Dynamic Learning and Context-Dependence in Sequential, Attribute-Based, Stated-Preference Valuation Questions
提出一种混合陈述偏好模型，结合公投式条件估值与实验设计的属性集，通过邮寄调查的序列估值问题发现：人们在序列后期对选项的区分度更高，偏好参数发生偏移，且前后选择集对当前选择有结构性影响，表明人们通过比较属性水平来学习对环境的偏好。
<i>A hybrid stated-preference model is presented that combines the referendum contingent valuation response format with an experimentally designed set of attributes. A sequence of valuation questions is asked to a random sample in a mail-out mail-back format. Econometric analysis shows greater discrimination between alternatives in the final choice in the sequence, and the vector of preference parameters shifts. Lead and lag choice sets have a structural influence on current choices and unobserved factors induce positive correlation across the responses. These results indicate that people learn about their preferences for attribute-based environmental goods by comparing attribute levels across choice sets.</i>