To ensure universal access to water supply and sanitation (WSS) services that are safe, reliable, sustainable, and affordable, it is important to attract the right types of financing and identify the aspects that could be hindering the success of WSS projects. In this study, 62 completed World Bank WSS projects were analyzed to understand the relationship between project characteristics, bank performance, and quality of results. The methodological approach included a systematic quantitative review and comparative, statistical, and regression analyses, considering important aspects of the projects. The existence of correlations and interactions between project results, bank performance, and key aspects of the projects (such as type of project, initial and final risk assessments, commitments and disbursements, and other characteristics) was observed. This study highlights the importance of rating and mitigating WSS project risks (especially the environmental, social, political, and governance risks) and the importance of development bank financing. The applied methodology could be used by both financiers and borrowers.

  • The study highlights the importance of assessing and mitigating risks, especially the environmental, social, political, and governance risks.

  • The rating of project risks appears to be a worthwhile procedure that could be adopted by financiers and borrowers alike.

  • Development bank financing is important for the quality of WSS project results.

Equitable and sustainable access to water supply and sanitation (WSS) services is essential to ensure good quality of life. The COVID-19 (coronavirus disease of 2019) pandemic outbreak, in 2020, was a situation that, once again, stressed the need to ensure that everyone has access to WSS services. Handwashing was identified as one of the daily hygiene measures to reduce disease transmission (Kumpel et al. 2022; Montojo et al. 2022; Nguyen & Pattanarsi 2022). According to the United Nations, even though WSS services have been defined as human rights in 2010, billions of people are still without access to safely managed drinking water and sanitation (UN-Water 2021).

Currently, there is a gap between current financing and future needs in the WSS sector. This gap needs to be addressed to ensure universal access to WSS services worldwide (OECD 2019; Jiang 2022). Closing this gap and maintaining the quality of water and sanitation services will require total investments of hundreds of millions of dollars (OECD 2015a; IDB 2021).

The private sector is a source of additional investments that could be exploited and leveraged to ensure the achievement of sustainable WSS services (Machete & Marques 2021). It is not only important to attract private financing but also to attract tailored financing for each type of project, to increase the project's odds of success. There are numerous examples of WSS projects that were canceled, that did not provide the desired results, or that the results of which were not sustainable.

Different projects have different characteristics (e.g., duration and objectives) and risk profiles. These could influence not only the ability to attract financiers, given that they have different appetites for risk and different expectations when financing projects (OECD 2018), but also the success and results of the projects. Project risks need to be mitigated to enhance investment returns and improve project results (OECD 2015b; Sarfraz et al. 2018; Jiang et al. 2019).

In this context, we identified the need to study the characteristics of completed WSS projects, to understand how they performed and their results. This analysis will include the identification of potential connections between the types of projects, the applied financing solutions, and the main performance characteristics of the projects, among other issues.

For this project, it was decided to analyze the World Bank's portfolio, since the World Bank (WB) is deeply involved in the WSS sector and provides detailed information about each of its projects. More specifically, this study focused on projects financed by two World Bank Group institutions, namely, the International Development Association (IDA) and the International Bank for Reconstruction and Development (IBRD). Notwithstanding the interconnectivity of IBRD and IDA resources, it was considered essential to analyze the projects of both institutions, since IBRD provides financial development and policy financing to middle-income and creditworthy poorer countries, and IDA helps countries in situations of relative poverty through zero-to-low-interest loans and grants (World Bank 2022a).

The data sample is composed of 62 concluded WSS projects, financed by IDA and/or IBRD, between January 2010 and November 2021. The total disbursement was about 9,898 million USD (United States dollars). The projects are considered concluded at the end of WB disbursement and involvement. The lengthy period was chosen to ensure the retrieval and analysis of a representative sample containing projects with both initial and final risk profiles and, also, project results and bank performance ratings. The data sample includes projects from 39 countries (Supplementary material, Appendix 1).

This paper is divided into four main sections. After the introduction, the methodological approach developed and applied in this study is described in Section 2. Then, in Section 3, the results of the analysis, focusing on the main characteristics of the projects and their results, are presented and discussed. Finally, the final section contains the concluding remarks and the expectations for future research.

The objective of the applied methodology was the identification, retrieval, and analysis of data from all relevant projects that benefited from commitments from the WB, from January 2010 to November 2021.

The WB database was accessed to retrieve all the projects specifically from the ‘Water Supply’ and/or ‘Sanitation’ sectors, which had a ‘Closed’ status, were financed by ‘IBRD’ and/or ‘IDA’, and had been approved by the bank's Board between the aforementioned timeframe. Since one of the objectives of this study is to further the understanding of WSS projects that receive repayable financing, the tag ‘Grants’ was not selected.

This allowed the retrieval of data from 69 projects that benefited from one of the three types of current WB lending instruments, namely: Development Policy Financing – DPF (provides budget support to the program of policy and institutional actions from governments or political subdivisions); Investment Project Financing – IPF (provides financing to governments for activities aimed at creating physical and/or social infrastructures); and Program-for-Results Financing – PforR (provides funds linked to the delivery of previously defined results) (World Bank 2021a).

The automatically retrieved data included the projects’ names, their region and country, the board approval and project closing dates, the total project costs, the borrowers’ identification, and the applied lending instruments. In addition to this automatic retrieval key information, it was manually retrieved additional information through the consultation of each project's main documents, including ‘Project Information Document’ (PID), ‘Project Appraisal Document’ (PAD), ‘Implementation Status and Results Report’ (ISR), ‘Implementation Completion and Results Report’ (ICR) and ‘Implementation Completion Report Review’ (ICR-Review).

