A Method to Estimate Discrete Choice Models That Is Robust to Consumer Search

• 成果类型: Article
• 署名作者: Abaluck, Jason; Compiani, Giovanni; Zhang, Fan
• 署名单位: Yale University; University of Chicago; Universidade Nova de Lisboa
• 刊物名称: JOURNAL OF POLITICAL ECONOMY
• ISSN/ISSBN: 0022-3808
• DOI: 10.1086/740223
• 发表日期: 2026
• 关键词: plan choice; INFORMATION; uncertainty; identification; inferences; insurance; MARKETS; demand; sets

摘要

We state conditions under which choice data suffice to identify preferences when consumers may not be fully informed about attributes of goods. Our approach can be used to test for full information, forecast how consumers will respond to information, and conduct welfare analysis when consumers are imperfectly informed. In a lab experiment, we successfully forecast the average response to new information when consumers engage in costly search. In data from Expedia, our method identifies which attribute was not immediately visible to consumers in search results and allows us to compute the value of additional information.