Identification and Estimation of a Discrete Game of Complete Information

• 成果类型: Article
• 署名作者: Bajari, Patrick; Hong, Han; Ryan, Stephen P.
• 署名单位: University of Minnesota System; University of Minnesota Twin Cities; Stanford University; Massachusetts Institute of Technology (MIT)
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA5434
• 发表日期: 2010
• 页码: 1529-1568
• 关键词: EMPIRICAL-ANALYSIS; equilibrium; models; entry; CHOICE; COMPETITION; prices

摘要

We discuss the identification and estimation of discrete games of complete information. Following Bresnahan and Reiss (1990, 1991), a discrete game is a generalization of a standard discrete choice model where utility depends on the actions of other players. Using recent algorithms to compute all of the Nash equilibria to a game, we propose simulation-based estimators for static, discrete games. We demonstrate that the model is identified under weak functional form assumptions using exclusion restrictions and an identification at infinity approach. Monte Carlo evidence demonstrates that the estimator can perform well in moderately sized samples. As an application, we study entry decisions by construction contractors to bid on highway projects in California. We find that an equilibrium is more likely to be observed if it maximizes joint profits, has a higher Nash product, uses mixed strategies, and is not Pareto dominated by another equilibrium.