The data that were additionally collected included the following information: type of project; project duration; IBRD, IDA, grant and/or borrower/recipient commitments (appraisal phase, beginning of the project, and revisions); amounts disbursed; initial and final risk assessments; applied risk mitigation techniques; and results ratings and bank performance ratings according to the WB and the independent evaluation group (IEG).

To determine the main aspects of the sample, the collected data were submitted to a systematic quantitative review, which consisted of grouping, summarizing, and descriptive statistical analysis of key information (e.g., geographical location of the project; project's dedication to the WSS sector; and type of lending instrument). Afterward, comparative, statistical, and regression data analyses were performed, to observe interactions between the projects’ results and bank performance, and key aspects of the projects (e.g., project duration, amounts committed, and average risk ratings). The comparative and statistical analysis was performed by building a correlation matrix (using Pearson's correlation coefficient) to help identify project characteristics that could potentially influence project success. Linear regression data analysis was applied to try to model the relationship between project result ratings and, both, the risks and financing characteristics of the projects.

Systematic quantitative review

An initial analysis resulted in the exclusion of around 10% of the projects, due to lack of information and their deviation from the scope of the present study. A summary of the 62 completed World Bank's WSS projects analyzed can be seen in Table 1.

Table 1

Summary of World Bank's WSS projects analyzed

RegionProject IDFinancing instrumentTotal commitment (million US$)Project dedication to WSS (%)
Africa East P125120 IPF 178 100 
P133591 IPF 233.8 96 
P150844 IPF 100 11 
Africa West P106975 IPF 185.5 38 
P117365 IPF 160 100 
P120026 IPF 123.04 100 
P123513 IPF 273 91 
P124715 IPF 260 41 
P156422 IPF 15 10 
P166075 IPF 11.54 36 
P169830 DPF 350 20 
East Asia and Pacific P112626 IPF 288.39 97 
P113151 IPF 58.85 100% 
P113844 IPF 371.7 90 
P115695 IPF 164.5 100 
P118109 IPF 29.05 10 
P118597 IPF 296.64 48 
P119077 IPF 356.2 100 
P119090 IPF 155 30 
P121414 IPF 700.77 33 
P123133 IPF 192.35 47 
P123384 IPF 344.72 40 
P126611 IPF 339.5 25 
P126817 IPF 127.38 84 
P126856 IPF 325.89 30 
P127435 PforR 266.04 100 
P129431 IPF 343.64 24 
P133018 IPF 400 100 
P133116 IPF 246.6 95 
P150113 IPF 15.89 18 
P158807 IPF 20 25 
P159956 DPF 38.59 27 
Europe and Central Asia P102733 IPF 85.74 92 
P118196 IPF 29 100 
P151416 IPF 14.4 41 
Latin America and Caribbean P106753 DPF 500 10 
P108654 IPF 410 95 
P112073 IPF 143.11 75 
P112074 IPF 117.13 76 
P117293 IPF 119.9 100 
P118064 IPF 84 96 
P120211 IPF 240 94 
P121167 IPF 150 40 
P143495 IPF 45 56 
P143996 IPF 115.6 47 
P145578 PforR 55 100 
P147006 IPF 32 97 
P150475 DPF 700 33 
P154275 IPF 81.2 100 
Middle East and North Africa P098459 IPF 75.1 100 
P117082 IPF 86.63 100 
P117355 IPF 16.13 19 
P120161 IPF 310 100 
P160236 DPF 250 27 
South Asia P090157 IPF 30.11 
P103999 IPF 235.05 100 
P121774 IPF 241.2 100 
P122269 IPF 83.44 100 
P132173 IPF 1000 95 
P143036 IPF 90 100 
P153251 PforR 1.5 100 
P167246 DPF 40 100 
RegionProject IDFinancing instrumentTotal commitment (million US$)Project dedication to WSS (%)
Africa East P125120 IPF 178 100 
P133591 IPF 233.8 96 
P150844 IPF 100 11 
Africa West P106975 IPF 185.5 38 
P117365 IPF 160 100 
P120026 IPF 123.04 100 
P123513 IPF 273 91 
P124715 IPF 260 41 
P156422 IPF 15 10 
P166075 IPF 11.54 36 
P169830 DPF 350 20 
East Asia and Pacific P112626 IPF 288.39 97 
P113151 IPF 58.85 100% 
P113844 IPF 371.7 90 
P115695 IPF 164.5 100 
P118109 IPF 29.05 10 
P118597 IPF 296.64 48 
P119077 IPF 356.2 100 
P119090 IPF 155 30 
P121414 IPF 700.77 33 
P123133 IPF 192.35 47 
P123384 IPF 344.72 40 
P126611 IPF 339.5 25 
P126817 IPF 127.38 84 
P126856 IPF 325.89 30 
P127435 PforR 266.04 100 
P129431 IPF 343.64 24 
P133018 IPF 400 100 
P133116 IPF 246.6 95 
P150113 IPF 15.89 18 
P158807 IPF 20 25 
P159956 DPF 38.59 27 
Europe and Central Asia P102733 IPF 85.74 92 
P118196 IPF 29 100 
P151416 IPF 14.4 41 
Latin America and Caribbean P106753 DPF 500 10 
P108654 IPF 410 95 
P112073 IPF 143.11 75 
P112074 IPF 117.13 76 
P117293 IPF 119.9 100 
P118064 IPF 84 96 
P120211 IPF 240 94 
P121167 IPF 150 40 
P143495 IPF 45 56 
P143996 IPF 115.6 47 
P145578 PforR 55 100 
P147006 IPF 32 97 
P150475 DPF 700 33 
P154275 IPF 81.2 100 
Middle East and North Africa P098459 IPF 75.1 100 
P117082 IPF 86.63 100 
P117355 IPF 16.13 19 
P120161 IPF 310 100 
P160236 DPF 250 27 
South Asia P090157 IPF 30.11 
P103999 IPF 235.05 100 
P121774 IPF 241.2 100 
P122269 IPF 83.44 100 
P132173 IPF 1000 95 
P143036 IPF 90 100 
P153251 PforR 1.5 100 
P167246 DPF 40 100 

Most of the projects were from East Asia and the Pacific (34%) and Latin America and the Caribbean (23%). The country with the most financed projects was China (11 projects), followed by Vietnam and Brazil (five projects each), and India (four projects). In this sample, more than half of the countries only had one project financed by the WB (53%).

