Stable outcomes and information in games: An empirical framework

Abstract

Empirically, many strategic settings are characterized by stable outcomes in which players’ decisions are publicly observed, yet no player takes the opportunity to deviate. To analyze such situations in the presence of incomplete information, we build an empirical framework by introducing a novel solution concept that we call Bayes stable equilibrium and computationally tractable approaches for estimation and inference. Our framework allows the researcher to be agnostic about players’ information and the equilibrium selection rule. In an application, we study the strategic entry decisions of McDonald’s and Burger King in the US. While the Bayes stable equilibrium identified set is always (weakly) tighter than the Bayes correlated equilibrium identified set, our results show that the former can be substantially tighter in practice. In a counterfactual experiment, we examine the impact of increasing access to healthy food on the market structures in Mississippi food deserts.