Designing optimal water supply systems for developing countries (Nigeria).

摘要

The water supply and sanitation situation in the developing world is still very inadequate. In Africa, for example, more than 47 percent of urban households are without access to safe water. The condition is even worse in rural areas.; This study reports a meta-analysis of more than 20 studies estimating household willingness to pay (WTP) for various improvements in water services in low-income countries using the contingent valuation method. Meta analysis is a statistical technique that combines findings from separate but similar studies to estimate a relationship between, in this case, household WTP and variables describing local conditions and research treatments. Point estimates of discounted monthly household WTP for private connection charges range from {dollar}3.47 to {dollar}5.55, depending on income, compared to {dollar}1.74 to {dollar}3.14 for public standpipes. WTP for sewer connections was {dollar}1.10 to {dollar}1.41.; After a search of secondary literature, life-cycle cost estimates were constructed from raw data provided by expert informants for construction and maintenance of groundwater schemes for public standpipes, private connections, and sanitation facilities for 3 model rural villages in Nigeria. Cost estimates and household WTP estimates are used to determine what proportion of households would sign-up for each service level at various prices, given household income. Because WTP for sewer connections was very low relative to costs, sewer connections were eliminated at this point in the analysis.; Rather than the one-size-fits-all water systems often provided by donor agencies and governments in developing countries, we show that providing a menu of service levels can be welfare-improving. Balanced-budget project feasibility and proportion of households served depend on the pricing scheme, as well as WTP and costs. It was found that 100 per cent of households are served only when some form of price discrimination (e.g., uniform price with targeted rebates) is used. The results are sensitive to the spatial dispersion of income classes in the model villages. With neighbor stratification by income, it becomes more likely that poor neighborhoods would not be served (in the absence of subsidies); with income classes scattered, it is more likely that whole villages may fail the balanced-budget test.