The sample under study includes projects with different types of objectives for the WSS sector, such as to reform regulatory frameworks and governance practices; to improve public financial management; to reform or establish public policies and institutional frameworks; to establish systems for treated wastewater safe disposal and reuse; to increase sustainable water and sanitation services access; to promote capacity building of key institutions in the WSS sector; among other objectives.

The projects financed by the WB are not limited to the WSS sector, covering a wide range of topics, sometimes even within the same project (e.g., energy, urban transport, and others). Due to the multidisciplinary nature of some of the projects, it was decided to characterize the type of WSS project financed by the WB, through the identification of the project's dedication to the WSS sector (i.e., how much the projects are exclusively about the WSS sector). Thus, it was observed that, on average, the sample is composed of projects 67% dedicated to the WSS sector (with a median of 91%). Only 21 of the projects were solely focused on the WSS sector.

IPF was used to finance 53 projects, while three of the remaining were financed through PforR and six through DPF. The projects depended on commitments from IDA and/or IBRD, and also sometimes on non-WB administered financing from other entities and grants.

The WB project cycle is comprised of six stages, namely: identification; preparation; appraisal; negotiations and board approval; implementation and support; and completion, validation, and evaluation (World Bank 2023). The studied sample is comprised of projects that went through these stages and are currently closed.

According to the World Bank (2023), the borrower is responsible for the identification and proposal of projects, while the initial project concept and its beneficiaries are agreed between the borrower and the WB. Then, the project preparation phase is the borrower's responsibility, while the WB provides technical assistance, analysis, and advice. Both the borrower and the bank contribute during the appraisal and the negotiation phases. The borrower is the responsible actor in the implementation phase, while the WB provides support to ‘improve results, help manage risks, and increase institutional development’. The WB ensures the existence of adequate fiduciary controls on the use of project funds during this phase. The project's progress is monitored by both the borrower and the WB. The WB is responsible for the completion, validation, and evaluation phase. Thus, at the end of the project, the WB analyses and evaluates outcomes, challenges, and lessons learned. The project results and the WB's performance is rated by the WB and the IEG.

During the implementation and support stage, changes to the project design and financing may occasionally be necessary, due to unforeseen occurrences, delays, and changing conditions. Sometimes, projects are not completed, and financing is interrupted due to the non-achievement of results. In contrast, the WB's policy and procedure frameworks foresee an increase in agreed financing motivated by the desire to expand and reward projects that produce positive results, for both IPF (‘The Bank may provide additional financing to an ongoing, well-performing Project (…)’) and PforR (‘The Bank provides the additional financing if it is satisfied with the overall implementation of the original (or restructured) PforR Program’) (World Bank 2021b, 2022b). In this study, 71% of projects had their durations extended, 24% incurred financier agreements changes, 85% received smaller amounts of financing than originally planned, and 10% received more than the original commitment.

Project risks are assessed, by the WB, through a Systematic Operations Risk rating Tool that rates each type of risk into one of the following four categories: high, substantial, moderate, or low (World Bank 2014). The main risks identified and rated by the WB are the following: institutional capacity for implementation and sustainability (IC); sector strategies and policies (SP); technical design of the project (TD); macroeconomic (MA); environmental and social (ES); fiduciary (FI); stakeholders (SH); and political and governance (PG). The results of the initial and final risk evaluations and the risk mitigation techniques applied were collected and analyzed. However, due to a lack of available data, some of the collected risk ratings were not the risk ratings attributed by the WB at the beginning or closure of the projects, but the first and final ratings that the WB published and/or rated.

According to the literature, risks generally decrease over the duration of infrastructure projects (Davison et al. 2013; Ehlers 2014; McCoy & Schwartz 2022). In the present study, the final risk ratings of the projects tended to be better or equal to the initial ratings. The average initial risk rating was substantial to moderate, while the final risk rating of the projects was moderate. However, this positive trend was not always observed for individual risks ratings. Regardless, most of the project risks appear to be, to some extent, somewhat mitigated.

The projects’ overall result rating and bank performance rating are, typically, calculated and published by both the WB and an IEG. The bank's performance is assessed by considering factors such as the adequacy of WB's initial technical assessments, the quality of WB supervision, and others. The overall result rating of a project depends on the achievement of specific predefined project development objectives. Each project has its own set of development objectives.

According to both the WB and the IEG ratings, the average project result rating and the WB's performance rating were both ‘moderately satisfactory’. The WB's ratings were similar to, but slightly more optimistic than, the ones issued by the IEG.

The projects’ overall result rating can range from highly unsatisfactory to highly satisfactory, as shown in Figure 1, which presents the overall project ratings, according to WB calculations. According to the WB, only 45% of the projects achieved their development objectives in a satisfactory or highly satisfactory manner.
Figure 1

Overall project ratings, according to the WB.

Figure 1

Overall project ratings, according to the WB.

Close modal

Comparative and statistical data analysis

Following the collection and individual analysis of the previously described projects’ main aspects, a comparative analysis was carried out, to assess their potential influence on the results of WSS projects.

