Progressive Random Choice
提出一个灵活的概率选择模型，容纳异质类型和有限理性，通过渐进结构捕捉行为特征差异，并唯一识别异质性以改进福利分析。
We introduce a flexible framework to study probabilistic choice that accommodates heterogeneous types and bounded rationality. We provide a novel progressive structure for the heterogeneous types to capture heterogeneity due to varying levels of a behavioral trait. Given an order of alternatives, our progressive structure sorts the types by the extent to which they align with this order. Unlike the random-utility model, our model uniquely identifies the heterogeneity, allowing policy makers to perform an improved welfare analysis. As a showcase, we provide characterization of a well-studied type of bounded rationality: “less-is-more.” In addition, we provide conditions for unique identification of the underlying order for the less-is-more structure.