritization exercise. The World Bank team included Darwin Marcelo (Task Team Leader), Deblina Saha, Aditi Raina and Schuyler House, other members of the World Bank Infrastructure, PPPs & Guarantees Group and the Sri Lanka Country Management Unit. Cledan Mandri‐Perrott (Head, Infrastructure Finance and PPP) provided essential guidance and oversight. The team from NPD comprised of Mr. Ahamadh Mubarak and Ms. Kumuduni Perera. A special mention of the support provided by Mr. Sajjan Jayasiriwardene, ex‐Additional General Manager of National Water Supply and Drainage Board, who helped us gather all relevant information for the exercise.

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# 1. Introduction

Governments face the dilemma of allocating limited resources to infrastructure projects while maximizing socioeconomic results and achieving development goals. The Government of Sri Lanka (GoSL) faces a similar challenge, including a reduction in government spending coupled with a widening gap in infrastructure service demand and provision. In this context, it becomes critical for the GoSL to have a system to prioritize investments that can incorporate national goals while optimizing the allocation of public funds.

In Sri Lanka, government investment on infrastructure as a percentage of GDP was 4.9% in 2015 (USD 3.98 billion against GDP of USD 80.6 billion).<sup>1</sup> An estimated USD 823 million of these investments were dedicated to the water sector.<sup>2</sup> As a point of comparison, Thailand spent 8% of its GDP on infrastructure in the same year, while Indonesia and Vietnam spent 9% and 13%, respectively. Estimations suggest that Sri Lanka will need to increase infrastructure investment to around 7% of GDP annually to achieve a level of basic services similar to that of more developed economies or spend around 4% of GDP annually to achieve more modest standards in terms of access and quality of services.<sup>3</sup> Given the current fiscal deficit in Sri Lanka, however, it is unlikely that the government will be able to increase investments to these levels. In 2015, the fiscal deficit reduced to 7.6% of Sri Lanka's GDP, which is still significantly higher than the target of 4.4% of GDP. In the same year, the external current account balance was at a deficit of 2.3%, and public debt rose to over 70% of GDP.<sup>4</sup> As the GoSL committed to reduce the fiscal deficit to 3.5% of GDP by 2020, public budgets will most likely continue to be insufficient to meet all of Sri Lanka's infrastructure needs, further reinforcing the need for a methodical approach to prioritizing the allocation of scarce public resources to infrastructure development.

The World Bank's Infrastructure Prioritization Framework (IPF) offers a systematic approach to infrastructure prioritization that places social‐environmental and financial‐economic factors at the forefront of decision‐making. The IPF is transparent and objective, following a clear step‐wise approach, while leaving space for deliberation to remain responsive to policy priorities. The IPF was piloted in Vietnam, Panama, and Argentina and is currently being applied in Argentina and Chile.

This paper presents the application of the IPF to water supply infrastructure investments in Sri Lanka. To this end, a set of new water supply projects was prioritized at the request of The National Planning Department of Sri Lanka (NPD). The paper first introduces the IPF

> 1 Source: Central Bank of Sri Lanka, Annual Report 2016 – Chapter 3 Economic and Social Infrastructure.

> 2 Source: Ministry of Finance, Annual Report – 2016.

> 3 Source: Nabi, I., & Biller, D. (2013). Investing in Infrastructure: Harnessing its Potential for Growth in Sri Lanka (No. 78300) (pp. 1–125). The World Bank.

> 4 Source: Central Bank of Sri Lanka, Annual Report 2016 – Chapter 10 Fiscal Policy and Government Finance.

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methodology then follows with background information on the infrastructure planning process in Sri Lanka. Then, the paper introduces the methodology adopted to prioritize water supply infrastructure projects. The last two sections present the results of the pilot, including a sensitivity analysis, as well as a discussion on the way forward to apply the IPF to different sectors.

# 2. Infrastructure Prioritization Framework (IPF)

## 2.1 The IPF Methodology

The IPF is a quantitative multi‐criteria approach to compare proposed infrastructure investments within a sector according to government‐selected social, environmental, financial, and economic criteria. Statistical methods are used to combine this information into a social‐environmental index (SEI) and a financial‐economic index (FEI). These two composite indicators are then displayed alongside the sector budget constraint, allowing a classification of projects for further selection and implementation.

The approach recognizes that objective evaluation and selection of investments cannot be dissociated entirely from policy discourse, professional experience, or the politics of project selection. In addition to economic benefits, projects may be chiefly valued by governments and other stakeholders due to key policy goals which are non‐economic in nature, or due to considerations that objective indicators cannot measure, such as protecting priority habitats, promoting social inclusion and cohesion, or honoring culture. As such, the IPF accommodates policy and political responsiveness in two ways: through the selection of criteria (project‐ level indicators) for assessment, and by leaving a degree of freedom in decision‐making through provision of two references for judgment (the indices). The IPF approach structures the prioritization process in a manner that accounts for multiple development objectives but remains practical to implement.

The IPF is quantitative in essence but does not require the reduction of all project‐level information into a common monetized unit of measure. The main characteristics of this framework include:

- a. It synthesizes multiple social, environmental, financial and economic criteria into two composite indicators –a social‐environmental index (SEI) and a financial‐economic index (FEI);

- b. It allows the inclusion of key relevant policy goals;

- c. It is adaptable to contexts with limited information and technical capacity;

- d. It considers the sector budget constraints in the classification of projects;

- e. It presents information in a visual interface that is simple and easy to interpret;

- f. It offers options for budget allocation redistribution between sectors; and

- g. It improves the availability and quality of information at the project‐level.

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2.2 Rationale and Principles for an Approach to Infrastructure Prioritization The IPF framework is differentiated in four ways from other approaches to infrastructure decision‐making. First, it incorporates national policy goals, social and environmental sustainability criteria, and long‐term development aims alongside financial and economic considerations. Second, it is predicated on parsimony and pragmatism. Third, it makes space for policy debate via criteria identification and the selection of projects from mid‐priority categories. Fourth, it provides decision‐makers with an intuitive, graphical interface upon which to compare alternative investment scenarios.

The IPF was created in response to observed government demand, including needs for (a) improving infrastructure planning at the national and sector levels; (b) considering large projects sets with scarce planning resources; (c) meaningfully addressing environmental and social primacies; and (d) balancing analytical efficiency, derived from standardization, with policy and political responsiveness. Adopting a systematic approach to prioritization is further justified by public demand for evidence, value, and legitimacy in infrastructure decision‐making. These logics are detailed in Marcelo, et al, 2016. To be deemed legitimate and comprehensive, prioritization must be based on sound evidence that affords meaningful comparison. In line with these considerations, the IPF is designed to employ quantitative measures to the greatest extent possible to limit subjectivity.