A correlation matrix was built using Pearson's correlation coefficient (with IBM SPSS Statistics software). The aim was to identify potential connections between the collected variables of the WSS projects and these projects’ results. The identification of statistically significant correlations was also intended, since these are correlations that are less likely to have occurred by chance. In Table 2, the correlations between the project result ratings and other key aspects of the WSS projects are presented. In Table 3, other relevant correlation results are presented including correlations between key project aspects and the duration of the project, the project's dedication to the WSS sector, and the bank performance rating according to the IEG.

Table 2

Correlations between project result ratings according to WB and other project key aspects

Correlations between project result ratings according to the World Bank and other project key aspects
 Project result rating according to the World Bank 
Project result rating according to the independent evaluation group 0.958** 
Bank performance rating according to the World Bank 0.654** 
Bank performance rating according to the independent evaluation group 0.739** 
Initial risk rating average 0.21 
Final risk rating average 0.430** 
Change in risk rating average between initial and final risks 0.23 
Environmental and social initial risks 0.08 
Fiduciary initial risks −0.02 
Stakeholders initial risks 0.03 
Political and governance initial risks 0.07 
Macroeconomic initial risks 0.09 
Technical design of the project initial risks 0.357** 
Sector strategies and policies initial risks 0.05 
Institutional capacity for implementation and sustainability initial risks 0.14 
Other initial risks 0.03 
Environmental and social final risks 0.368** 
Fiduciary final risks 0.19 
Stakeholders final risks 0.405** 
Political and governance final risks −0.01 
Macroeconomic final risks 0.17 
Technical design of the project final risks 0.508** 
Sector strategies and policies final risks 0.258* 
Institutional capacity for implementation and sustainability final risks 0.422** 
Other final risks 0.378* 
Difference between initial and final environmental and social risk 0.2 
Difference between initial and final fiduciary risk 0.16 
Difference between initial and final stakeholders risk 0.335** 
Difference between initial and final political and governance risk −0.06 
Difference between initial and final macroeconomic risk 0.08 
Difference between initial and final technical design of the project risk 0.1 
Difference between initial and final sector strategies and policies risk 0.2 
Difference between initial and final institutional capacity for implementation and sustainability risk 0.256* 
Difference between initial and final other risks −0.03 
Lending instrument −0.13 
Who committed at appraisal −0.03 
Who committed at the beginning 0.04 
Who disbursed 0.11 
Changes between who committed and who disbursed 0.11 
Commitment at appraisal – IBRD 0.24 
Commitment at appraisal – IDA −0.16 
Commitment at appraisal – Grant 0.13 
Commitment at appraisal – Other −0.08 
Commitment at appraisal – Total −0.01 
Committed at the beginning – IBRD 0.24 
Committed at the beginning – IDA −0.2 
Committed at the beginning – Grant 0.11 
Committed at the beginning – Other −0.06 
Committed at the beginning – Total 0.02 
Disbursed – IBRD 0.33 
Disbursed – IDA 0.06 
Disbursed – Grant 0.11 
Disbursed – Other 0.08 
Disbursed – Total 0.22 
Difference between commitment at appraisal and disbursement – IBRD (%) 0.443** 
Difference between commitment at appraisal and disbursement – IDA (%) 0.302* 
Difference between commitment at appraisal and disbursement – Grant (%) 0.2 
Difference between commitment at appraisal and disbursement – Other (%) 0.2 
Difference between commitment at appraisal and disbursement – Total (%) 0.519** 
Difference between commitment at the beginning and disbursement – IBRD (%) 0.453** 
Difference between commitment at the beginning and disbursement – IDA (%) 0.406** 
Difference between commitment at the beginning and disbursement – Grant (%) −0.05 
Difference between commitment at the beginning and disbursement – Other (%) 0.19 
Difference between commitment at the beginning and disbursement – Total (%) 0.631** 
Number or total financier agreements 0.15 
Number of initial financier agreements −0.06 
Difference between number of initial and final financier agreements 0.21 
Project dedication to water supply and sanitation −0.14 
Region −0.2 
Duration of the project 0.05 
If the duration was extended 0.18 
Correlations between project result ratings according to the World Bank and other project key aspects
 Project result rating according to the World Bank 
Project result rating according to the independent evaluation group 0.958** 
Bank performance rating according to the World Bank 0.654** 
Bank performance rating according to the independent evaluation group 0.739** 
Initial risk rating average 0.21 
Final risk rating average 0.430** 
Change in risk rating average between initial and final risks 0.23 
Environmental and social initial risks 0.08 
Fiduciary initial risks −0.02 
Stakeholders initial risks 0.03 
Political and governance initial risks 0.07 
Macroeconomic initial risks 0.09 
Technical design of the project initial risks 0.357** 
Sector strategies and policies initial risks 0.05 
Institutional capacity for implementation and sustainability initial risks 0.14 
Other initial risks 0.03 
Environmental and social final risks 0.368** 
Fiduciary final risks 0.19 
Stakeholders final risks 0.405** 
Political and governance final risks −0.01 
Macroeconomic final risks 0.17 
Technical design of the project final risks 0.508** 
Sector strategies and policies final risks 0.258* 
Institutional capacity for implementation and sustainability final risks 0.422** 
Other final risks 0.378* 
Difference between initial and final environmental and social risk 0.2 
Difference between initial and final fiduciary risk 0.16 
Difference between initial and final stakeholders risk 0.335** 
Difference between initial and final political and governance risk −0.06 
Difference between initial and final macroeconomic risk 0.08 
Difference between initial and final technical design of the project risk 0.1 
Difference between initial and final sector strategies and policies risk 0.2 
Difference between initial and final institutional capacity for implementation and sustainability risk 0.256* 
Difference between initial and final other risks −0.03 
Lending instrument −0.13 
Who committed at appraisal −0.03 
Who committed at the beginning 0.04 
Who disbursed 0.11 
Changes between who committed and who disbursed 0.11 
Commitment at appraisal – IBRD 0.24 
Commitment at appraisal – IDA −0.16 
Commitment at appraisal – Grant 0.13 
Commitment at appraisal – Other −0.08 
Commitment at appraisal – Total −0.01 
Committed at the beginning – IBRD 0.24 
Committed at the beginning – IDA −0.2 
Committed at the beginning – Grant 0.11 
Committed at the beginning – Other −0.06 
Committed at the beginning – Total 0.02 
Disbursed – IBRD 0.33 
Disbursed – IDA 0.06 
Disbursed – Grant 0.11 
Disbursed – Other 0.08 
Disbursed – Total 0.22 
Difference between commitment at appraisal and disbursement – IBRD (%) 0.443** 
Difference between commitment at appraisal and disbursement – IDA (%) 0.302* 
Difference between commitment at appraisal and disbursement – Grant (%) 0.2 
Difference between commitment at appraisal and disbursement – Other (%) 0.2 
Difference between commitment at appraisal and disbursement – Total (%) 0.519** 
Difference between commitment at the beginning and disbursement – IBRD (%) 0.453** 
Difference between commitment at the beginning and disbursement – IDA (%) 0.406** 
Difference between commitment at the beginning and disbursement – Grant (%) −0.05 
Difference between commitment at the beginning and disbursement – Other (%) 0.19 
Difference between commitment at the beginning and disbursement – Total (%) 0.631** 
Number or total financier agreements 0.15 
Number of initial financier agreements −0.06 
Difference between number of initial and final financier agreements 0.21 
Project dedication to water supply and sanitation −0.14 
Region −0.2 
Duration of the project 0.05 
If the duration was extended 0.18 

