MICRO/THEORY: Similarity of Information in Games; Professor Joyee Deb (New York University)

Abstract

We propose a new class of stochastic orders to compare the interdependence of joint distributions, that can be used to study the effect of increasing information similarity among players in a game. The orders named "Concentration along the Diagonal" (CAD) capture the intuitive idea that more similar information means that conditional on receiving information, each agent believes that it is now more likely that others have also received the same information. We show that for canonical binary action, symmetric, separable games, and symmetric pure strategy Bayes-Nash equilibrium, increasing similarity of information in the CAD order is equivalent to expanding (shrinking) the equilibrium set when the game exhibits strategic complementarity (substitutability).