In the classic Arrow-Debreu model, the existence of money is not accommodated. However, using trading post market segmentation and requiring budget balance in each pair-wise transaction the model can converge to monetary equilibrium. Uniqueness of the common medium of exchange (commodity money)...

This paper demonstrates the existence of pure strategy stationary Markov equilibrium in a class of dynamic stochastic games. Our main result implies the existence of behavior strategy stationary Markov equilibrium in any stochastic games in which the sets of actions are compact, the set of...

We study a class of repeated games with Markovian private information and characterize optimal equilibria as players become arbitrarily patient.  We show that seemingly non-cooperative action may occur in equilibrium and serve as signals of changes in private information. Players forgive such...

Motivated by recent developments in applied dynamic analysis, this paper presents new sufficient conditions for the existence of a Markov perfect equilibrium in dynamic stochastic games. The main results imply the existence of a Markov perfect equilibrium provided the sets of actions are...

This paper studies the problem of self governance in a model in which information flows are governed by the community structure. In each round of an infinitely repeated game, an agent and an investor, who is selected from a finite set of investors, play a trust game. Investors receive...

We study repeated Bayesian n-player games in which the players' privately known types evolve according an irreducible Markov chain. Our main result shows that, with communication, any Pareto-efficient payoff vector above a stationary minmax value can be approximated arbitrarily closely in a...

This paper studies long term relationships, modeled as repeated games, with restricted feedback. Players condition current play on summary statistics of past play rather than the entire history, as may be the case in online markets. Our state strategy equilibrium framework allows for arbitrary...