Household Demand for Improved Sanitation Services: A Contingent Valuation Study on Addis Ababa, Ethiopia
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Date
2003-07
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Addis Ababa University
Abstract
As any developing country, lack of adequate infrastructure provision is an enormous problem in Ethiopia. When we see the case of Addis Ababa, the current coverage of sanitation service is very low. It is this very fact that has made the government of Ethiopia to extend a concerted effort to improve the condition. In doing so, the government has stated that, the policy for increasing the coverage as well as the proper use of any sustainability of the service requires implementation of a cost recovery system. But this requires information on people’s preferences and WTP for the
proposed improvement. Therefore, the paper examined the determinants of willingness-to-pay for improved sanitation service and investigates the possibility of cost recovery policy directions using the contingent valuation method. For the three suggested improvements (WTP for sewer connection, WTP for improved sludge disposal and WTP for public toilets) a face-to-face personal interview using bidding game elicitation technique on 440 households was conducted. The Heckman two-step estimator used for the empirical analysis revealed that income, education, family size and age are
factors, which consistently affect the decisions whether or not one is willing to pay and the willingness to pay amount for the three WTP scenarios. In matching demand and supply, for the two suggested improvements (WTP for sewer system and WTP for improved sludge disposal), the mean WTP showed that consumers are not able to pay for the improvement to attain full recovery basis. The paper has shown the need for integrated design criteria for the respective sanitation facilities to achieve improvement in the service.
Key Words: Willingness-to-pay, improved sanitation service, Heckman two-step estimator, contingent valuation method, Addis Ababa, Ethiopia
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Keywords
Willingness-to-pay, improved sanitation service, Heckman two-step estimator