Furthermore, comprehensiveness requires that project comparisons make space for multiple policy goals and facets of project selection. This lends support to employing multi‐criteria approaches, with criteria selected to reflect considerations of effectiveness and value, as well as sector and national policy goals. The IPF captures the strengths of multi‐criteria decision approaches, but also allows use of inputs from cost‐benefit analysis (CBA).<sup>5</sup> Finally, the process to prioritize investments must be administratively and politically feasible. This suggests that governments adopt the principle of parsimony –using the least amount of relevant information needed to inform a decision. Administrative feasibility means that it can be implemented within limits of institutional capacity, cost, time, and data availability. Political feasibility, on the other hand, accepts that prioritization cannot be so devoid of deliberation that it is rendered completely inflexible or unresponsive to political factors. In summary, most infrastructure policy‐making contexts demand a reconciliation of highly technical and objective policy analysis, on the one hand, and more political and practice‐ based inputs, on the other, all within the resource means of governments.

> 5 We recognize multiple approaches to investment decision‐making, including social cost‐benefit analysis (SCBA). For an extensive discussion of alternative approaches, see Marcelo, et al, 2016. Whereas SCBA requires fully monetized information on costs and benefits, IPF makes use of available inputs (e.g., financial CBA). IPF's value‐adds to CBA are in (a) directly treating non‐marketed impacts in 'natural' units; (b) relieving the burden of making and justifying assumptions required to monetize benefits and costs; and (c) dealing directly with issues like equity and social justice.

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<!-- Start of picture text --> Project Initiation<br>Ministry Approval<br>|<br>NPD Evaluation<br>Large Project Small Project<br><!-- End of picture text -->

<!-- Start of picture text --> ¥<br>_ j RecommendationIn-Principal NPD RecommendationFinal NPD<br>Final NPD<br>Recommendation<br> _— Cabinet Approval —<$_<—¥$\_—_+<br>Inclusion in Inclusion in<br><!-- End of picture text --> <!-- Start of picture text --> Plan* Budget<br>External National<br>Resource Budget<br>Department Department<br><!-- End of picture text -->
The infrastructure planning process is described in further detail as follows:

- 1) Project Initiation: Projects can be proposed by Ministries, Departments, Public Corporations or Government Owned Companies and are submitted along with pre‐ feasibility studies to the Chief Accounting Officer (CAO) of the relevant Ministry.

- 2) Ministry Approval: If the proposal is acceptable to the relevant Ministry, the relevant Chief Accounting Officer shall submit the proposal to the National Planning Department (NPD). Ministry CAO approval is necessary for the project to go ahead, even if it is initiated within the Ministry.

- 3) NPD Evaluation: Proposals are submitted to the NPD for a preliminary evaluation of the feasibility of the project. Based on the estimated construction costs and maintenance costs of the projects, they can be classified as

- i. Large projects: Projects with an estimated initial cost over LKR. 20 million<sup>6</sup> (USD 0.13 million) and recurrent annual operation/maintenance costs more than LKR. 1 million (USD 6,530) are categorized as large projects and follow a two‐stage approval process:

- a) _Preliminary Approval:_ If the project is in line with the National Development Framework _(a rolling five‐year development planning arrangement)_ and development priorities, the NPD grants preliminary approval for the project concept paper and suggests the relevant line ministry to do the detailed feasibility study. The NPD may recommend to the relevant line ministry to obtain the approval of the Cabinet of Ministers for the project concept before a detailed feasibility study is carried out, if the NPD considers it is appropriate.

- b) _Final Approval:_ In cases where preliminary approval is required and granted by the Cabinet of Ministers, the Pre‐Feasibility Report for the project is passed on to the line Ministry and, if necessary, to the Department of External Resources. The line Ministry, along with Proposing Agency, carries out a detailed feasibility study and formulates the final project proposal, both of which are submitted to the NPD for final appraisal. NPD performs a final appraisal and sends its recommendation to the line Ministry and, if necessary, to the Department of External Resources/Department of National Budget.

- ii. Small projects: Projects with an estimated initial cost less than LKR. 20 million (USD 0.13 million) and recurrent annual operation/maintenance cost less than LKR. 1 million (USD 6,530) are categorized as small projects and follow a single‐stage approval process by NPD before Cabinet approval.

> 6 This is the current cutoff limit followed as per the Treasury Circular No. 138 dated 04.04.2008. However, this is proposed to be increased to LKR 100 million as per the draft Govt. Financial Code 2016.

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- 4) Cabinet Approval: The Line Ministry considers the Project Proposal along with the Final Appraisal Report of the Department of National Planning and submits these to the Cabinet of Ministers for final approval.

- 5) Inclusion in Sector Master Plan: A sector master plan is a comprehensive multi‐year plan that is developed within the National Development Framework for each sector. Each line ministry develops the Sector Master Plan. Large projects are included in the proposed sector master plan after receiving In‐Principal NPD recommendation. Then, the proposed sector master plan receives Cabinet approval. Small projects, once approved by the Cabinet of Ministers, should be included in the relevant sector master plan.

- 6) Inclusion in Medium‐Term Budget/ Expenditure Framework: A Medium‐Term Budget/ Expenditure Framework is a rolling three‐year budget/expenditure planning and management framework. Projects approved by the Cabinet of Ministers are included in the Medium‐Term Budget/ Expenditure Framework.

- 7) Funding Proposal : Preliminary approval to explore avenues of funding is also sought from the Cabinet of Ministers after having appraised the proposed funding arrangements:

- a) In the event financing is envisaged in terms of the Foreign Loans Act, it should be referred to the External Resources Department.

- b) In the event financing is envisaged through annual Budgeting, it should be referred to the National Budget Department.

# 3.2 Improving the Infrastructure Planning Process in Sri Lanka

A critical point in the infrastructure planning process is the transition from the preparation, deliberation, and endorsement phases, to the allocation of funds for project implementation. Here, the need for evidence, value, and legitimacy in infrastructure decision‐making is essential to the efficacy, efficiency and transparency of the entire process. The IPF can play a key role in this transition by systematizing the prioritization of investments according to a set of criteria chosen by consensus among the relevant stakeholders, with consideration of the budget constraint.

