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A behavioral study of “noise” in coordination games

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  • Mäs, Michael
  • Nax, Heinrich H.

Abstract

‘Noise’ in this study, in the sense of evolutionary game theory, refers to deviations from prevailing behavioral rules. Analyzing data from a laboratory experiment on coordination in networks, we tested ‘what kind of noise’ is supported by behavioral evidence. This empirical analysis complements a growing theoretical literature on ‘how noise matters’ for equilibrium selection. We find that the vast majority of decisions (96%96%) constitute myopic best responses, but deviations continue to occur with probabilities that are sensitive to their costs, that is, less frequent when implying larger payoff losses relative to the myopic best response. In addition, deviation rates vary with patterns of realized payoffs that are related to trial-and-error behavior. While there is little evidence that deviations are clustered in time or space, there is evidence of individual heterogeneity.

Suggested Citation

  • 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.
  • Handle: RePEc:ehl:lserod:65422
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    File URL: http://eprints.lse.ac.uk/65422/
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    Cited by:

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    6. Sawa, Ryoji, 2019. "Stochastic stability under logit choice in coalitional bargaining problems," Games and Economic Behavior, Elsevier, vol. 113(C), pages 633-650.
    7. Schüssler, Katharina & Schüssler, Michael & Mühlbauer, Daniel, 2018. "Individual Differences and Contribution Sequences in Threshold Public Goods," Rationality and Competition Discussion Paper Series 88, CRC TRR 190 Rationality and Competition.
    8. Xiaochao Wei & Yanfei Zhang & Qi Liao & Guihua Nie, 2022. "Multi-Agent Simulation of Product Diffusion in Online Social Networks from the Perspective of Overconfidence and Network Effects," Sustainability, MDPI, vol. 14(11), pages 1-18, May.
    9. 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).
    10. 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).
    11. Konstantin Avrachenkov & Vivek S. Borkar, 2019. "Metastability in Stochastic Replicator Dynamics," Dynamic Games and Applications, Springer, vol. 9(2), pages 366-390, June.
    12. Sawa, Ryoji & Wu, Jiabin, 2018. "Reference-dependent preferences, super-dominance and stochastic stability," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 96-104.
    13. Angelovski, Andrej & Di Cagno, Daniela & Güth, Werner & Marazzi, Francesca & Panaccione, Luca, 2018. "Does heterogeneity spoil the basket? The role of productivity and feedback information on public good provision," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 77(C), pages 40-49.
    14. H Peyton Young & Sam Jindani, 2020. "The dynamics of costly social norms," Economics Series Working Papers 883, University of Oxford, Department of Economics.
    15. Sawa, Ryoji & Wu, Jiabin, 2018. "Prospect dynamics and loss dominance," Games and Economic Behavior, Elsevier, vol. 112(C), pages 98-124.
    16. Grech, Philip D. & Nax, Heinrich H., 2020. "Rational altruism? On preference estimation and dictator game experiments," Games and Economic Behavior, Elsevier, vol. 119(C), pages 309-338.
    17. Goryunov, Maxim & Rigos, Alexandros, 2022. "Discontinuous and continuous stochastic choice and coordination in the lab," Journal of Economic Theory, Elsevier, vol. 206(C).
    18. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
    19. Irene Crimaldi & Pierre-Yves Louis & Ida Minelli, 2020. "Interacting non-linear reinforced stochastic processes: Synchronization and no-synchronization," Working Papers hal-02910341, HAL.
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    21. 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

    behavioral game theory; discrete choice; evolution; learning; logit response; stochastic stability; trial-and-error;
    All these keywords.

    JEL classification:

    • 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
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior

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