Identification and Estimation of Large Network Games with Private Link Information

• 成果类型: Article
• 署名作者: Eraslan, Hulya; Tang, Xun
• 署名单位: Rice University; National Bureau of Economic Research; University of Osaka
• 刊物名称: INTERNATIONAL ECONOMIC REVIEW
• ISSN/ISSBN: 0020-6598
• DOI: 10.1111/iere.70050
• 发表日期: 2026
• 关键词: social interactions; models

摘要

We study the identification and estimation of large network games in which individuals choose continuous actions while holding private information about their links and payoffs. Extending the framework of Galeotti et al., we build a tractable empirical model of such network games and show that the parameters in individual payoffs are identified under large-market asymptotics in which the number of individuals increases to infinity on a single large network. We then propose a semiparametric two-step M-estimator for these individual payoffs and demonstrate its good finite-sample performance in simulations.