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A Foundation for Markoiv Equilibria in Infinite Horizon Perfect Information Games

V. Bhaskar
University College London

George J. Mailath
University of Pennsylvania - Department of Economics

Stephen Morris
Princeton University - Department of Economics


August 5, 2009

PIER Working Paper No. 09-029

Abstract:     
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 equilibria. An equilibrium is purifiable if close by behavior is consistent with equilibrium when agents' payoffs at each node are perturbed additively and independently. An equilibrium has bounded recall if there exists K such that at most one player's strategy depends on what happened more than K periods earlier. We show that only Markov equilibria have bounded memory and are purifiable. Thus if a game has at most one long-run player, all purifiable equilibria are Markov.

Keywords: Markov, bounded recall, purification

JEL Classifications: C72, C73

Working Paper Series

Date posted: August 24, 2009 ; Last revised: September 21, 2009

Suggested Citation

Bhaskar, V., Mailath, George J. and Morris, Stephen Edward, A Foundation for Markoiv Equilibria in Infinite Horizon Perfect Information Games (August 5, 2009). PIER Working Paper No. 09-029. Available at SSRN: http://ssrn.com/abstract=1460780


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Contact Information

George J. Mailath (Contact Author)
University of Pennsylvania - Department of Economics ( email )
3718 Locust Walk
Philadelphia, PA 19104
United States
215-898-7749 (Phone)
215-573-2057 (Fax)
HOME PAGE: http://www.ssc.upenn.edu/~gmailath
V. Bhaskar
University College London ( email )
Gower Street
London WC1E 6BT United Kingdom
Stephen Edward Morris
Princeton University - Department of Economics ( email )
Princeton, NJ 08544-1021
United States
Feedback to SSRN (Beta)


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