*Correlation is significant at the 0.05 level (two-tailed).

**Correlation is significant at the 0.01 level (two-tailed).

Where: ‘Who’ refers to the different combinations of financing entities, namely: IDA; IBRD; IBRD and IDA; IDA and other entities; IBRD and other entities; or IDA, IBRD, and other entities.

Table 3

Correlations between several project key aspects and the duration of the projects, the project's dedication to WSS, and the bank performance rating according to the Independent Evaluation Group

VariablesCorrelation result
Duration Who committed at appraisal 0.357** 
Who committed at the beginning 0.439** 
Who disbursed 0.303* 
Changes between who committed and who disbursed −0.085 
Initial risk rating average 0.219 
Final risk rating average 0.296* 
Change in risk rating average 0.133 
Project dedication to WSS Who committed at appraisal 0.360** 
Who committed at the beginning 0.16 
Who disbursed 0.21 
Bank performance rating according to the Independent Evaluation Group Who committed at appraisal −0.059 
Who committed at the beginning −0.036 
Who disbursed 0.036 
Changes between who committed and who disbursed 0.071 
Initial risk rating average −0.014 
Final risk rating average 0.427** 
Change in risk rating average 0.394** 
Difference between commitment at appraisal and disbursement – IBRD (%) 0.24 
Difference between commitment at appraisal and disbursement – IDA (%) 0.148 
Difference between commitment at appraisal and disbursement – Grant (%) 0.12 
Difference between commitment at appraisal and disbursement – Other (%) 0.241 
Difference between commitment at appraisal and disbursement – Total (%) 0.372** 
Difference between commitment at the beginning and disbursement – IBRD (%) 0.265* 
Difference between commitment at the beginning and disbursement – IDA (%) 0.274* 
Difference between commitment at the beginning and disbursement – Grant (%) −0.234 
Difference between commitment at the beginning and disbursement – Other (%) 0.24 
Difference between commitment at the beginning and disbursement – Total (%) 0.454** 
VariablesCorrelation result
Duration Who committed at appraisal 0.357** 
Who committed at the beginning 0.439** 
Who disbursed 0.303* 
Changes between who committed and who disbursed −0.085 
Initial risk rating average 0.219 
Final risk rating average 0.296* 
Change in risk rating average 0.133 
Project dedication to WSS Who committed at appraisal 0.360** 
Who committed at the beginning 0.16 
Who disbursed 0.21 
Bank performance rating according to the Independent Evaluation Group Who committed at appraisal −0.059 
Who committed at the beginning −0.036 
Who disbursed 0.036 
Changes between who committed and who disbursed 0.071 
Initial risk rating average −0.014 
Final risk rating average 0.427** 
Change in risk rating average 0.394** 
Difference between commitment at appraisal and disbursement – IBRD (%) 0.24 
Difference between commitment at appraisal and disbursement – IDA (%) 0.148 
Difference between commitment at appraisal and disbursement – Grant (%) 0.12 
Difference between commitment at appraisal and disbursement – Other (%) 0.241 
Difference between commitment at appraisal and disbursement – Total (%) 0.372** 
Difference between commitment at the beginning and disbursement – IBRD (%) 0.265* 
Difference between commitment at the beginning and disbursement – IDA (%) 0.274* 
Difference between commitment at the beginning and disbursement – Grant (%) −0.234 
Difference between commitment at the beginning and disbursement – Other (%) 0.24 
Difference between commitment at the beginning and disbursement – Total (%) 0.454** 

*Correlation is significant at the 0.05 level (two-tailed).

**Correlation is significant at the 0.01 level (two-tailed).

 ‘Who’ refers to the different combinations of financing entities, namely IDA; IBRD; IBRD and IDA; IDA and other entities; IBRD and other entities; or IDA, IBRD, and other entities.

