Valuing drinking water quality improvement using a Bayesian analysis of the multinomial probit model

Abstract

This article estimates a multinomial probit model structured according to the defensive expenditures for drinking water (DW) choice, using a Bayesian analysis with Gibbs sampling. We also approximate the nonmarginal benefit from discrete improvement in DW quality by calculating the willingness to pay for safe DW. The result shows that the average household of the Seoul Metropolitan Area in Korea is willing to pay 6048 Korean won (GBP 2.91) per month to obtain improved DW similar to boiled water in quality.

Acknowledgements

This work was supported by the Brain Korea 21 Project in 2005. Responsibility for errors and omissions rests with the authors.