Bayesian Estimation of Willingness‐to‐pay Where Respondents Mis‐report Their Preferences*
提出一个修正的条件logit模型，用贝叶斯方法处理揭示偏好实验中受访者误报偏好的不确定性，并应用于英国消费者对无农药食品的选择数据，发现修正后的支付意愿估计值大幅下调。
Abstract We introduce a modified conditional logit model that takes account of uncertainty associated with mis‐reporting in revealed preference experiments estimating willingness‐to‐pay (WTP). Like Hausman et al . [ Journal of Econometrics (1988) Vol. 87, pp. 239–269], our model captures the extent and direction of uncertainty by respondents. Using a Bayesian methodology, we apply our model to a choice modelling (CM) data set examining UK consumer preferences for non‐pesticide food. We compare the results of our model with the Hausman model. WTP estimates are produced for different groups of consumers and we find that modified estimates of WTP, that take account of mis‐reporting, are substantially revised downwards. We find a significant proportion of respondents mis‐reporting in favour of the non‐pesticide option. Finally, with this data set, Bayes factors suggest that our model is preferred to the Hausman model.