The comparative analysis, firstly, allowed us to assess and confirm that the project evaluations performed by the WB could be considered reliable. This confirmation was important since some of the projects only received project result ratings from the WB itself. The IEG only rated projects that were also rated by the WB. Therefore, as expected from the systematic quantitative review and visual comparative analysis, it was found that the following variables have strong and significant correlations with each other: WB project result rating, IEG project result rating, WB performance self-rating, and IEG rating of WB performance. Financiers that have a supportive role in the implementation of projects and that help manage risks and improve results, such as the WB, should only evaluate their involvement positively if the projects achieve the intended results. Thus, it is expected that the success of WSS projects could be highly dependent on the performance of their financiers.

The performance of development banks could be important since they generally provide technical support and capacity training when they get involved in WSS projects; and monitor the development of the project to support the achievement of objectives. Development banks do not act solely to maximize profits (Reis 2022). Development banks seek to support projects that, due to their characteristics, are unable to attract the necessary private financing (Machete & Marques 2023). Thus, this type of financier frequently carries out critical actions in financing and supporting projects aligned with sustainable development goals.

As anticipated, projects with less average risk at the time of completion presented better results and WB performance ratings. Although initial and final average risks are correlated, initial average risk ratings do not appear to greatly influence the result of the project (i.e., a correlation was not observed), while final average risks do (i.e., a correlation was observed).

In addition, even though a correlation was not identified, there is a tendency for projects with better average initial risk ratings to be lengthier. This is interesting since lengthier projects have better final project risk ratings (i.e., the duration of the project positively correlates with the average final risk rating of the project) and have the tendency to present better result ratings. Thus, to promote project success, it is important to lower the impact of risks on a project even before the start of the project and to apply appropriate risk mitigation techniques during the project's life.

Since, as previously mentioned, the average risk rating of the WSS projects tended to improve by the end of the WB project cycle, it could be theorized that WSS project loans are not necessarily high risk, as most financiers believe them to be. This observation is supported in the literature, given that other authors mentioned that the longer-term infrastructure loans that WSS projects require are not necessarily riskier (Choi et al. 2010; OECD 2010, 2019; Sorge 2011). Nonetheless, the long-term outcomes of the projects (e.g., long-term financial viability) were not analyzed in the present study.

The duration (in years) and the dedication of the project to the WSS sector (in percentage) seem to positively correlate with the entities that commit financing at the appraisal phase of projects. In addition, it was observed that, typically, the more dedicated to the WSS sector and the lengthier the project is, the more complex the financiers’ arrangement (i.e., the need to involve more than one institution appears to increase). The duration of the project has the potential to influence who actually commits at the beginning of the project and then who disburses financing (i.e., significant positive correlations were observed). The dedication to the WSS sector appears to only have the potential to be influential in attracting or scaring financiers in the appraisal phase. This could mean that, once the financiers decide to finance a WSS project, they do not usually withdraw from the project due to the dedication factor.

However, no correlation was found between the result rating of the project and the entities that committed at appraisal, committed at the beginning of the project, or actually disbursed financing. In this sample, the different combinations of financing entities (i.e., IDA; IBRD; IBRD and IDA; IDA and other entities; IBRD and other entities; or IDA, IBRD, and other entities) do not appear to be highly influential on the project's result ratings or bank performance.

Changes in who actually disburses financing (in comparison with who committed at appraisal and the beginning of the project) do not appear to have the potential to greatly influence the result rating of the projects or the bank's performance. Even though there was no correlation, a positive relationship was observed, in which better results could be found in projects that benefited from financing from the initially established financiers. This type of positive relationship was expected since suitable financing arrangements do not need to be changed to ensure project success. This observation highlights the need to correctly scale and plan WSS projects, including their financing needs, to guarantee their success. The literature provides support for this observation, since other researchers mentioned the need for careful financial planning of infrastructure projects (through, for example, rigorous project evaluation procedures) to ensure project success and avoid the need for reactionary and corrective actions (Hoggan et al. 1981; Merna & Njiru 2002).

Good project planning is essential. However, it is not easy to predict future projects' needs, especially when the initial circumstances change after the beginning of the project. Therefore, sometimes, the WB chooses to release more than one credit and/or change the amounts of the provided financing.

The result ratings of projects were better the more it was disbursed by IBRD or IDA in relation to their commitment at appraisal and their original commitment. This positive correlation was also observed for the projects’ total disbursements. The same type of correlation was not apparent for the appraisal and original commitments from grants or other financiers. In addition, in instances where grant amounts were lower than expected, the WB performed better. Thus, potentially, there could be a lower need for the disbursement of non-repayable financing in WSS projects when financiers (especially development finance institutions) perform well.

Higher amounts of disbursement by IBRD or IDA, in relation to their original commitment, correlated positively to the WB performance rating. This positive correlation was also evident for the projects’ total disbursements. It was observed that when the recorded results were positive during the project cycle, there was a tendency to disburse additional financing and extend the duration of the projects.

These results were not unexpected given that, as previously mentioned, the WB tends to provide extra financing and/or extend the timeline of projects that are providing positive results. Hence, the main constraint for additional financing is the performance of the project.

However, higher amounts of commitment did not guarantee better project results, for either of the lending instruments analyzed. Thus, it is important to assess and determine the amounts that need to be disbursed for the success of the project at the project's appraisal and/or initial phases, and only increase the amounts afterward if justifiable. This type of strategy is a leveraging tool that can be applied by financiers, to incentivize the borrower's good performance, since only good-performing projects would get the opportunity to receive additional financing for further development.

