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Learning to Forgive

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  • Thomas Norman

Abstract

The Folk Theorem for infinitely repeated games offers an embarrassment of riches; nowhere is equilibrium multiplicity more acute. This paper selects amongst these equilibria in the following sense. If players learn to play an infinitely repeated game using classical hypothesis testing, it is known that their strategies almost always approximate equilibria of the repeated game. It is shown here that if, in addition, they are sufficiently conservative in adopting their hypotheses, then almost all of the time is spent approximating an efficient subset of equilibria that share a forgiving property. This result provides theoretical justification for the general sense amongst practitioners that efficiency is focal in such games.

Suggested Citation

  • Thomas Norman, 2006. "Learning to Forgive," Economics Series Working Papers 296, University of Oxford, Department of Economics.
    • Handle: RePEc:oxf:wpaper:296
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    File URL: https://ora.ox.ac.uk/objects/uuid:2fbc90ad-f296-43e4-9912-05ea689bd65c
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    References listed on IDEAS

    as
    1. Foster, Dean P. & Young, H. Peyton, 2003. "Learning, hypothesis testing, and Nash equilibrium," Games and Economic Behavior, Elsevier, vol. 45(1), pages 73-96, October.
    2. Fudenberg, Drew & Maskin, Eric, 1991. "On the dispensability of public randomization in discounted repeated games," Journal of Economic Theory, Elsevier, vol. 53(2), pages 428-438, April.
    3. Fudenberg, Drew & Maskin, Eric, 1990. "Evolution and Cooperation in Noisy Repeated Games," American Economic Review, American Economic Association, vol. 80(2), pages 274-279, May.
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    More about this item

    Keywords

    Repeated Games; Folk Theorem; Learning; Hypothesis Testing; Equilibrium Selection;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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