The IPF may be introduced into the infrastructure planning process immediately before preliminary approval to explore avenues of funding is sought from the Cabinet of Ministers. It is at this stage that proposed projects included in sector master plans must compete for the pool of limited funding in order to move to implementation. Since the IPF allows decision‐ makers to identify a limited set of priority projects that may be implemented within the budget constraints (which disallows implementation of all projects), it is important that such priority projects be identified before the financing scheme for all projects is determined so that the available financing or budget can be optimally utilized. While projects approved by the Cabinet can make it to the Sector Master Plan or medium‐term plan, the implementation of these projects in a budget cycle will be determined by the IPF so that projects with larger social, environmental, financial and economic benefits are implemented ahead of others 10
<!-- Start of picture text --> Project Initiation<br>Ministry Approval<br>NPD Evaluation<br>Large Project Small Project<br>¥<br>In-Principal NPD Final NPD<br>Recommendation Recommendation<br>Final NPD<br>Recommendation<br><!-- End of picture text --> <!-- Start of picture text -->
-—____—— Cabinet Approval :<br>Inclusion in Inclusion in<br>— Sector Master Application of IPF Medium;  Term<br>Plan* Too! , Budget<br>Funding Proposal<br>External National<br>Resource Budget<br>Department Department<br><!-- End of picture text -->
facilities. Some projects involve integration with other systems, depending on whether they include expansion into new service areas (specific details can be found in Table 8). In the list of proposed projects, two are distinctly different from the others: the Water Treatment Plant at Kethhena and the expansion of the water pipeline along the Orugodawatta‐Ambatale Road. At the request of the NPD, the former was retained in the analysis, but it was excluded from calculations used to determine the weighting process (discussed in detail later) in order to avoid bias. The latter was removed from the final analysis altogether, since financial and economic analysis for that particular project was not readily comparable to those of the other projects.

Overall, the exercise sought to facilitate prioritization in a manner that i) accounts for broader economic, social, and environmental considerations and ii) remains feasible with respect to time, cost, analytical capacity, and data availability.

# 4.1. The IPF Implementation Process

Implementing the IPF is relatively straightforward, following five steps (see Figure 3):

1. Selecting decision criteria;

2. Gathering project‐level criteria data; 3. Calculating social‐environmental and financial‐economic composite indicators; 4. Plotting projects and budget limits; and 5. Selecting projects.

To implement these steps, it is necessary to make three key decisions:

1. Define criteria to be included in the Socio‐Environmental and Financial‐Economic indices;

2. Define a criteria‐weighting methodology to combine variables and calculate scores; and 3. Establish a decision rule for medium priority projects.

In the subsequent sub‐section, the application of the IPF is described in terms of the steps presented in the figure below, with direct reference to the Sri Lankan Water Supply pilot. An extensive technical description of the IPF methodology is also detailed in Marcelo et al, 2015.

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<!-- Start of picture text --> Consensus between decision makers, experts, and<br>| Source project data data (CBA elements elements<br>L tbe. ___) key stakeholders ) —<br>EPA SS SS | incorporated when available)<br>L | Ill Calculate | Includes statistical statistical /mathematicalmathematical methods to<br><!-- End of picture text -->

Consensus between decision makers, experts, and | Source project data data (CBA elements elements L<sup>tbe.</sup> ___) key stakeholders ) — EPA SS SS | incorporated when available) L | Ill Calculate | Includes statistical statistical<sup>/mathematicalmathematicalmethodsto</sup> ‘Composite Indicators; combine criteria into two composite indicators L, Combine SEI, SEI, FEI, and budget constraint and budget constraint constraint to visualize relative project performance performance LEaEa Based on informed deliberation on informed deliberation informed deliberation deliberation

<!-- Start of picture text --> L, Combine SEI, SEI, FEI, and budget constraint and budget constraint constraint<br>to visualize relative project performance performance<br>LEaEa Based on informed deliberation on informed deliberation informed deliberation deliberation<br><!-- End of picture text -->
_Table 1. Preliminary_ _<u>proposed selection criteria</u>_

||SEI|FEI|
|---|---|---|
|‒|Beneficiaries/Users per $ invested|‒<br>Benefit‐cost ratio|
|‒|Jobs created (direct and indirect)|‒<br>Existing water resource yield|
|‒|Poverty level (in area of intervention)||
|‒|Quality of existing water||
|‒|Water‐borne diseases||
|‒|Alternative water resources||

The IPF requires a minimum level of relevant information at the project level to compare infrastructure projects. Therefore, the aim is not to produce a long list of criteria, but to carefully select those that would be most effective in capturing the key differentiating factors among the projects. The selection of variables may differ based on government policy goals (e.g., sectorial, social, and environmental aims) and stakeholder consultations, but generally includes indicators of value, efficiency, and social and environmental impact.

It is also essential that the selected criteria make it possible to discern between projects with some degree of precision and exhibit sufficient variability (for each decision criterion) to allow distinction between projects or groups of projects. In other words, a criterion with little to no variability across projects is not useful to any prioritization strategy.

4.1.2. Step 2: Data Consolidation and Preparation The next step is to define the set of projects and consolidate the information at the project level. An initial list of 27 projects corresponding to project proposals that NPD received from the National Water Supply and Drainage Board (NWSDB) and several from the Megapolis Master Plan was considered.<sup>7</sup> From this list, two projects pertaining to the construction of new water reservoirs were removed from consideration, as the nature of these projects was quite different to other water supply projects. Two other projects were discarded, as they were in very early stages of preparation and hence did not have sufficient information. In addition, one project was also excluded since it went under procurement at the time of this analysis. Lastly, six new projects from the Public Investment Program (2016‐2020) were added to the final list of projects, taking the total project count to 28.

The subsequent step is to gather the data to calculate the indicators that would comprise the SEI and FEI scores for each project. Project data were entered into a simple Excel

> 7 The Western Region Megapolis project (or Megapolis Master Plan) has a list of 171 projects with a total investment of approximately US$40 billion. The projects under this list incorporate Transport, Energy, Water, Housing, Townships, Environment and waste management, Port, Airport, Logistics and tourism related projects confined mostly to the western region. The transport component of the Megapolis plan has been developed by using the Urban Transport Master Plan for the Colombo Metropolitan region together with the land use plan based on the developments envisaged under the Megapolis. Similarly, the Water projects identified under the Megapolis plan is a collection of investments identified by the NWSDB, enhanced by the requirements of the land use planning such as the "aero city", "industrial city", "techno city", etc.

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environment that recorded, for each project under study, raw project data associated with each criterion. Additional calculations were made in cases where data were not readily available at the project level.

# 4.1.3. Step 3: Calculation of the Indicators

The approach to calculate the composite SEI and FEI is two‐fold and includes (a) identifying the criteria to be included in each composite indicator, along with their units of measurement, and (b) specifying a method to estimate or assign weights to the criteria involved in calculation of the SEI and FEI. In this section, the criteria selected as inputs to the SEI and FEI are described, along with the selected weighting methods.

The preliminary list of criteria presented in Table 2 was further revised by two experts in the water sector: a local consultant (former Additional General Manager of National Water Supply and Drainage Board) and an international water expert. The preliminary criteria were also contrasted against current data availability. A final list of criteria that resulted from this process is shown in Table 2 below.

