Common Information Based Markov Perfect Equilibria for Linear-Gaussian Games with Asymmetric Information

Common Information based Markov Perfect Equilibria for Linear-Gaussian Games with Asymmetric Information

We consider a class of two-player dynamic stochastic nonzero-sum games where the state transition and observation equations are linear, and the primitive random variables are Gaussian. Each controller acquires possibly different dynamic information about the state process and the other controller’s past actions and observations. This leads to a dynamic game of asymmetric information among the c...

Perfect Bayesian Equilibria in Reputation Games with Nested Information Structure

We analyze reputation games where a strategic long-lived player acts in a repeated game against a collection of short-lived (myopic) Bayesian players. The running assumption in our model is that the information at the short-lived players is nested in that of the long-lived player in a causal fashion. Under this setup, we show that the set of perfect Bayesian equilibria coincide with a properly ...

A Foundation for Markov Equilibria in Infinite Horizon Perfect Information Games

We study perfect information games with an infinite horizon played by an arbitrary number of players. This class of games includes infinitely repeated perfect information games, repeated games with asynchronous moves, games with long and short run players, games with overlapping generations of players, and canonical non-cooperative models of bargaining. We consider two restrictions on equilibri...

Games with Perfect Information

Markov Perfect Equilibria in Stochastic Bequest Games

In many real-life situations, the preferences of an economic agent change over time. Rational behaviour of such agents was studied by many authors (Strotz, Pollak, Bernheim and Ray) who considered so-called “consistent plans”. Phelps and Pollak [10] introduced the notion of “quasi-hyperbolic discounting”, which is a modification of the classical discounting proposed in 1937 by Samuelson. Within...