Most of the projects did not receive the totality of the amounts initially agreed upon, and the result ratings of the projects were not as positive as desired. Thus, the WB (and other financiers) could more heavily apply conditional disbursement of financing during the development of the project cycle. This would mean the establishment of interim objectives that need to be reached by the borrowers before the disbursement of pre-determined amounts of financing. In addition, it would be advisable to implement preplanned action plans for when the interim objectives are not being met, to ensure the successful completion of the project.

The WB's PforR is an example of a results-based financing instrument, which ties financing to the achievement of results, which could be an important source of finance for development finance (Rodriguez et al. 2012). However, despite being introduced in 2012, PforR is still not widely applied. Only 10 WSS PforR projects were approved by the bank's Board between January 2015 and April 2021, corresponding to 5.4% of all projects that were approved in that period (Machete & Marques 2023). This instrument still needs to be adjusted to improve its applicability and to ensure that contractual results are not limited to easily achievable objectives that do not promote the sustainability of project results.

The described WB's flexibility could be a factor that positively influences the success of the WSS projects it finances. According to Ehlers (2014), banks have the expertise to monitor projects, the capacity to negotiate debt restructurings in case of unforeseen events, and the flexibility to gradually disburse funds, making their loans a beneficial option to finance the WSS sector and its projects.

Lastly, regarding the three types of WB lending instruments, it was not possible to draw comparative conclusions concerning their relationship with the result ratings of projects and bank performance ratings, since, as previously mentioned, the sample was mainly composed of projects financed by IPF.

Regression analysis

The results of the statistical data analysis point to potential relationships between risks or financing characteristics and project result ratings. To study these relationships we applied linear regression.

In this context, the two hypotheses that we tested were the following: there is a relationship between initial and final risk ratings and project result ratings (H1); and there is a relationship between changes in the amount disbursed compared to the amount originally committed by each entity and project result ratings (H2). The null hypotheses are the inexistence of the mentioned relationships. In Table 4, it can be seen the two hypotheses’ dependent and independent variables and their units.

Table 4

Descriptions and units of the dependent and independent variables for each of the hypotheses to be applied in the regression analysis

HypothesisDependent Variable
Independent Variables
DescriptionUnitsDescriptionUnits
H1 Project result rating Highly satisfactory – 6
Satisfactory – 5
Moderately satisfactory – 4
Moderately unsatisfactory – 3 
Risk ratings Low – 4
Moderate – 3
Substantial – 2
High - 1 
H2  Unsatisfactory – 2
Highly unsatisfactory – 1
Canceled - 0 
Difference between disbursements and original commitments 
HypothesisDependent Variable
Independent Variables
DescriptionUnitsDescriptionUnits
H1 Project result rating Highly satisfactory – 6
Satisfactory – 5
Moderately satisfactory – 4
Moderately unsatisfactory – 3 
Risk ratings Low – 4
Moderate – 3
Substantial – 2
High - 1 
H2  Unsatisfactory – 2
Highly unsatisfactory – 1
Canceled - 0 
Difference between disbursements and original commitments 

The determination of the interaction for each hypothesis was performed using SPSS Statistics software. The summary of the multiple linear regression models, which help estimate the relationship between the dependent and independent variables, for H1 and H2, can be seen in Table 5. This table includes the following information: correlation coefficient (R), coefficient of determination (R2), adjusted coefficient of determination (adjusted R2), standard error of the estimate (std. error of the estimate) and Durbin–Watson residuals analysis.

Table 5

Multiple linear regression model summary for each tested hypothesis

Model summary
H1H2
Correlation coefficient (R0.715 0.684 
Coefficient of determination (R20.512 0.468 
Adjusted R2 0.33 0.43 
Standard error of the estimate 1.01907 0.94022 
Durbin–Watson 1.866 2.104 
Model summary
H1H2
Correlation coefficient (R0.715 0.684 
Coefficient of determination (R20.512 0.468 
Adjusted R2 0.33 0.43 
Standard error of the estimate 1.01907 0.94022 
Durbin–Watson 1.866 2.104 

The independence, normality, and homoscedasticity residual conditions were confirmed for the H1 and H2 models, and both null hypotheses were rejected.

The following is the regression equation for H1.
formula
(1)
where iES indicates environmental and social initial risks; iFI indicates fiduciary initial risks; iSH indicates stakeholders initial risks; iPG indicates political and governance initial risks; iMA indicates macroeconomic initial risks; iTD indicates technical design of the project initial risks; iSP indicates sector strategies and policies initial risks; iIC indicates institutional capacity for implementation and sustainability initial risks; fES indicates environmental and social final risks; fFI indicates fiduciary final risks; fSH indicates stakeholders final risks; fPG indicates political and governance final risks; fMA indicates macroeconomic final risks; fTD indicates technical design of the project final risks; fSP indicates sector strategies and policies final risks; fIC indicates institutional capacity for implementation and sustainability final risks.

The contribution of each independent variable to the model, given by the standardized β coefficients (which provide the comparable capacity of each independent variable to predict the dependent variable) was very low. The result of the standardized β coefficients analysis suggests none of the independent variables can predict the result better than the others. However, through the analysis of the p-values, it was observed that two groups of risks presented a significant impact on the project result rating, namely the ES, and PG risks (final risks p-values were, respectively, equal to, and smaller than the α level of 0.05). Nonetheless, according to the analysis of the p-values, none of the independent variables have a high statistically significant impact on the outcome variable (i.e., none have a p-value < 0.001).

In brief, it was observed that the WB's practice of rating various types of risks at the beginning of each project could be considered advantageous since it could help guide the actions necessary for the project's success. Project risks need to be mitigated before and, more importantly, during the project cycle. Thus, the practice of assessing risks at the start, during, and at the end of the project's lifetime, appears to be a worthwhile procedure that could be adopted by financiers and borrowers alike.