_Table 2. Final criteria selected_

||SEI (8)||FEI (2)|
|---|---|---|---|
|‒|New beneficiaries/users per $ invested|‒|Benefit‐cost ratio|
|‒|Jobs created (direct) per $ invested|‒|Existing water resource yield|
|‒|Poverty level (in area of intervention)|‒|Non‐revenue water (%)|
|‒|Bacterial quality of existing water|||
|‒|Water‐borne diseases|||
|‒|Continuity of supply|||
|‒|Existing safe water coverage|||

# 4.1.3.a.  Input Criteria for Social and Environmental Index (SEI)

This section describes the seven input criteria for the SEI: SEI 1. Beneficiaries: For each project, the criterion 'beneficiaries' measures the number of new direct project beneficiaries per million dollars invested. All 28 projects to which the IPF framework is applied are being developed in areas that usually have some existing National Water Supply and Drainage Board (NWSDB) scheme serving a portion of the population in those areas. The new projects would connect these existing beneficiaries as well as some previously untapped portions of the population, who are the new beneficiaries. Projects with a greater number of new beneficiaries are expected to have higher SEI scores. This criterion considers only new beneficiaries, as it aims to determine the additional social benefits that are generated by the implementation of the project. However, the benefits to existing beneficiaries are accounted for in the benefit‐cost analysis under the FEI. The information was obtained from the project's pre‐feasibility studies shared by NWSDB.

15
SEI 2. Jobs Created: This criterion accounts for the number of direct jobs created by the project during the construction and operational phases. The number of jobs created during the operational phase was available in the pre‐feasibility studies of the projects. The number of jobs created during the construction phase was calculated based on the cost estimate for pipe laying works and civil/structural work and the unit cost of labor. First, the cost of labor was assumed as 20% of the pipe laying cost and as 40% of the civil/structural work cost. Then, the typical size of labor crews used in pipe supply and laying and civil/structural work was identified based on available data in NWSDB, and the rates charged per crew were estimated based on the daily wage rates for skilled and unskilled labor using the NWSDB Rate Book for the respective year. The detailed calculations are provided in Annexure‐II.

SEI 3. Poverty Level: This criterion refers to the poverty level in the area where the project is to be located. It is calculated as the percentage of people living below the poverty line measured thorough the poverty head count index data available at a District Secretarial Divisions (DSD) published by the Department of Census and Statistics.<sup>8</sup> If a Project covers more than one DSD, then the poverty level input criteria for that particular project is calculated as a weighted average of the poverty levels in each of the DSDs based on their existing populations.

SEI 4. Bacterial Quality of Water: This criterion attempts to factor in the quality of water using a consistent parameter across all projects. Because almost all projects in the analysis include water treatment, these projects aim to improve the quality levels of supplied water. Bacterial quality is measured by the number of failed water quality tests during the last 36 months in the areas where the projects will be implemented.<sup>9</sup> In order to prioritize projects in areas where quality is in most need of improvement, projects where test failure levels are higher are prioritized for improvement works. Such data was collected from either the pre‐ Feasibility Reports or Bacteriological WQ Test results for the relevant years from NWSDB.

SEI 5. Prevalence of Water Borne Diseases: This criterion measures the average annual number of diarrhea/ dysentery, hepatitis, and typhoid cases in the last five years per 100,000 of the population to be served by the projects. This data was aggregated from various sources, including pre‐feasibility reports, health offices (RDHS, MOH, PHI, Regional Epidemiologist etc.), and the Department of Health. Again, since a key aim of all projects included in the analysis is to provide safe piped water supply, areas with higher prevalence of waterborne disease receive higher priority for intervention works.

SEI 6. Continuity of Supply: This criterion is based on the hours of water supply per day in the areas where the project will be located. The lower the hours of supply, the higher the priority for implementing projects serving those areas. These data are obtained from either the pre‐

> 8 The districts of Sri Lanka are divided into administrative sub‐units known as _divisional secretariats_ . The Divisions are administered by a 'Divisional Secretary' and are known as 'D.S. Divisions'. There are 331 of them.

> 9 The data are collected as part of the standardized process specified by the Sri Lanka Standards Institution (SLSI). SLSI stipulates the number of tests to be conducted every month based on the number of consumers.

16
Feasibility Studies or Assessment of Pipe Borne Water Supply Facilities in DSDs published on the NWSDB website, as at end of December 2015.<sup>10</sup> As the data are available only for brackets of service, a score was assigned to each bracket in the following manner: _Table 3. Hours of supply_ _<u>per day</u>_

|SupplyHours|Score(A)|
|---|---|
|18 ≤ x ≤ 24|1|
|12 ≤ x < 18|2|
|6 ≤ x < 12|3|
|1 ≤ x < 6|4|

If a project covers more than one DSD, then the score for the hours of supply is assigned to each DSD based on their respective hours of supply, and the final score is computed as a weighted average of the individual scores each DSD received and their existing population.

SEI 7. Existing Safe Water Coverage: This criterion measures the percentage of population with access to safe water sources. Projects are given higher priority if they are located in areas where fewer consumers (as a percentage of the population) have access to safe water. Data for this criterion were obtained from pre‐feasibility studies (PFS), 2012 census data, and data from DSD offices (Resource Profile) and Grama Niladhari Divisions (GND).<sup>11</sup> In cases where data could not be directly extracted from PFS Reports, census information and data from DSD and GND were used to calculate the number of households with access to unsafe water sources (i.e., unprotected wells, rivers, tanks, streams etc.).<sup>12</sup> Information for an additional environmental indicator was also considered to measure the sustainability of proposed water extraction (in terms of the maintenance of the ecosystem function). The proposed indicator was the quantity of extraction as a percentage of the surface water flow; however, due to limited information on the total water demand from the source (not just of the particular project) as well as detailed flow / runoff data (to account for floods and low water flows), it was not possible to get accurate estimates for the projects in this analysis. Using the variable without knowing the total water extraction would provide misleading information, as it would not be possible to know to how the additional withdrawal would impact the ecosystem.

4.1.3.b. Input Criteria for Financial and Economic Index This section describes the two input criteria for the FEI, namely the benefit‐cost ratio and the water resource yield.

> 10 <u>http://www.waterboard.lk/web/index.php?option=com_content&view=article&id=78&Itemid=425&lang=en</u>

> 11 Sub‐unit of District Secretarial Divisions (DSDs).

> 12 http://www.statistics.gov.lk/PopHouSat/CPH2011/index.php?fileName=H4&gp=Activities&tpl=3

17
FEI 1. Benefit‐Cost Ratio: For each water project, the benefit‐cost ratio (BCR) corresponds to the net present value of all financial and economic benefits divided by the net present value of all costs (annualized operating expenses and capital expenditures). This calculation includes the economic benefits accruing out of time savings for collection of water, monetary savings for reduction in purchase of drinking/cooking water from private suppliers, and health benefits attributable to reduced instances of waterborne diseases and chronic kidney disorder cases. It is assumed that 10 minutes per‐day, per‐family would be saved in water collection in cases where data were not readily available. Similarly, it is assumed that Rs. 20 (US$ 0.13) per family per day would be saved by not purchasing water from private vendors and that chronic kidney disorder cases could be reduced by 20% with access to higher‐quality water delivered by the new projects. The higher the benefit‐cost ratio, the more benefits accrue to the population. As such, higher BCRs contribute to higher composite FEI scores.

