Dichotomous‐choice contingent valuation with ‘dont know’ responses and misreporting
提出一种新方法，同时处理二分选择条件估值中的误报和“不知道”回答，使用贝叶斯Probit框架和Gibbs采样估计参数，发现“不知道”更可能对应“是”，误报偏向“否”。
Abstract A new approach is presented that simultaneously deals with Misreporting and Don't Know (DK) responses within a dichotomous‐choice contingent valuation framework. Utilising a modification of the standard Bayesian Probit framework, a Gibbs with Metropolis–Hastings algorithm is used to estimate the posterior densities for the parameters of interest. Several model specifications are applied to two contingent valuation datasets: one on wolf management plans, and one on the US Fee Demonstration Program. We find that DKs are more likely to be from people who would be predicted to have positive utility for the bid. Therefore, a DK is more likely to be a YES than a NO. We also find evidence of misreporting, primarily in favour of the NO option. The inclusion of DK responses has an unpredictable impact on willingness‐to‐pay estimates, since it impacts differently on the results for the two datasets we examine. Copyright © 2009 John Wiley & Sons, Ltd.