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Punishment and Cooperation in Stochastic Social Dilemmas

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  • Erte Xiao
  • Howard Kunreuther

Abstract

Previous findings on punishment have focused on environments in which the outcomes are known with certainty. In this paper, we conduct experiments to investigate how punishment affects cooperation in a two-person stochastic prisoner's dilemma environment where each person can decide whether or not to cooperate, and the outcomes of alternative strategies are specified probabilistically under a transparent information condition. In particular, we study two types of punishment mechanisms: 1) an unrestricted punishment mechanism: both persons can punish; and 2) a restricted punishment mechanism: only cooperators can punish non-cooperators. We show that the restricted punishment mechanism is more effective in promoting cooperative behavior than the unrestricted one in a deterministic social dilemma. More importantly, the restricted type is less effective in an environment where the outcomes are stochastic than when they are known with certainty. Our data suggest that one explanation is that non-cooperative behavior is less likely to be punished when there is outcome uncertainty. Our findings provide useful information for designing efficient incentive mechanisms to induce cooperation in a stochastic social dilemma environment.

Suggested Citation

  • Erte Xiao & Howard Kunreuther, 2012. "Punishment and Cooperation in Stochastic Social Dilemmas," NBER Working Papers 18458, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:18458
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    Cited by:

    1. Faillo, Marco & Grieco, Daniela & Zarri, Luca, 2013. "Legitimate punishment, feedback, and the enforcement of cooperation," Games and Economic Behavior, Elsevier, vol. 77(1), pages 271-283.
    2. Li, Lingfang (Ivy) & Xiao, Erte, 2010. "Money Talks? An Experimental Study of Rebate in Reputation System Design," MPRA Paper 22401, University Library of Munich, Germany.
    3. Gaudeul, Alexia & Crosetto, Paolo & Riener, Gerhard, 2017. "Better stuck together or free to go? Of the stability of cooperation when individuals have outside options," Journal of Economic Psychology, Elsevier, vol. 59(C), pages 99-112.
    4. Fangfang Tan & Erte Xiao, 2014. "Third-Party Punishment: Retribution or Deterrence?," Working Papers tax-mpg-rps-2014-05, Max Planck Institute for Tax Law and Public Finance.
    5. Jared Rubin & Roman Sheremeta, 2016. "Principal–Agent Settings with Random Shocks," Management Science, INFORMS, vol. 62(4), pages 985-999, April.
    6. Paolo Crosetto & Alexia Gaudeul & Gerhard Riener, 2012. "Partnerships, Imperfect Monitoring and Outside Options: Theory and Experimental Evidence," Jena Economic Research Papers 2012-052, Friedrich-Schiller-University Jena.
    7. Timothy Cason & Lata Gangadharan, 2015. "Promoting cooperation in nonlinear social dilemmas through peer punishment," Experimental Economics, Springer;Economic Science Association, vol. 18(1), pages 66-88, March.
    8. Vesely, Stepan & Wengström, Erik, 2017. "Risk and Cooperation: Experimental Evidence from Stochastic Public Good Games," Working Papers 2017:3, Lund University, Department of Economics.
    9. Paolo Crosetto & Alexia Gaudeul & Gerhard Riener, 2012. "Partnerships, Imperfect Monitoring and Outside Options: Theory and Experimental Evidence," Jena Economic Research Papers 2012-052, Friedrich-Schiller-University Jena.
    10. Daniela Grieco & Marco Faillo & Luca Zarri, 2013. "Top Contributors as Punishers," Working Papers 24/2013, University of Verona, Department of Economics.
    11. Tan, Fangfang & Xiao, Erte, 2012. "Peer punishment with third-party approval in a social dilemma game," Economics Letters, Elsevier, vol. 117(3), pages 589-591.
    12. repec:spr:jesaex:v:3:y:2017:i:2:d:10.1007_s40881-017-0041-2 is not listed on IDEAS

    More about this item

    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
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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