Estimation of Discrete Games with Weak Assumptions on Information
提出一种在弱信息假设下估计静态离散博弈的方法，采用贝叶斯相关均衡作为解概念，刻画识别集，并应用于意大利超市行业分析大型商场对本地超市的影响。
Abstract We propose a method to estimate static discrete games with weak assumptions on the information available to players. We do not fully specify the information structure of the game but allow instead for all information structures consistent with players knowing their own payoffs. To make this approach tractable, we adopt as a solution concept Bayes correlated equilibrium (BCE). We characterize the sharp identified set under BCE and unrestricted equilibrium selection, and find that in simple games with limited variation in covariates identified sets are informative. In an application, we estimate a model of entry in the Italian supermarket industry and quantify the effect of large malls on local supermarkets. Estimates and predictions differ from those obtained under more restrictive assumptions.