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Cooperation and Punishment

Author

Listed:
  • Jonathan P. Thomas

    (University of St. Andrews)

  • Robert Evans

    (University of Cambridge)

Abstract

We show that, in repeated common interest games without discounting, strong `perturbation implies efficiency' results require that the perturbations must include strategies which are `draconian' in the sense that they are prepared to punish to the maximum extent possible. Moreover, there is a draconian strategy whose presence in the perturbations guarantees that any equilibrium is efficient. We also argue that the results of Anderlini and Sabourian (1995) using perturbation strategies which are cooperative (and hence non-draconian) are not due to computability per se but to the further restrictions they impose on allowable beliefs.

Suggested Citation

  • Jonathan P. Thomas & Robert Evans, 2000. "Cooperation and Punishment," Game Theory and Information 0004002, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpga:0004002
    Note: Type of Document - Acrobat PDF; prepared on IBM PC; pages: 22 ; figures: included. pdf file, prepared from sci word
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    References listed on IDEAS

    as
    1. Aumann, Robert J. & Sorin, Sylvain, 1989. "Cooperation and bounded recall," Games and Economic Behavior, Elsevier, vol. 1(1), pages 5-39, March.
    2. Sorin, Sylvain, 1999. "Merging, Reputation, and Repeated Games with Incomplete Information," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 274-308, October.
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    Cited by:

    1. Kumabe, Masahiro & Mihara, H. Reiju, 2008. "Computability of simple games: A characterization and application to the core," Journal of Mathematical Economics, Elsevier, vol. 44(3-4), pages 348-366, February.
    2. Anderson, Christopher M. & Putterman, Louis, 2006. "Do non-strategic sanctions obey the law of demand? The demand for punishment in the voluntary contribution mechanism," Games and Economic Behavior, Elsevier, vol. 54(1), pages 1-24, January.
    3. Herbert Gintis, 2000. "Strong Reciprocity and Human Sociality," UMASS Amherst Economics Working Papers 2000-02, University of Massachusetts Amherst, Department of Economics.
    4. Anderlini, Luca & Sabourian, Hamid, 2001. "Cooperation and computability in n-player games," Mathematical Social Sciences, Elsevier, vol. 42(2), pages 99-137, September.
    5. Bochet, Olivier & Page, Talbot & Putterman, Louis, 2006. "Communication and punishment in voluntary contribution experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 60(1), pages 11-26, May.
    6. Dan Protopopescu, 2009. "Dynamic Stackelberg Game with Risk-Averse Players: Optimal Risk-Sharing under Asymmetric Information," UFAE and IAE Working Papers 797.09, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    7. Mailath, George J. & Samuelson, Larry, 2015. "Reputations in Repeated Games," Handbook of Game Theory with Economic Applications,, Elsevier.
    8. Samuel Bowles & Herbert Gintis, 2002. "Social Capital and Community Governance," Economic Journal, Royal Economic Society, vol. 112(483), pages 419-436, November.
    9. Wolitzky, Alexander, 2011. "Indeterminacy of reputation effects in repeated games with contracts," Games and Economic Behavior, Elsevier, vol. 73(2), pages 595-607.
    10. Chun Lei Yang & Ching Syang Jack Yue, 2004. "The Rise of Cooperation in Correlated Matching Prisoners Dilemma: An Experiment," Levine's Bibliography 122247000000000097, UCLA Department of Economics.

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    More about this item

    Keywords

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    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation

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