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A Bayesian Quantile Binary Regression Approach to Estimate a Payment for Environmental Services
Vásquez Lavín, Felipe; Other authors; Flores, R.; Ibarnegaray, V.
发表日期2017-04-29
出版年2017
语种英语
摘要

Vásquez Lavín, Felipe, R. Flores and V. Ibarnegaray. 2017. “A Bayesian Quantile Binary Regression Approach to Estimate a Payment for Environmental Services.” Environment and Development Economics 22:2: 156-176.
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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.

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.

主题Chile
URLhttps://efdinitiative.org/publications/bayesian-quantile-binary-regression-approach-estimate-payment-environmental-services
来源智库Environment for Development Initiative (Sweden)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/138379
推荐引用方式
GB/T 7714
Vásquez Lavín, Felipe,Other authors,Flores, R.,et al. A Bayesian Quantile Binary Regression Approach to Estimate a Payment for Environmental Services. 2017.
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