Social Learning Equilibria

• 成果类型: Article
• 署名作者: Mossel, Elchanan; Mueller-Frank, Manuel; Sly, Allan; Tamuz, Omer
• 署名单位: Massachusetts Institute of Technology (MIT); University of Navarra; IESE Business School; Princeton University; California Institute of Technology
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA16465
• 发表日期: 2020
• 页码: 1235-1267
• 关键词: Information diffusion; aggregation; networks

摘要

We consider a large class of social learning models in which a group of agents face uncertainty regarding a state of the world, share the same utility function, observe private signals, and interact in a general dynamic setting. We introduce social learning equilibria, a static equilibrium concept that abstracts away from the details of the given extensive form, but nevertheless captures the corresponding asymptotic equilibrium behavior. We establish general conditions for agreement, herding, and information aggregation in equilibrium, highlighting a connection between agreement and information aggregation.