FEI 2. Existing Water Resource Yield: This criterion is used to check the level of implementation hazards for the projects by verifying the extent to which the new projects will be able to extract water from existing water resources. This is done by considering whether the project has Approved Water Rights, MOUs with other users, and water availability throughout the year. The higher the existing water resource yield, the higher is the contribution of this input criterion to the final composite FEI score.

The scoring matrix is detailed below: _Table 4: Scale for measuring existing water resources yield_

|Approved Water Ri|ghts|Water Availability Thr<br>the Year|oughout|MOU with Other<br>Users|Water|
|---|---|---|---|---|---|
|_Documents Availability_|_Score_<br>_(A)_|_Confirmation on_<br>_Availability of Water_|_Score_<br>_(B)_|_Documents_<br>_Availability_|_Score_<br>_(C)_|
|Available (or if not<br>relevant)|1|100 % Confirmed|1|Available (or if not<br>relevant)|1|
|Not Available|0|Not<br>confirmed<br>in<br>drought season etc.|0|Not Available|0|
|ExistingWater Resource Y|ield Score|=|Score A|+ Score B +Score C||

FEI 3. Non‐Revenue Water : This criterion measures the percentage of non‐revenue water (NRW) that exists in the existing water supply schemes serving the areas or DSDs where the new projects will be located. NRW is a good measure of the economic efficiency of the current water supply systems. The higher the existing NRW, the greater the need for projects that improve infrastructure and management practices. NRW values are weighted by the number of existing beneficiaries in the service area, since larger distribution networks that cover larger populations are also likely to see larger losses. Data on the NRW values were sourced from NWSDB (2015).

Table 5 below provides basic descriptive statistics on the indicators used in the IPF analysis to show the variation that exists between the projects with respect to the various indicators.

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_Table 5: Descriptive statistics_

|VARIABLE|N|MEAN|STD.DEV.|MIN|MAX|
|---|---|---|---|---|---|
|Total Expected Cost (USD million)|28|96.07|84|9|481|
|Total number of new beneficiaries|27|113,677|89,201|0|286,692|
|Total number of jobs created|27|1,687|1,424|193|7,109|
|Poverty Level|27|8|4|3|22|
|Hours of water supply||||||
|(1=18 ≤ x ≤ 24; 4= 1 ≤ x < 6)|27|2|1|1|4|
|Quality of Water|23<sup>a</sup>|5|8|0|25|
|Existing safe water coverage|28|83|14|39|97|
|Prevalence of water borne diseases (#)|27|209|140|32|568|
|Non-revenue water level|27|22|7|11|37|
|Net present value of benefits|27|103|95|4|319|
|Net present value of costs|27|84|75|7|322|

Notes: The data of projects not included in the IPF analysis are excluded. a Four projects have missing data

# 4.1.3.c.  Combining Criteria into Composite Indicators

IPF aggregates the SEI and FEI indicators into two composite scores for easier interpretation and comparison. This helps to reduce the data from a complex, multidimensional frame into fewer dimensions. Aggregating indicators into combined indices requires assigning weights to each criterion, then summing the weighted indicator values to yield a combined total. The IPF uses a variation of the Principal Component Analysis (PCA) originally developed by K. Pearson (1901) to determine the weights associated with each criterion to obtain composite indicators at the project level.

In simple terms, PCA is a data reduction and mathematical technique that allows the transformation of a set of possibly correlated variables into a new, uncorrelated set of "principal components" (see Figure 4). These principal components are defined as linear combinations of the variables (in this case, the project criteria) to be synthesized. The transformation is done in such a way that the first principal component is the linear combination of variables that retains the maximum variability contained in the original data (seen Column 1, Table 5).<sup>13</sup> Each principal component assigns weights to each individual criterion. These weights specify the extent to which each variable contributes to the SEI and FEI. In PCA, the sum of the squares of the weights of the variables under the SEI or FEI is equal to one, and the highest weights tend to be assigned to criteria with larger variation. This is because indicators that have a wide range are the most informative and allow for better cross‐project comparisons. Variables with very low variation do not allow for significant differentiation between projects and are thus assigned lower weights. Importantly, the resulting SEI and FEI composite scores

> 13 The subsequent principal components are subject to being orthogonal (uncorrelated) to the previous ones.

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Table 6 below summarizes the results of SEI calculations according to the various weighting scenarios. Scenario 1 shows the results for the 1<sup>st</sup> principal component when no restrictions are imposed. This linear combination can explain up to 29% of the variation in the data. The second column shows the results when PCA‐determined weights are constrained to be all non‐negative. As one can see in Scenario 2, some of the resulting weights are zero.

Scenario 3 introduces an additional constraint to PCA so that no variable contributes less than 5% to the composite SEI score. This ensures that all criteria –carefully selected by consensus between experts and stakeholders– contribute, albeit minimally, to the scores given to the projects through the SEI. While each subsequent constraint reduces the power to explain the variation in the data, the weights derived in Scenario 3 are considered to be the most objective given the constraints and can still explain 21% of data variance. Therefore, these are used as the weights applied in the final IPF results.

NPD suggested that existing safe water coverage should receive the highest priority/weight, followed by prevalence of water borne diseases, poverty level, beneficiaries per million dollars invested. The lowest priority was recommended to be accorded to jobs created per million dollars invested. The jobs created criterion was deemed of lowest priority by the NPD since the direct jobs primarily reflect temporary jobs created during construction. In contrast, long‐term direct jobs associated with operation and maintenance of the project comprise only a small percentage (on average, 0.03%) of the total number of direct jobs created.

Scenario 4 below shows the results that emerge when the analysis is based on the subjective PCA weighting recommendation of the NPD.<sup>17</sup> Following this rule, there is a significant loss in the efficiency of the resulting SEI in terms of the data variation that can be explained compared to previous estimations (see Scenario 4, Table 6).

Finally, a simple average weighting method (Scenario 5 in Table 6) is also estimated. Overall, while there are differences in some individual rankings (as can be expected) due to the different weights, the general trend of the projects that are the highest and lowest on the spectrum does not vary significantly (more details in Section 4.1.5).

> 17 The NPD references were used as additional constraints in the generation of weights through PCA.

