Published Paper Details:

The main objective of this study was to assess household water demand and willingness to pay (WTP) for improved water services in Abobo Woreda of Gambella Region. The specific objectives of the research were to estimate mean WTP and establish factors that influence per capita water consumption and WTP for improved water service. The survey data were collected from 260 households using both purposive and cluster sampling methods, in the month of April 2019, mainly in four villages, namely; Tegny, Village 14, Village 17 and Chebukier. The study used the Contingent Valuation Method (CVM) to estimate WTP using a double-bounded dichotomous choice elicitation format. In assessing the determinants of WTP and water consumption, the study employed both the probit model and double-log regression model, respectively. Results from the study showed that about 67% of households in the study areas were willing to pay the initial bid offered for an improvement in their water services. Generally, about 93% of the sampled households were willing to pay something for the improvement in water services. The study further showed that the estimated mean WTP for a 20 liter of water was 0.40 Cents. On household water demand, results showed that the mean daily per capita water consumption was 26.18 liters. Results from the probit model showed that gender, household size, household income, distance and owning a backyard garden positively and significantly affect WTP. Moreover, age, household daily water used, household averting behavior, current water quality, and the initial bid offered negatively and significantly affected WTP for improved water. On the other hand, results from the double-log regression model showed that gender and years of using source were positive factors influencing household water consumption. In addition, distance, household size, and education level were negative determinants of household water consumption. The implications of the study are that factors such as age, income, level of education, gender, distance, and household size should be considered when setting domestic water tariffs and designing strategies on demand management.