This paper studies the robustness of an equilibrium to incomplete information in binary‐action supermodular games. Using a generalized version of belief operator, we explore the restrictions that prior beliefs impose on higher order beliefs. In particular, we obtain a nontrivial lower bound on the probability of a common belief event, uniform over type spaces, when the underlying game has a monotone potential. Conversely, when the game has no monotone potential, we construct a type space with an arbitrarily high probability event in which players never have common belief about that event. As an implication of these results, we show for generic binary‐action supermodular games that an action profile is robust to incomplete information if and only if it is a monotone potential maximizer. Our study offers new methodology and insight to the analysis of global game equilibrium selection.

This paper characterizes an equilibrium payoff subset for Markovian games with private information as discounting vanishes. Monitoring might be imperfect, transitions depend on actions, types correlated or not, values private or interdependent. It focuses on equilibria in which players report their information truthfully. This characterization generalizes those for repeated games, and reduces to a collection of one-shot Bayesian games with transfers. With independent private values, the restriction to truthful equilibria is shown to be without loss, except for individual rationality; in the case of correlated types, results from static mechanism design can be applied, resulting in a folk theorem.

We present an algorithm to compute the set of perfect public equilibrium payoffs as the discount factor tends to 1 for stochastic games with observable states and public (but not necessarily perfect) monitoring when the limiting set of (long-run players') equilibrium payoffs is independent of the initial state. This is the case, for instance, if the Markov chain induced by any Markov strategy profile is irreducible. We then provide conditions under which a folk theorem obtains: if in each state the joint distribution over the public signal and next period's state satisfies some rank condition, every feasible payoff vector above the minmax payoff is sustained by a perfect public equilibrium with low discounting.

We consider the efficient allocation of a single good with interdependent values in a quasilinear environment. We present an approach to modeling interdependent preferences distinguishing between “payoff types” and “belief types” and report a characterization of when the efficient allocation can be partially Bayesian implemented on a finite type space. The characterization can be used to unify a number of sufficient conditions for efficient partial implementation in this classical auction setting. We report how a canonical language for discussing interdependent types - developed in a more general setting by Bergemann, Morris and Takahashi (2011) - applies in this setting and note by example that this canonical language will not allow us to distinguish some types in the payoff type - belief type language.