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_Table 6: Sensitivity analysis for the composition of the SEI and percentage of data variation explained by each_

||Contributio<br>|n (as a %) of e<br>diffe<br>|ach indicator to t<br>rent weighting sc<br>|he composite SEI<br>hemes<br>|score under<br>|
|---|---|---|---|---|---|
|INDICATORS|Standard<br>PCA*|PCA with<br>weights>0|PCA with<br>weights>min<br>requirement|PCA weights<br>using NPD<br>rule|Simple<br>Average|
||(1)|(2)|(3)|(4)|(5)|
|1. Beneficiaries/US m$|0.055|0%|9%|15%|14.3%|
|2. Jobs created/US m$|0.574|27%|19%|9%|14.3%|
|3. Poverty level|0.082|12%|10%|15%|14.3%|
|4. Continuity of water supply|0.333|28%|24%|15%|14.3%|
|5. Bacterial quality of water|-0.479|0%|9%|9%|14.3%|
|6. Existing safe water coverage|0.564|30%|19%|24%|14.3%|
|7. Prevalence of water-borne diseases|-0.040|2%|9%|15%|14.3%|
|Total||100%|100%|100%|100%|
|% of data variance explained|33%|29%|22%|17%|16%|

Notes: *The figures presented in this column are the originally calculated weights using the unrestricted PCA methodology While there is no normative reason to use one weighting scheme over the other, the IPF analysis herein first presents the PCA method, which is both unbiased with respect to weighting and also best makes use of variation in the data for the purposes of differentiating projects. While there are differences in some individual rankings (as can be expected) due to the different weights, the general patterns of project ranking do not vary significantly.

# Financial and Economic Indicator (FEI)

Similar to the SEI, the FEI scores are also calculated using the PCA approach. However, for the FEI PCA‐based weighting, three other outlier projects in addition to Project 25 (mentioned earlier) were removed. These include outliers include Projects 2 and 4, whose NRW levels are exceptionally higher than the others (36.9 and 36.34, respectively), and Project 27, whose and yield value was zero<sup>18</sup> . All three projects were included in the analysis and only excluded from the weighting process to remove biases.

Table 7 below shows the composition of the FEI score using the PCA approach and a simple average for a comparison.<sup>19</sup> The benefit‐cost ratio has the highest weighting in the FEI indicator when using the PCA (the FEI is constituted almost entirely by the BCR). This is acceptable, as it is the most critical factor to distinguish between projects on financial and economic aspects.

> 18 Based on a September 2014 feasibility report, the water supply for this project is proposed to be drawn from an existing water supply system (Kalu Ganga Water Supply Project) by laying a new transmission pipeline. The report indicates, however, that the existing system has no capacity and must be augmented, but that no proposal or feasibility study has been prepared to ensure water availability.

> 19 Refer to Annexure V to see the exact weights that emerge from the analysis.

22
SET=0.09x Beneficiaries + 0.19XJobs + 0.10xPoverty + 0.24XContinuity of Water Supply + 0.09x Bacterial Quality ofWater + 0.19XExisting Safe Water Coverage + 0.09x Prevalence of Water Borne Diseases FET=0.68X Benefit Cost Ratio + 0.16XExisting Water Resource Yield+ 0.16XNon-Revenue Water Level
_Table 8: Project SEI and FEI rankings and total expected costs_

|ID<sup>21</sup>|PROJECT|SEI<br>Ranking|FEI<br>Ranking|Investment<br>(US$m)|
|---|---|---|---|---|
|P1|Kirama-Katuwana WSP<sup>a</sup><br>|4|21|9|
|P2|Kandy North (Pathadumbara) Water Supply<sup>b</sup>|26|10|112|
|P3|Katana Water Supply (Phase I & II)<sup>a</sup>|23|16|45|
|P4|Hemmathagama Water Supply Scheme<sup>b</sup>|14|8|60|
|P5|Thambuththegama Water Supply<sup>a</sup>|15|6|91|
|P6|Anuradhapura South Water Supply<sup>b</sup>|18|7|102|
|P7|Towns East Polonnaruwa Water Supply<sup>b</sup>|21|13|359|
|P8|Matara Stage IV Water Supply<sup>b</sup>|11|20|134|
|P9|Expansion: Water Pipeline Orugodawatta-Ambatale Road<sup>c</sup>|25||64|
|P10|Eheliyagoda Water Supply<sup>b</sup>|16|14|34|
|P11|Eppawala Water Supply<sup>b</sup>|7|4|40|
|P12|Palugaswewa Water Supply<sup>a</sup>|3|3|20|
|P13|Valachchenai Water Supply<sup>b</sup>|8|25|75|
|P14|Dankotuwa Water Supply<sup>a</sup>|28|23|92|
|P15|Greater Galle Stage III<sup>d</sup>|27|17|67|
|P16|Bandarawela, Diyathalawa, Haputhale Integrated Water Supply<sup>b</sup>|13|15|111|
|P17|Divulapitiya Water Supply<sup>a</sup>|20|27|57|
|P18|Mirigama, Kandalama, Kaleliya and Ganegoda Group Towns|||95|
||Water Supply<sup>b</sup>|24|26||
|P19|Hatharaliyadda Water Supply Scheme<sup>a</sup>|9|24|13|
|P20|Eppawala, Rajangana, Nochchiyagama & Giribawa WSP<sup>b</sup>|17|18|357|
|P21|Yan Oya Water Supply<sup>b</sup>|1|2|102|
|P22|Towns South of Puttlam WSP<sup>b</sup>|12|12|98|
|P23|Greater Mannar WSP<sup>b</sup>|10|11|109|
|P24|Greater Vavuniya WSP<sup>b</sup>|22|9|159|
|P25|Construction of Treatment Plant at Kethhena<sup>e</sup>|2|1|3|
|P26|Ingirya, Handapangoda Water Supply<sup>f</sup>|19|22|81|
|P27|Makandura, Pannala, Kuliyapitiya Water Supply<sup>b</sup>|5|5|14|
|P28|Kalpitiya WSP<sup>b</sup>|7|20|94|

Notes: a Augmentation of the existing system/s with a new raw water source and treatment b Augmentation of the existing small system/s with an integrated project including a new raw water source and treatment c Replacement of an existing unserviceable pipe line due to a road expansion d Expansion of the existing system to provide water to the developing surrounding areas with additional treatment.

e Augmentation of water treatment plant only. Additional water would be distribution to new areas through different funding.

f Augmentation of an existing water supply system with an integrated project. No treatment plant is included as it will receive treated water from another project.

g Augmentation of treated water with a new treatment plant and new transmission systems to provide water to adjoining areas. Distribution systems will be laid with funding obtained from another project.

> 21 In subsequent sections, the results are presented by using project IDs for ease of representation on charts.

24
Implementing the full portfolio of water infrastructure projects would require a US$3.08 billion investment –an amount that exceeds the budget for new water infrastructure projects in the next four years. The estimated available budget over the next four years, as detailed in Table 9 below, is approximately US$ 0.35 billion. This figure is based on a conservative budget estimate that accounts only for the amounts allocated to 'new' water infrastructure projects and does not consider funds budgeted to maintain ongoing projects.

_Table 9: Budget allocation for new projects_

|Year|Budget for New Water Supply Projects<br>(LKR Billion)<br>(USD Million)|
|---|---|
|2017|10.4<br>76.3|
|2018|11.4<br>84.0|
|2019|12.6<br>92.4|
|2020|13.8<br>101.6|
|Total|48.2<br>354.3|

Source: National Water Supply and Drainage Board Galle Road, Ratmalana Vote Ledger Statement: May 31<sup>st</sup> , 2017. Notes: The allocations from 2018 up to 2020 are based on 10 % increase per year from allocations for year 2017.

