Regression analysis of residents’ perception on willingness to pay (WTP) for improved water supply: a case from Nigeria
Journal: Agricultural and Resource Economics: International Scientific E-Journal (Vol.4, No. 2)Publication Date: 2018-06-20
Authors : Tolulope J. Akeju; Samson A. Adeyinka; Gbenga J. Oladehinde; Afolabi F. Fatusin;
Page : 5-18
Keywords : residents’ perception; willingness to pay; improved water supply; Nigeria.;
Abstract
Purpose. The purpose of this paper was to investigate residents' perception on willingness to pay (WTP) for improved water supply in Owo Local Government Area of Ondo State, Nigeria using regression analysis. Methodology / approach. Data were collected from 512 households through multistage sampling from eleven political wards in Owo. The data were analysed using descriptive statistics and stepwise regression. Results. Findings showed that 44.9 % of the residents obtained water from public utility while 21.5 % and 18.8 % obtained water from well and borehole respectively. Majority of the residents (72.6 %) were of the opinion that public water supply were irregular and unreliable but were willing to pay for improved water supply (74.6 %). Residents were willing to pay an average sum of N972 (US$2.7) per month for improved water supply services. Originality / scientific novelty. The results of stepwise regression analysis revealed that age, income, access to water supply, education, quality of water, frequency of water supply and gender were the factors influencing residents' willingness to pay (WTP) for improved water supply services in the study area. There is need for government to create enabling policy for public-private partnership in the improvement of water supply in the study area. Practical value / implications. The implication of these findings is that government and public-private organisation should consider age, income, access to water supply, education, quality of water, frequency of water supply and gender when evaluating residents' willingness to pay in the study area.
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