Estimation of Discrete Games with Weak Assumptions on Information

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 and the distribution of opponents’ payoffs. To make this approach tractable we adopt a weaker solution concept: Bayes Correlated Equilibrium (BCE), developed by Bergemann and Morris (2016). We characterize the sharp identified set under the assumption of BCE and no assumptions on equilibrium selection, and find that in simple games with modest variation in observable covariates identified sets are narrow enough to be informative. In an application, we estimate a model of entry in the Italian supermarket industry and quantify the effect of large malls on local grocery stores. Parameter estimates and counterfactual predictions differ from those obtained under the restrictive assumption of complete information.