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Punishment strategies in repeated games: Evidence from experimental markets

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  • Wright, Julian

Abstract

An experiment is designed to provide a snapshot of the strategies used by players in a repeated price competition game with a random continuation rule. One hundred pairs of subjects played the game over the Internet, with subjects having a few days to make their decisions in each round. Occasionally subjects are asked to enter one-period-ahead pricing strategies instead of prices. According to the elicited strategies, between 90% and 95% of subjects punish less harshly (in their initial response to a deviation) than implied by the grim trigger strategy, and do so in a way that depends on the size of the other subjectʼs deviation. Future earnings are highest for subjects adopting the tit-for-tat strategy, even after controlling for a subjectʼs past earnings. Punishment strategies are generally softer and more graduated than implied by a grim trigger strategy, and do better as a result.

Suggested Citation

  • Wright, Julian, 2013. "Punishment strategies in repeated games: Evidence from experimental markets," Games and Economic Behavior, Elsevier, vol. 82(C), pages 91-102.
    • Handle: RePEc:eee:gamebe:v:82:y:2013:i:c:p:91-102
    DOI: 10.1016/j.geb.2013.06.012
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    Cited by:

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    2. Werner, Tobias, 2021. "Algorithmic and human collusion," DICE Discussion Papers 372, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    3. Correia-da-Silva João & Pinho Joana & Vasconcelos Hélder, 2015. "How Should Cartels React to Entry Triggered by Demand Growth?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 15(1), pages 209-255, January.
    4. Lijia Tan & Lijia Wei, 2014. "Special Section: Experiments on Learning, Methods, and Voting," Pacific Economic Review, Wiley Blackwell, vol. 19(3), pages 313-331, August.
    5. Stephen Martin, 2018. "Behavioral antitrust," Chapters, in: Victor J. Tremblay & Elizabeth Schroeder & Carol Horton Tremblay (ed.), Handbook of Behavioral Industrial Organization, chapter 15, pages 404-454, Edward Elgar Publishing.
    6. Schimit, P.H.T. & Santos, B.O. & Soares, C.A., 2015. "Evolution of cooperation in Axelrod tournament using cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 204-217.

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    More about this item

    Keywords

    Experiment; Cooperation; Tit-for-tat; Grim trigger strategy;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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