Observational Learning and Information Disclosure in Search Markets
利用房屋实地看房和交易数据，构建并估计了买家观察学习、搜索与出价的结构模型，量化不同信息披露规则对买卖双方福利的影响。
We develop and estimate a structural model of buyers’ observational learning, search, and bidding, using unique data on in-person home viewings and transactions. We use the estimated model to quantify the welfare impact of different information disclosure rules. Our findings indicate that prohibiting the disclosure of home viewing information while permitting only the disclosure of time-on-market would extend the sale time and raise the transaction price, benefiting sellers but harming buyers on average. This paper was accepted by Raphael Thomadsen, marketing. Funding: Z. Fan gratefully acknowledges financial support from the National Natural Science Foundation of China [Grant 72533006]. X. Weng gratefully acknowledges funding from the National Natural Science Foundation of China [Grants 72225001, 72561160161, and 72192843], as well as from the Wuhan East Lake High-Tech Development Zone (also known as the Optics Valley of China, or OVC) National Comprehensive Experimental Base for Governance of Intelligent Society. L.-A. Zhou gratefully acknowledges support from the National Natural Science Foundation of China [Grant 72192844]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.00917 .