Figures 5 and 6 show the ordering/ranking of the projects based on their SEI and FEI scores. These figures also display the estimated budget limit to show which projects could be implemented, given the budget constraint, if projects were selected according to one or the other index score only.

_Figure 5: SEI ranking for water infrastructure projects in Sri Lanka_ <!-- Start of picture text --> Social and Environmental Indicator (SEI)<br>100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>P14 P15 P2 P9 P18 P3 P24 P7 P17 P26 P6 P20 P10 P5 P4 P16 P22 P8 P23 P19 P13 P11 P28 P27 P1 P12 P25 P21<br><!-- End of picture text --> ‐‐‐‐ Budget constraint of US$ 0.35b Source: Authors' calculations 25
_Figure 6: FEI rankings for water infrastructure projects in Sri Lanka_ <!-- Start of picture text --> Financial and Economic Indicator (FEI)<br>100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>‐‐‐‐ Budget constraint of US$ 0.35b<br>Source: Authors' calculations<br>P17 P18 P13 P19 P14 P26 P1 P8 P28 P20 P15 P3 P16 P10 P7 P22 P23 P2 P24 P4 P6 P5 P27 P11 P12 P21 P25<br><!-- End of picture text --> Project 14, the Dankotuwa Water Supply Project, ranks the lowest on the SEI scale. This is because the project serves an area that has low levels of poverty and a good existing water supply system in terms of both quantity and quality.<sup>22</sup> According to the FEI, on the other hand, projects 17 and 18 (i.e. Divulapitiya Water Supply; Mirigama, Kandalama and Kaleliya and Ganegoda Group Towns Water Supply, respectively) score the lowest. These low FEI scores are driven by their low benefit‐cost ratios, since both projects have high costs per beneficiary (Project 17‐ US$ 1299 per beneficiary and Project 18 ‐ US$ 1518 per beneficiary).

Distinctively, two projects rank extremely high on both the SEI and FEI. Project 25 (Construction of Treatment Plant at Kethhena) scores the highest on both indicators. This is largely because it would have a high number of both beneficiaries (90,824 new beneficiaries per million dollars invested) and jobs created (67 jobs per million dollars invested). These numbers are significantly higher than any other project in the list. However, it must be repeated that this project is distinctly different in nature to the others in the project list: it is the only water treatment project, while all others are water supply projects.

The other project that scores highly on both indicators is Project 21, Yan Oya Water Supply Project. This project has the lowest safe water coverage (38.59%) and demonstrates a high level of need with respect to water service quality (water supply of between 1‐6 hours per day and in an area with a prevalence of chronic kidney disorder). The third project in the high

> 22 Both project areas have a supply of 18‐24 hours of water, low incidence of water quality issues and a high safe water coverage rate.

26
priority bracket is Project 12, Palugaswewa Water Supply, which also has a low safe water coverage rate and the highest prevalence of water‐borne diseases and chronic kidney disease among all the proposed project sites.

Considering the project rankings for both SEI and FEI (Figure 7) under the assumed budget limits, some projects are designated as "high priority" for being relatively high on both indicators (i.e. projects 11, 12, 21, 25 and 27 that have been marked as green points). Given the budget constraints, several projects (such as projects 14, 15, 17, 18, 22, 26, etc. designated by red points) are of lower priority for implementation, scoring lower according to both SEI and FEI.

_Figure 7: IPF Matrix: Mapping of projects by SEI and FEI_ <!-- Start of picture text --> 100<br>P21<br>90<br>80<br>P25<br>70<br>P12<br>P1<br>60<br>P28 P27<br>P11<br>50 P13 P19 P23<br>P16 P4<br>P8 P22<br>40 P10 P5<br>P20<br>P17 P26 P7 P6<br>30<br>P18<br>P3 P24<br>20<br>P15 P2<br>10<br>P14<br>0<br>0 10 20 30 40 50 60 70 80 90 100<br>FEI<br>SEI (PCA, positive, min req 5%)<br><!-- End of picture text --> ● High Priority Projects

- Lower Priority Projects

● Medium Priority Projects ‐‐‐‐ Budget constraint of US$ 0.35b Source: Authors' calculation High priority projects are in the upper right quadrant (those that fall within the budget constraint imposed along both the SEI and FEI axes), while the lower priority projects are in the lower left quadrant. Projects located in the upper left and lower right quadrants scored relatively high on either the SEI or FEI, but not both. For example, Project 5, Thambuththegama Water Supply project, scored higher on FEI than SEI, whereas Projects 1, 27
13 and 28 (i.e. Kirama‐Katuwana WSP, Valachchenai Water Supply Kalpitiya WSP) scored higher on SEI but not the FEI. These projects are considered medium priority projects.

By design, some of the medium priority projects could still be implemented, since the budget is not completely exhausted after executing all high priority projects. In fact, the five high priority projects constitute only 51% of the available budget. Implementation of the medium‐ priority projects should be subject to expert discussion for selection, preferably under the framework of decision rules used to guide deliberation and selection from among the medium‐priority set (e.g., the relative importance of each index, selection by some key policy goal, etc.). These decision guidelines should be discussed and agreed to prior to comparison and selection.

# 4.1.5. Sensitivity Analysis

To evaluate how sensitive the results are to the different possible weighting schemes (e.g., PCA, subjective rule, simple average), additional calculations were carried out using alternative weights based on the subjective criteria (only for SEI) and equal weighting of criteria (for both, SEI and FEI). Individual SEI and FEI rankings under these different scenarios can be found in Annexures VII, VIII and IX.

In this section, two additional prioritization matrices are presented using the results of the SEI from the subjective and simple average weighting approaches. These are presented below in Figures 8 and 9.

The sensitivity analysis reveals that the results of the IPF analysis remain consistent across all three scenarios. Specifically, Projects 12, 21 and 25 (i.e. Palugaswewa Water Supply, Yan Oya Water Supply project and Construction of Treatment Plant at Kethhena) are high priority regardless of what weightage system is utilized. Similarly, Projects 14 and 15 (i.e. Dankotuwa Water Supply project and Greater Galle Stage III) tend to remain low on the SEI, as these projects are in areas with high existing safe water coverage, consistent levels of water supply with water supply hours between 18‐24, and low poverty levels and, compared to other projects, will generate fewer jobs.

There are, however, some noticeable differences between the sensitivity analysis scenarios and the IPF scenario based on PCA. Firstly, Project 27 that ranks high in the IPF analysis, becomes a medium priority project in the subjective weight and simple average scenario. This is because compared to the PCA weights, in both other approaches, the jobs created and beneficiaries per million dollars invested indicators have comparatively low weights, while these factors are key to the projects' high priority status in the PCA scenario. Similarly, Project 11 is high priority in both the PCA and subjective weight scenario, but a medium priority in the simple average. This is because the slight change in individual rankings resulted in Project 23 (Greater Mannar WSP) – a higher budget project (USD 109 million) – ranking higher, leaving Project 11 just outside the available budget.

