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Heterogeneity in preferences and behavior in threshold models

Author

Listed:
  • Philip R Neary

    (Royal Holloway University of London, UK)

  • Jonathan Newton

Abstract

A coordination game is repeatedly played on a graph by players (vertices) who have heterogeneous cardinal preferences and whose strategy choice is governed by the individualistic asynchronous logit dynamic. The idea of potential driven autonomy of sets of players is used to derive results on the possibility of heterogeneous preferences leading to heterogeneous behavior. In particular, a class of graphs is identified such that for large enough graphs in this class, diversity in ordinal preferences will nearly always lead to heterogeneity in behavior, regardless of the cardinal strength of the preferences. These results have implications for network design problems, such as when a social planner wishes to induce homogeneous/heterogeneous behavior in a population.

Suggested Citation

  • Philip R Neary & Jonathan Newton, 2017. "Heterogeneity in preferences and behavior in threshold models," The Journal of Mechanism and Institution Design, Society for the Promotion of Mechanism and Institution Design, University of York, vol. 2(1), pages 141-159, December.
    • Handle: RePEc:jmi:articl:jmi-v2i1a5
    DOI: 10.22574/jmid.2017.12.005
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Sawa, Ryoji & Wu, Jiabin, 2023. "Statistical inference in evolutionary dynamics," Games and Economic Behavior, Elsevier, vol. 137(C), pages 294-316.
    2. Heller, Yuval & Kuzmics, Christoph, 2020. "Communication, Renegotiation and Coordination with Private Values (Extended Version)," MPRA Paper 102926, University Library of Munich, Germany, revised 26 Jul 2021.
    3. Heller, Yuval & Kuzmics, Christoph, 2024. "Communication, renegotiation and coordination with private values," Games and Economic Behavior, Elsevier, vol. 143(C), pages 51-76.
    4. Jiabin Wu, 2019. "Social connections and cultural heterogeneity," Journal of Evolutionary Economics, Springer, vol. 29(2), pages 779-798, April.
    5. 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).
    6. Roberto Rozzi, 2021. "Competing Conventions with Costly Information Acquisition," Games, MDPI, vol. 12(3), pages 1-29, June.
    7. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
    8. John Lynham & Philip R. Neary, 2024. "Tiebout sorting in online communities," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 73(3), pages 1149-1174, October.
    9. Naono, Miharu, 2022. "Cost heterogeneity and the persistence of bilingualism," Games and Economic Behavior, Elsevier, vol. 136(C), pages 325-339.
    10. Argyrios Deligkas & Eduard Eiben & Gregory Gutin & Philip R. Neary & Anders Yeo, 2023. "Some coordination problems are harder than others," Papers 2311.03195, arXiv.org, revised Nov 2023.

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    More about this item

    Keywords

    Heterogeneity; potential; networks.;
    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
    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact

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