A partial folk theorem for games with private learning
AbstractThe payoff matrix of a finite stage game is realized randomly, and then the stage game is repeated infinitely. The distribution over states of the world (a state corresponds to a payoff matrix) is commonly known, but players do not observe nature’s choice. Over time, they can learn the state in two ways. After each round, each player observes his own realized payoff (which may be stochastic, conditional on the state), and he observes a noisy public signal of the state (whose informativeness may vary with the actions chosen). Actions are perfectly observable. The result is that for any function that maps each state to a payoff vector that is feasible and individually rational in that state, there is a sequential equilibrium in which patient players learn the realized state with arbitrary precision and achieve a payoff close to the one specified for that state. That result extends to the case where there is no public signal, but instead players receive very closely correlated private signals of the vector of realized payoffs.
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Bibliographic InfoArticle provided by Econometric Society in its journal Theoretical Economics.
Volume (Year): 7 (2012)
Issue (Month): 2 (May)
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Web page: http://econtheory.org
Repeated games; learning; folk theorem;
Other versions of this item:
- Thomas E. Wiseman, 2011. "A Partial Folk Theorem for Games with Private Learning," 2011 Meeting Papers 181, Society for Economic Dynamics.
- C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
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.:
- O. Gossner & N. Vieille, 2000.
"Strategic Learning in Games with Symmetric Information,"
THEMA Working Papers
2000-27, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
- Gossner, Olivier & Vieille, Nicolas, 2003. "Strategic learning in games with symmetric information," Games and Economic Behavior, Elsevier, vol. 42(1), pages 25-47, January.
- GOSSNER, Olivier & VIEILLE, Nicolas, 1998. "Strategic learning in games with symmetric information," CORE Discussion Papers 1998023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Atakan, Alp E. & Ekmekci, Mehmet, 2013.
"A two-sided reputation result with long-run players,"
Journal of Economic Theory,
Elsevier, vol. 148(1), pages 376-392.
- Mehmet Ekmekci & Alp Atakan, 2009. "A two Sided Reputation Result with Long Run Players," Discussion Papers 1510, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Robert J. Aumann, 1995. "Repeated Games with Incomplete Information," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262011476, June.
- Lovo, Stefano & Tomala, Tristan & Hörner, Johannes, 2009. "Belief-free equilibria in games with incomplete information: characterization and existence," Les Cahiers de Recherche 921, HEC Paris.
- Sonja Brangewitz & Gael Giraud, 2011. "Learning in Infinite Horizon Strategic Market Games with Collateral and Incomplete Information," Working Papers 456, Bielefeld University, Center for Mathematical Economics.
- Yuichi Yamamoto, 2013. "Individual Learning and Cooperation in Noisy Repeated Games," PIER Working Paper Archive 13-038, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Francoise Forges & Antoine Salomon, 2013. "Bayesian Repeated Games," Working Papers hal-00803919, HAL.
- Yuichi Yamamoto, 2012. "Individual Learning and Cooperation in Noisy Repeated Games," PIER Working Paper Archive 12-044, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
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