Limit Points of Endogenous Misspecified Learning

• 成果类型: Article
• 署名作者: Fudenberg, Drew; Lanzani, Giacomo; Strack, Philipp
• 署名单位: Massachusetts Institute of Technology (MIT); Yale University
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA18508
• 发表日期: 2021
• 页码: 1065-1098
• 关键词: model; expectations; equilibrium

摘要

We study how an agent learns from endogenous data when their prior belief is misspecified. We show that only uniform Berk-Nash equilibria can be long-run outcomes, and that all uniformly strict Berk-Nash equilibria have an arbitrarily high probability of being the long-run outcome for some initial beliefs. When the agent believes the outcome distribution is exogenous, every uniformly strict Berk-Nash equilibrium has positive probability of being the long-run outcome for any initial belief. We generalize these results to settings where the agent observes a signal before acting.