Willingness-to-Pay Estimates Using the Double-Bounded Dichotomous-Choice Contingent Valuation Format: A Test for Validity and Precision in a Bayesian Framework
研究了双边界二分式选择条件估值法中受访者可能根据初始出价更新支付意愿的问题，发现更新行为会改变福利估计值并降低精度。
The Double-Bounded Dichotomous- Choice (DB-DC) Contingent Valuation format is thought to yield more precise welfare estimates. Questions remain about its validity. The initial bid may represent information with which respondents update their willingness to pay. A Bayesian model of respondent decision making is estimated for two data sets. The results indicate updating or shifts in respondent willingness to pay between iterated valuations. Nonparametric testing of the welfare estimates reveals that the model incorporating updating yields different values from the standard model. The expected increases in the precision of the DB-DC welfare estimates are lost when updating occurs.