Bayesian learning in repeated games of incomplete information

John Nachbar

Social Choice and Welfare, 2001, vol. 18, issue 2, 303-326

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.

Date: 2001-04-17
Note: Received: 15 October 1997/Accepted: 17 March 1999
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