Information and Modeling Issues in Designing Water and Sanitation Subsidy Schemes

39 Pages Posted: 20 Apr 2016

See all articles by Vivien Foster

Vivien Foster

World Bank

Andres Gomez-Lobo

University of Chile - Department of Economics

Jonathan Halpern

Georgetown University

Date Written: May 2000

Abstract

Evaluating design alternatives is a first step in introducing optimal water subsidy schemes. The definition of appropriate targeting criteria and subsidy levels needs to be supported by empirical analysis, generally an informationally demanding exercise. An assessment carried out in Panama revealed that targeting individual households would be preferable to geographically based targeting. Empirical analysis also showed that only a small group of very poor households needed a subsidy to pay their water bill.

In designing a rational scheme for subsidizing water services, it is important to support the choice of design parameters with empirical analysis that simulates the impact of subsidy options on the target population. Otherwise, there is little guarantee that the subsidy program will meet its objectives.

But such analysis is informationally demanding. Ideally, researchers should have access to a single, consistent data set containing household-level information on consumption, willingness to pay, and a range of socioeconomic characteristics. Such a comprehensive data set will rarely exist. G-mez-Lobo, Foster, and Halpern suggest overcoming this data deficiency by collating and imaginatively manipulating different sources of data to generate estimates of the missing variables.

The most valuable sources of information, they explain, are likely to be the following:

- Customer databases of the water company, which provide robust information on the measured consumption of formal customers but little information on unmeasured consumption, informal customers, willingness to pay, or socioeconomic variables.

- General socioeconomic household surveys, which are an excellent source of socioeconomic information but tend to record water expenditure rather than physical consumption.

- Willingness-to-pay surveys, which are generally tailored to a specific project, are very flexible, and may be the only source of willingness-to-pay data. However, they are expensive to undertake and the information collected is based on hypothetical rather than real behavior. Where such surveys are unavailable, international benchmark values on willingness to pay may be used.

Combining data sets requires some effort and creativity, and creates difficulties of its own. But once a suitable data set has been constructed, a simulation model can be created using simple spreadsheet software. The model used to design Panama's water subsidy proposal addressed these questions:

- What are the targeting properties of different eligibility criteria for the subsidy?

- How large should the subsidy be?

- How much will the subsidy scheme cost, including administrative costs?

Armed with the above information, policymakers should be in a position to design a subsidy program that reaches the intended beneficiaries, provides them with the level of financial support that is strictly necessary, meets the overall budget restrictions, and does not waste an excessive amount of funding on administrative costs.

This paper - a product of the Finance, Private Sector, and Infrastructure Sector Unit, Latin America and the Caribbean Region - is part of a larger effort in the region to evaluate and disseminate lessons of experience in designing policies to improve the quality and sustainability of infrastructure services and to enhance the access of the poor to these basic services. The authors may be contacted at vfoster@worldbank.org or jhalpern@worldbank.org.

Suggested Citation

Foster, Vivien and Gomez Lobo, Andres and Halpern, Jonathan, Information and Modeling Issues in Designing Water and Sanitation Subsidy Schemes (May 2000). World Bank Policy Research Working Paper No. 2345. Available at SSRN: https://ssrn.com/abstract=630717

Vivien Foster

World Bank ( email )

1818 H Street, N.W.
Washington, DC 20433
United States

Andres Gomez Lobo

University of Chile - Department of Economics ( email )

Diagonal Paraguay 257
Torre 26, Of. 1801
Santiago
Chile

Jonathan Halpern (Contact Author)

Georgetown University ( email )

Washington, DC 20057
United States

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