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Bayesian learning in repeated games of incomplete information

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  • John H. Nachbar

    ()
    (Department of Economics, Washington University, One Brookings Drive, St. Louis, MO 63130, USA)

Abstract

In Nachbar [20] and, more definitively, Nachbar [22], I argued that, for a large class of discounted infinitely repeated games of complete information (i.e. stage game payoff functions are common knowledge), it is impossible to construct a Bayesian learning theory in which player beliefs are simultaneously weakly cautious, symmetric, and consistent. The present paper establishes a similar impossibility theorem for repeated games of incomplete information, that is, for repeated games in which stage game payoff functions are private information.

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Bibliographic Info

Article provided by Springer in its journal Social Choice and Welfare.

Volume (Year): 18 (2001)
Issue (Month): 2 ()
Pages: 303-326

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Handle: RePEc:spr:sochwe:v:18:y:2001:i:2:p:303-326

Note: Received: 15 October 1997/Accepted: 17 March 1999
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Cited by:
  1. Peyton Young, 2002. "Learning Hypothesis Testing and Nash Equilibrium," Economics Working Paper Archive 474, The Johns Hopkins University,Department of Economics.
  2. John H. Nachbar, 2005. "Beliefs in Repeated Games," Econometrica, Econometric Society, vol. 73(2), pages 459-480, 03.
  3. Young, H. Peyton, 2002. "On the limits to rational learning," European Economic Review, Elsevier, vol. 46(4-5), pages 791-799, May.
  4. Dean P. Foster & H. Peyton Young, 2001. "On the Impossibility of Predicting the Behavior of Rational Agents," Working Papers 01-08-039, Santa Fe Institute.

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