Although it may be advantageous to analyze the other types of risks assessed by the WB (namely, IC, SP, TD, MA, FI, and SH risks), the findings highlighted the potential connection between ES and PG risks and WSS project results. ES risks are prevalent in the WSS sector since their related issues (such as water scarcity, environmental changes, or population resettlement due to infrastructure projects) can, for example, pose a threat to socioeconomic development and/or result in project delays (Liu et al. 2017; OECD 2019; Braeckman et al. 2022; Machete & Marques 2023). Political and governance risks can be prevalent and affect the WSS sector, when, for example, a country's political and financial status is unstable, or there is a risk for exploitation and corruption (Rees 1998; Winpenny 2003; Jiang et al. 2019). Thus, borrowers and financiers are advised to, at least, rate the environmental, social, political, and governance risks. The importance of rating these risks has been, also, highlighted by Machete & Marques (2023). This study found that the WB almost always rates the environmental, social, political, and governance risks at the beginning of the project and that these risks, potentially, impact the decision to finance, or not, a project.

The regression equation for H2 is presented next, where the independent variables are the difference between the disbursement and original commitment (in %) for IBRD, IDA, grants, and other entities (i.e., non-WB entities), respectively.
formula
(2)
where IBRD indicates difference between disbursement and original commitment from IBRD (in %); IDA indicates difference between disbursement and original commitment from IDA (in %); Grant indicates difference between disbursement and original commitment from grants (in %); Other indicates difference between disbursement and original commitment from other entities (in %).

According to the analysis of the standardized β coefficients, the order of importance of the independent variables is as follows, from more to least importance: IBRD, IDA, grant, and other entities. In addition, in this model, both the IBRD and IDA independent variables have a high statistically significant impact on the outcome variable (p-value < 0.001).

As previously mentioned, the disbursement of additional financing by the WB is usually applied to well-performing projects. Therefore, the analysis shows that causality appears to be possible both ways: additional WB financing can be disbursed when the project provides good results, while additional financing disbursement could, also, lead to improved results. In addition, the opposite was observed for the amounts disbursed by grants, which could mean that a higher dependency on grants could be an indicator of the worst project results.

The analysis highlights the importance of development banks’ financing for WSS projects compared to other types of financing. This relative importance was also highlighted by a recent study on investment projects in Africa and Asia. Heidler et al. (2023) concluded that multilateral development banks and governments are the most important investors in WSS infrastructure projects. In addition to their relative importance, the relevance of development banks for the financing and development of the WSS sector has been highlighted, demonstrated, and mentioned by various authors in the literature, such as: Kolker et al. (2016) who highlighted the role of development banks as significant WSS sector funders; and Reis (2022) who studied public development banks involvement in the achievement of the SDGs and highlighted the relevancy of development banks in the WSS sector.

This study attempted to identify potential interactions between the projects’ results and WB performance ratings, and projects’ key aspects. The characteristics and results of 62 completed World Bank's WSS projects (approved between January 2010 and November 2021, and with closed status) were analyzed. A systematic quantitative review and comparative, statistical, and regression analyses were performed, examining several project characteristics.

In this context, it was observed that there is a relationship between risks and result ratings of WSS projects. Risk ratings at the beginning and closing of projects are potential indicators of project success. However, only the environmental, social, political, and governance risks exhibited a statistically significant relationship with project result ratings. So, decision-makers (e.g., financiers and borrowers) are advised to always assess, at least, these risks. In addition, decision-makers should apply mitigation techniques to help reduce the negative impacts of risks on project results. In this context, and in short, the performed analysis highlighted the importance of analyzing and evaluating the risks associated with the project, to help promote actions aligned with the success of the project.

A relationship was also observed between the rating of project results and changes in the amounts disbursed relative to what was originally committed by each entity. The performance of the project can influence its access to additional financing, and the disbursement of additional repayable financing (by the main financier and/or others) could positively affect the results of the project.

Thus, the performed analysis seems to suggest that decision-makers should avoid relying excessively on non-repayable financing (i.e., grants), and should focus on reducing the risks associated with the project (especially the environmental, social, political, and governance risks) while guaranteeing a good performance capable of attracting further financing from the project's main financier. Also, the active involvement of multilateral development banks could be promoted, both at the start and during the project cycle.

The developed analysis is significant for financing institutions, borrowers, and academia alike. This study's methodological approach can be replicated in future research, not only in the WSS sector but also in other infrastructure projects financed by different types of financing institutions. The main limitations of this study's methodology were the following: limited access to data; the multidisciplinary nature of the projects did not facilitate an analysis solely focused or influenced by the WSS sector; and dependency on ratings carried out by the WB and/or IEG, without the possibility to assess the strengths/weaknesses and the validity of the rating methodologies applied to rate risks, results, and performance.

Moving forward, it would be interesting to apply the same type of analysis to a sample including projects financed by other development finance institutions, to deepen the understanding of WSS projects’ characteristics relationship with results, and diverse financing needs. Future research might develop methodologies to rate project risks and results, applicable to projects financed by different entities, and include in the analysis the long-term outcomes of the projects. Also, future research could develop an analysis that includes the role and influence of specific entities on the relevant stages of the project.

I.M. and R.M. conceptualized the study; I.M. prepared the methodology; I.M. did software analysis; I.M. and R.M. validated the study; I.M. did formal analysis; I.M. investigated the study; I.M. collected resources; R.M. did data curation; I.M. wrote and prepared the original draft; I.M. and R.M. wrote, reviewed, and edited the article; R.M. supervised the article. All authors have read and agreed to the published version of the manuscript.

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

The authors have no relevant financial or non-financial interests to disclose.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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Supplementary data