A Bayesian Quantile Binary Regression Approach to Estimate a Payment for Environmental Services

Peer Reviewed
24 November 2016

Felipe Vásquez Lavín, Ricardo Flores, Verónica Ibarnegaray

Stated preference approaches, such as contingent valuation, focus mainly on the estimation of the mean or median willingness to pay (WTP) for an environmental good. Nevertheless, these two welfare measures may not be appropriate when there are social and political concerns associated with implementing a payment for environmental services (PES) scheme. In this paper the authors used a Bayesian estimation approach to estimate a quantile binary regression and the WTP distribution in the context of a contingent valuation PES application. Our results show that the use of other quantiles framed in the supermajority concept provides a reasonable interpretation of the technical nonmarket valuation studies in the PES area. We found that the values of the mean WTP are 10–37 times higher than the value that would support a supermajority of 70 per cent of the population.

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Publication reference
Lavín, F. V., Flores, R., & Ibarnegaray, V. (2016). A Bayesian quantile binary regression approach to estimate payments for environmental services. Environment and Development Economics, 22(2), 156–176. doi:10.1017/s1355770x16000255

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Publication | 29 April 2017