Information and Modeling Issues in Designing Water and Sanitation Subsidy Schemes
In designing a rational scheme for subsidizing water services, it is important to support the choice of design parameters with empirical analysis that stimulates the impact of subsidy options on the target population. Otherwise, there is little gua...
| Main Authors: | , , |
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| Format: | Policy Research Working Paper |
| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2014
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/2000/05/437410/information-modeling-issues-designing-water-sanitation-subsidy-schemes http://hdl.handle.net/10986/18848 |
| Summary: | In designing a rational scheme for
subsidizing water services, it is important to support the
choice of design parameters with empirical analysis that
stimulates 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. The authors
suggest overcoming this data deficiency by collating, and
imaginatevily 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: 1) 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. 2) General socioeconomic
household surveys, which are an excellent source of
socioeconomic information, but tend to record water
expenditure rather than physical consumption. 3)
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: a) What are the
targeting properties of different eligibility criteria for
the subsidy? b) How large should the subsidy be? c) 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. |
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