Learning in Repeated Interactions on Networks

• 成果类型: Article
• 署名作者: Huang, Wanying; Strack, Philipp; Tamuz, Omer
• 署名单位: California Institute of Technology; Yale University
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA20806
• 发表日期: 2024
• 页码: 1-27
• 关键词: Strategic experimentation

摘要

We study how long-lived, rational agents learn in a social network. In every period, after observing the past actions of his neighbors, each agent receives a private signal, and chooses an action whose payoff depends only on the state. Since equilibrium actions depend on higher-order beliefs, it is difficult to characterize behavior. Nevertheless, we show that regardless of the size and shape of the network, the utility function, and the patience of the agents, the speed of learning in any equilibrium is bounded from above by a constant that only depends on the private signal distribution.