28
Figure 8: IPF Matrix using subjective rule suggested by NPD <!-- Start of picture text --> 100<br>P21<br>90<br>80<br>P12 P25<br>70<br>P1 P10<br>P11<br>60 P23<br>50 P13 P28 P8 P16 P4 P5<br>P20 P27<br>40 P19<br>P17 P22<br>P26 P6<br>P7<br>30 P18<br>P3 P24<br>20 P15 P2<br>10 P14<br>0<br>0 10 20 30 40 50 60 70 80 90 100<br>FEI<br>Figure 9: IPF Matrix using a simple average for SEI weights<br>100<br>P25<br>P21<br>90<br>P1<br>80<br>P12<br>70<br>P23<br>P13<br>60 P10<br>P8 P4 P11<br>50 P26 P28 P27<br>P16<br>P17 P19<br>P5<br>40 P20 P22<br>P6<br>P3<br>P18<br>30 P7 P24<br>P15 P2<br>20<br>P14<br>10<br>0<br>0 10 20 30 40 50 60 70 80 90 100<br>FEI<br>SEI (subjective weights)<br>SEI (simple average weights)<br><!-- End of picture text --> Figure 9: IPF Matrix using a simple average for SEI weights

- High Priority Projects

- Lower Priority Projects

- Medium Priority Projects

- ‐‐‐‐ Budget constraint of US$ 0.35b

Source: Authors' calculation 29
## 4.1.6. Step 5: Project Selection

The IPF methodology is intended to inform project selection and foster more transparent, evidence‐based infrastructure policy. The IPF does not, however, propose the issuance of a definitive list of investments. As such, the process of project selection and the discussions and decision processes surrounding it remain a crucial part of infrastructure policy‐making. The IPF is intended to frame government decision‐making in a way that ensures the consideration of key policy goals and fosters accountability in decision‐making.

Projects categorized as 'High Priority' via IPF are natural targets for implementation and are recommended for selection, as they represent the set of projects that score highly with respect to both social‐environmental and economic‐financial considerations. It must be noted, however, that a "good" project in terms of financial and economic performance, may nevertheless be undesirable from a social and environmental perspective, and vice versa. For instance, Project 23 (Greater Mannar Water Supply Project) has a high SEI but a relatively low FEI score. The identification of medium‐priority projects leaves space for expert review, flexibility, and informed political debate. The framework informs decisions regarding projects in this category but leaves room for structured professional and political judgment.

In contrast, a project that achieves very low SEI and FEI scores is an indication that it has serious shortcomings in terms of its expected impacts as compared with other project alternatives. Decision‐makers should have strong, evidence‐ or policy‐based justification for the selection of a project that lies near the origin of the Infrastructure Prioritization Matrix.

# 5.Way Forward

The IPF is a dynamic exercise, in that it can be refined with access to more informative and accurate data. It is also a preliminary exercise that provides a quick overview of how proposed projects compare according to the two parameters of interest. Therefore, this final section looks at what subsequent steps will likely be required to make best use of the IPF in project prioritization in Sri Lanka. Four general tactics for moving forward are described in the following section. These include supplementing the analysis with actual budget data; integrating IPF into the current planning process; building capacity for project prioritization; and identifying the most effective procurement options for proposed projects.

## a) Supplementing analysis with actual budget data

For the purposes of this report, the analysis was based on budget estimates as indicated in 4.1.4 above. As described above, the classification of projects into priority categories (high, medium, lower) requires identifying or estimating the actual budget constraint for the sector.

Naturally, budget increases will result in more resources available to implement additional projects. An expansion of the budget limit would shift the imposed budget lines on the matrix 30
and would thus move some medium‐priority projects into the higher priority zone and some lower priority projects into the medium priority zone. Budget decreases would have the opposite effect. With space to implement fewer projects, some of the higher priority projects would move into the medium priority zone and some medium priority projects would shift to lower priority zone. Therefore, determining the actual budget envelope available for sector development is critical. The IPF approach and the sensitivity scenarios in this report can be re‐run once the actual budget allocation to water sector projects is determined.

# b) Integrating the IPF into the infrastructure planning process

The IPF is a tool developed to guide policy‐making in terms of identifying the projects most likely to help governments attain their development goals. As such, the IPF would be most effective if it is integrated into the infrastructure planning process of a country. Sri Lanka has a well‐defined infrastructure planning process with a clear opportunity to be improved by embedding the IPF in between the project approval phase and financing scheme identification phase (as described in Section 2 above). This is an essential policy decision that requires consulting with multiple stakeholders, including implementing agencies (for example National Water Supply and Drainage Board in case of water sector projects).

# c) Facilitating capacity building workshops

To improve the usefulness of IPF in Sri Lanka and to extend its application to additional sectors, it is important that officials from various departments within the NPD and implementing agencies are trained to effectively utilize the IPF without external support.

The current pilot was applied only to water supply infrastructure projects and carried out largely by the World Bank team, with inputs from officials of the water department within NPD. While the IPF was introduced and discussed with a larger audience within NPD, during the actual process of piloting, the IPF the World Bank team liaised mostly with the officials of the water department within NPD. To build adequate capacity within the broader group of government stakeholders engaged in infrastructure planning, training workshops are planned to train designated officials from all departments of NPD and other sector ministries, as well as other implementing agencies.

# d) Identifying procurement schemes for priority projects

Once the IPF is used to generate a final list of priority projects within each sector, the next step should be to determine the most appropriate procurement schemes for these projects (for example, which of the projects should be implemented as PPPs and which should be implemented by the public entities). The IPF provides elements that can be used as a first step in the identification of potential PPP projects. As the FEI component of the IPF captures financial and economic benefits accruing from a project through indicators such as the project's benefit‐cost ratio (as in the current pilot for water supply investments), internal rate of return, net present value etc., the financial components of these may be used to help identify commercially viable projects.

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Depending on the input indicators (particularly if they are generally measures of financial viability), the FEI may as a whole be used to identify the likeliest candidates for PPP, though this is not the case for this study. The FEI in this IPF study includes NRW levels that represent the current levels of economic inefficiency of existing supply schemes and not of the newly‐ proposed projects themselves. Therefore, areas with existing high levels of NRW are prioritized as they represent a greater economic _need_ in terms of intervention. When considering PPPs, however, projects with the highest likelihood of greater economic efficiency and lower water losses are likely the best candidates for private participation.

Further, it is to be noted that this is a preliminary analysis and must be supported with exhaustive PPP project appraisal. PPPs have great potential to harness the financial resources and expertise of the private sector to expand the space for infrastructure development, but they require careful consideration with respect to commercial viability and sustainability, as well as the legal, regulatory, and organizational underpinnings required to support long‐term contracts.

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