Abstract
BackgroundThere is a substantial interest in the values that consumers place on drinking water quality and supply. Financial resources are crucial to improving the urban potable water supply in developing countries that are characterized by low-cost recovery rates and a high and rapidly growing demand for more reliable services. This study examined households’ willingness to pay (WTP) for the improvement of water services by identifying their water choice decisions and the mode of water supply that they prefer the water supply authority to use among several alternative water supply options. Stated-preference data were collected from 322 randomly selected households in Addis Ababa, who were presented with three sets of choices (three alternative bundle choices, including the reference scenario). The data were analyzed using the mixed logit WTP space model. Three approaches to modeling the distribution of WTP (fixed, uncorrelated, and correlated) using mixed logit WTP space models were compared.ResultsThree-quarters of the households agreed to contribute money toward ecosystem-based water supply management (EBWSM) intervention programs on a monthly basis. The average contribution that the respondents were willing to pay was 150.5 Ethiopian Birr (ETB) as a one-off lump sum to kick off the EBWSM activities. Most of the respondents chose a bundle of water supply options that provides risk-free and high-quality water with no months of shortages than moderate water quality that is safe to drink and palatable with 1 month shortages annually. This implies that households would need to be supplied with risk-free, high-quality water without interruption at an appropriate flow pressure. The model with correlations fitted the data well with the highest simulated log-likelihoods at convergence and gave the best estimate of the households’ WTP for water improvement. Nearly 46% of the sampled households were willing to pay more than 33 ETB per month, and 49% of the households were willing to pay between 21 ETB and 33 ETB per month for the monthly water bill. Overall, approximately 95% of the sampled households were willing to pay more than 21 ETB.ConclusionCustomers are willing to pay to avoid most types of water supply restrictions. Moreover, WTP is sensitive to the scope of service improvement, income, affixed price, and elicitation method. In summary, mixed logit WTP-space models can help accurately predict household-level WTP, which can be used to select improvements in drinking water access and services in the Legedadie-Dire catchments.
Highlights
Urban drinking water is publicly supplied under regulation
In this study, we used mixed logit WTP space models to examine downstream household water users’ willingness to pay (WTP) for improved access to or quality of drinking water services based on stated preference data collected from 322 households
The results showed that three-quarters of the households are willing to contribute a certain amount of money on a monthly basis toward ecosystem-based water supply management (EBWSM) intervention programs
Summary
Urban drinking water is publicly supplied under regulation. Globally, nine of every ten people do not have their wastewater treated to any degree, five of ten have inadequate sanitation, and two of ten lack access to a safe water supply (World Bank 1996). Financing the water supply system is imperative to diversify livelihood options for the urban poor in addition to ensuring their access to water because the lack of water supply, hygiene, and sanitation takes an enormous toll on health and well-being and has a large financial cost, including a sizable loss of economic activity (Connor 2015). Time lost due to walking and waiting for water has a ripple effect on their lives, their communities, and the entire economy This time cannot be spent carrying out income-generating activities to diversify their livelihoods, which could contribute to poverty alleviation and social and economic development (WWAP 2015; Connor 2015). Three approaches to modeling the distribution of WTP (fixed, uncorrelated, and correlated) using mixed logit WTP space models were compared
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