Bayesian Analysis of Interval Data Contingent Valuation Models and Pricing Policies
提出一种灵活的贝叶斯统计方法，分析受访者对公共商品（如环境资源或休闲区）的支付意愿，处理零支付意愿和区间观测数据，并预测不同门票价格下的收入，为制定定价政策提供依据。
The general aim of a contingent valuation survey is to elicit the willingness to pay (WTP) of respondents for some (public) commodity without a clear market price. This could be a program to protect some environmental resource or, as in our application, the access to a recreational area of particular interest. In this context, we want to accommodate the possibility of zero WTP and we need to deal with the fact that observations arise as intervals for WTP, rather than point observations. We propose a flexible Bayesian statistical analysis of WTP as a function of characteristics of the respondents that formally incorporates this structure through a mixture model. We consider model uncertainty and pay particular attention to the predictive distribution of revenue if a certain entry price were asked. The latter is an important toot for deriving pricing policies.