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An experimental investigation of stochastic adjustment dynamics

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  • Lim, Wooyoung
  • Neary, Philip R.

Abstract

This paper describes an experiment designed to test which, if any, stochastic adjustment dynamic most accurately captures the behaviour of a large population. The setting is a large population coordination game, the Language Game of Neary (2012), in which actions are strategic complements and two homogeneous groups have differing preferences over equilibria. We find that subject behaviour is highly consistent with the myopic best-response learning rule with deviations from this rule that are (i) dependent on the myopic best-response payoff but not on the deviation payoff, and (ii) directed in the sense of being group-dependent. We also find a time trend to deviations, with the magnitude tapering off as time progresses. This is in contrast to much of the theoretical literature that supposes a variety of other specifications of learning rules and both time-independent and payoff-dependent explanations for deviations.

Suggested Citation

  • Lim, Wooyoung & Neary, Philip R., 2016. "An experimental investigation of stochastic adjustment dynamics," Games and Economic Behavior, Elsevier, vol. 100(C), pages 208-219.
  • Handle: RePEc:eee:gamebe:v:100:y:2016:i:c:p:208-219
    DOI: 10.1016/j.geb.2016.09.010
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    Cited by:

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    5. Hwang, Sung-Ha & Rey-Bellet, Luc, 2021. "Positive feedback in coordination games: Stochastic evolutionary dynamics and the logit choice rule," Games and Economic Behavior, Elsevier, vol. 126(C), pages 355-373.
    6. 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.
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    9. Ennio Bilancini & Leonardo Boncinelli, 2018. "Social coordination with locally observable types," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(4), pages 975-1009, June.
    10. Stephenson, Daniel, 2019. "Coordination and evolutionary dynamics: When are evolutionary models reliable?," Games and Economic Behavior, Elsevier, vol. 113(C), pages 381-395.
    11. Sawa, Ryoji, 2021. "A stochastic stability analysis with observation errors in normal form games," Games and Economic Behavior, Elsevier, vol. 129(C), pages 570-589.
    12. Benndorf, Volker & Martínez-Martínez, Ismael & Normann, Hans-Theo, 2021. "Games with coupled populations: An experiment in continuous time," Journal of Economic Theory, Elsevier, vol. 195(C).
    13. Bilancini, Ennio & Boncinelli, Leonardo & Nax, Heinrich H., 2021. "What noise matters? Experimental evidence for stochastic deviations in social norms," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).
    14. Roberto Rozzi, 2021. "Competing Conventions with Costly Information Acquisition," Games, MDPI, vol. 12(3), pages 1-29, June.
    15. Sawa, Ryoji, 2021. "A prospect theory Nash bargaining solution and its stochastic stability," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 692-711.
    16. Sawa, Ryoji & Wu, Jiabin, 2018. "Reference-dependent preferences, super-dominance and stochastic stability," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 96-104.
    17. Sawa, Ryoji & Wu, Jiabin, 2018. "Prospect dynamics and loss dominance," Games and Economic Behavior, Elsevier, vol. 112(C), pages 98-124.
    18. Bilancini, Ennio & Boncinelli, Leonardo & Newton, Jonathan, 2020. "Evolution and Rawlsian social choice in matching," Games and Economic Behavior, Elsevier, vol. 123(C), pages 68-80.
    19. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
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    21. Goryunov, Maxim & Rigos, Alexandros, 2020. "Discontinuous and Continuous Stochastic Choice and Coordination in the Lab," Working Papers 2020:17, Lund University, Department of Economics, revised 15 Jun 2022.

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    More about this item

    Keywords

    Stochastic adjustment dynamics; Experiment; The Language Game; Evolutionary game theory;
    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
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior

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