Format:
1 Online-Ressource (46 Seiten))
Edition:
Online-Ausg
Content:
May 2000 - 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.
Content:
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.
Content:
· 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.
Additional Edition:
Halpern, Jonathan Information and Modeling Issues in Designing Water and Sanitation Subsidy Schemes
Language:
English
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