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Coalitional stochastic stability

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  • Newton, Jonathan

Abstract

This paper takes the idea of coalitional behavior – groups of people occasionally acting together to their mutual benefit – and incorporates it into the framework of evolutionary game theory that underpins the social learning literature. An equilibrium selection criterion is defined which we call coalitional stochastic stability (CSS). This differs from existing work on stochastic stability in that profitable coalitional deviations are given greater importance than unprofitable single player deviations. A general characterization of CSS is given together with more detailed characterizations for specific classes of games. Applications include contracting, asymmetric social norms and collusive price setting, the latter of which is shown in some circumstances to facilitate competitive outcomes.

Suggested Citation

  • Newton, Jonathan, 2012. "Coalitional stochastic stability," Games and Economic Behavior, Elsevier, vol. 75(2), pages 842-854.
  • Handle: RePEc:eee:gamebe:v:75:y:2012:i:2:p:842-854
    DOI: 10.1016/j.geb.2012.02.014
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    References listed on IDEAS

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    Cited by:

    1. Mäs, Michael & Nax, Heinrich H., 2016. "A behavioral study of “noise” in coordination games," Journal of Economic Theory, Elsevier, vol. 162(C), pages 195-208.
    2. Rusch, Hannes, 2019. "The evolution of collaboration in symmetric 2×2-games with imperfect recognition of types," Games and Economic Behavior, Elsevier, vol. 114(C), pages 118-127.
    3. Mäs, Michael & Nax, Heinrich H., 2016. "A behavioral study of “noise” in coordination games," LSE Research Online Documents on Economics 65422, London School of Economics and Political Science, LSE Library.
    4. Newton, Jonathan, 2015. "Stochastic stability on general state spaces," Journal of Mathematical Economics, Elsevier, vol. 58(C), pages 46-60.
    5. Ennio Bilancini & Leonardo Boncinelli, 2020. "The evolution of conventions under condition-dependent mistakes," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 69(2), pages 497-521, March.
    6. repec:syd:wpaper:2123/9993 is not listed on IDEAS
    7. Sung-Ha Hwang & Jonathan Newton, 2017. "Payoff-dependent dynamics and coordination games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 64(3), pages 589-604, October.
    8. Klaus, Bettina & Newton, Jonathan, 2016. "Stochastic stability in assignment problems," Journal of Mathematical Economics, Elsevier, vol. 62(C), pages 62-74.
    9. Hwang, Sung-Ha & Lim, Wooyoung & Neary, Philip & Newton, Jonathan, 2018. "Conventional contracts, intentional behavior and logit choice: Equality without symmetry," Games and Economic Behavior, Elsevier, vol. 110(C), pages 273-294.
    10. Newton, Jonathan & Angus, Simon D., 2015. "Coalitions, tipping points and the speed of evolution," Journal of Economic Theory, Elsevier, vol. 157(C), pages 172-187.
    11. Newton, Jonathan, 2017. "Shared intentions: The evolution of collaboration," Games and Economic Behavior, Elsevier, vol. 104(C), pages 517-534.
    12. Newton, Jonathan & Wait, Andrew & Angus, Simon D., 2019. "Watercooler chat, organizational structure and corporate culture," Games and Economic Behavior, Elsevier, vol. 118(C), pages 354-365.
    13. Sawa, Ryoji, 2019. "Stochastic stability under logit choice in coalitional bargaining problems," Games and Economic Behavior, Elsevier, vol. 113(C), pages 633-650.
    14. Newton, Jonathan & Sercombe, Damian, 2020. "Agency, potential and contagion," Games and Economic Behavior, Elsevier, vol. 119(C), pages 79-97.
    15. Jonathan Newton, 2019. "Agency Equilibrium," Games, MDPI, Open Access Journal, vol. 10(1), pages 1-15, March.
    16. Vincent Boucher, 2017. "The Estimation of Network Formation Games with Positive Spillovers," Cahiers de recherche 1710, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    17. Sawa, Ryoji, 2014. "Coalitional stochastic stability in games, networks and markets," Games and Economic Behavior, Elsevier, vol. 88(C), pages 90-111.
    18. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, Open Access Journal, vol. 9(2), pages 1-67, May.
    19. Hannes Rusch, 2017. "The Evolution of Collaboration in Symmetric 2x2-Games with Imperfect Recognition of Types," MAGKS Papers on Economics 201739, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    20. Boucher, Vincent, 2020. "Equilibrium homophily in networks," European Economic Review, Elsevier, vol. 123(C).
    21. Akira Okada & Ryoji Sawa, 2016. "An evolutionary approach to social choice problems with q-quota rules," KIER Working Papers 936, Kyoto University, Institute of Economic Research.
    22. Leung, Michael P., 2019. "A weak law for moments of pairwise stable networks," Journal of Econometrics, Elsevier, vol. 210(2), pages 310-326.
    23. Lim, Wooyoung & Neary, Philip R., 2016. "An experimental investigation of stochastic adjustment dynamics," Games and Economic Behavior, Elsevier, vol. 100(C), pages 208-219.

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    More about this item

    Keywords

    Stochastic stability; Learning; Coalition; Lexicographic; Contract;
    All these keywords.

    JEL classification:

    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • 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

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