Households’ willingness to pay for improved water service in Bonga town, Kaffa zone, Southwestern Ethiopia (International Journal of Agricultural Research, Innovation and Technology, 2022)
This study was initiated to estimate households’ willingness to pay for improved water services and identify its determinants by using the contingent valuation method in Bonga town of Kaffa zone, Southwestern Ethiopia. A cross-sectional data from a total of 212 sampled households’ from two randomly selected kebeles of Bonga town. Contingent valuation survey responses were analyzed through descriptive and econometric analysis using Probit and Bivariate probit model. Double bounded dichotomous choice with open-ended follow-up format was used to elicit the household’s willingness to pay. The descriptive analysis showed that out of the total 205 valid responses indicated that most households’ have perceived the problem of existing water services and were willing to pay for its improvement. Results from the study showed that about 80.98% of the sampled households were willing to pay the initial bid offered for an improvement in their water services scheme. The Probit model regression result shows that the age, daily water use, satisfaction level, fetching time, initial bid, ownership of the house, quality, family size, stay in town, and income were important factors that influenced WTP for improved water service. The study also shows that the maximum willingness to pay for improved water service was calculated to be 57.62 Birr and 30.11 Birr per month from double bounded and open-ended format respectively. The study also reveals that the aggregate welfare gains from the improvement of water supply in the study area were calculated to be 1,176,531 and 614,810 ETB per month from double bounded dichotomous choice and open-ended format respectively. Therefore, the policymakers, as well as project implementers who design solutions to address the problem of water service in the study area, should take account of these factors into their decision.Int. J. Agril. Res. Innov. Tech. 12(1): 105-114, June 2022