A Foundation for Markov Equilibria with Finite Social Memory
AbstractWe study stochastic games with an infinite horizon and sequential moves played by an arbitrary number of players. We assume that social memory is finite---every player, except possibly one, is finitely lived and cannot observe events that are sufficiently far back in the past. This class of games includes games between a long-run player and a sequence of short-run players and games with overlapping generations of players. Indeed, any stochastic game with infinitely lived players can be reinterpreted as one with finitely lived players: Each finitely-lived player is replaced by a successor, and receives the value of the successor's payoff. This value may arise from altruism, but the player also receives such a value if he can “sell” his position in a competitive market. In both cases, his objective will be to maximize infinite horizon payoffs, though his information on past events will be limited. An equilibrium is purifiable if close-by behavior is consistent with equilibrium when agents' payoffs in each period are perturbed additively and independently. We show that only Markov equilibria are purifiable when social memory is finite. Thus if a game has at most one long-run player, all purifiable equilibria are Markov.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Penn Institute for Economic Research, Department of Economics, University of Pennsylvania in its series PIER Working Paper Archive with number 12-003.
Length: 28 pages
Date of creation: 31 Jan 2012
Date of revision:
Purification; Markov perfect equilibrium; dynamic games;
Find related papers by JEL classification:
- C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
- C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- George Mailath & Wojciech Olszewski, 2008.
"Folk theorems with Bounded Recall under(Almost) Perfect Monitoring,"
1462, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Mailath, George J. & Olszewski, Wojciech, 2011. "Folk theorems with bounded recall under (almost) perfect monitoring," Games and Economic Behavior, Elsevier, vol. 71(1), pages 174-192, January.
- George J. Mailath & Wojciech Olszewski, 2008. "Folk Theorems with Bounded Recall under (Almost) Perfect Monitoring," PIER Working Paper Archive 08-019, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Eaton, Jonathan & Engers, Maxim, 1990. "Intertemporal Price Competition," Econometrica, Econometric Society, vol. 58(3), pages 637-59, May.
- Doraszelski, Ulrich & Escobar, Juan, 2008.
"A Theory of Regular Markov Perfect Equilibria in Dynamic Stochastic Games: Genericity, Stability, and Purification,"
CEPR Discussion Papers
6805, C.E.P.R. Discussion Papers.
- Doraszelski, Ulrich & Escobar, Juan, 2010. "A theory of regular Markov perfect equilibria in dynamic stochastic games: genericity, stability, and purification," Theoretical Economics, Econometric Society, vol. 5(3), September.
- Juan Escobar & Ulrich Doraszelski, 2008. "A Theory of Regular Markov Perfect Equilibria\\in Dynamic Stochastic Games: Genericity, Stability, and Purification," 2008 Meeting Papers 453, Society for Economic Dynamics.
- Mas-Colell, Andreu & Whinston, Michael D. & Green, Jerry R., 1995. "Microeconomic Theory," OUP Catalogue, Oxford University Press, number 9780195102680, September.
- Liu, Qingmin & Skrzypacz, Andrzej, 2009. "Limited Records and Reputation," Research Papers 2030, Stanford University, Graduate School of Business.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dolly Guarini).
If references are entirely missing, you can add them using this form.