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Coordination under global random interaction and local imitation

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  • Abhimanyu Khan

Abstract

Individuals are randomly matched to play a $$2\times 2$$ 2 × 2 coordination game where the Pareto efficient and risk dominant equilibria differ. Players choose strategies by imitating the strategy of the most successful individual they observe. So, while individuals interact globally, their observation and hence imitation, as determined by their social network, may be local. When all individuals observe each other, the most successful individual in the entire population is imitated; here, in the stochastically stable state, the population coordinates on the Pareto-efficient outcome. While this outcome is always stochastically stable, even when observability is incomplete, the state where everyone plays the action of the risk-dominant equilibrium may be stochastically stable as well. Reasonably tight sufficient conditions for unique stochastic stability of the state where all coordinate on the Pareto-efficient equilibrium strategy include each individual observing at least four other individuals or when each individual observes the same number of other individuals. These properties are readily generalisable to larger $$m\times m$$ m × m coordination games where the coordination outcomes can be Pareto-ranked. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Abhimanyu Khan, 2014. "Coordination under global random interaction and local imitation," International Journal of Game Theory, Springer;Game Theory Society, vol. 43(4), pages 721-745, November.
  • Handle: RePEc:spr:jogath:v:43:y:2014:i:4:p:721-745
    DOI: 10.1007/s00182-013-0399-1
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    Cited by:

    1. Cabo, Francisco & García-González, Ana, 2020. "Interaction and imitation with heterogeneous agents: A misleading evolutionary equilibrium," Journal of Economic Behavior & Organization, Elsevier, vol. 179(C), pages 152-174.
    2. Antonio Cabrales & Esther Hauk, 2022. "Norms and the Evolution of Leaders' Followership," CESifo Working Paper Series 9845, CESifo.
    3. Fei Shi, 2015. "Long-run technology choice with endogenous local capacity," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 59(2), pages 377-399, June.
    4. Zhiwei Cui, 2019. "Matching, Imitation, and Coordination in Networks," Dynamic Games and Applications, Springer, vol. 9(1), pages 47-67, March.
    5. Abhimanyu Khan & Ronald Peeters & Frank Thuijsman & Philippe Uyttendaele, 2016. "Network Characteristics Enabling Efficient Coordination: A Simulation Study," Dynamic Games and Applications, Springer, vol. 6(4), pages 495-519, December.
    6. Nicola Campigotto, 2021. "Pairwise imitation and evolution of the social contract," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1333-1354, September.
    7. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
    8. Cui, Zhiwei & Wang, Rui, 2016. "Collaboration in networks with randomly chosen agents," Journal of Economic Behavior & Organization, Elsevier, vol. 129(C), pages 129-141.
    9. Eugenio Vicario, 2021. "Imitation and Local Interactions: Long Run Equilibrium Selection," Games, MDPI, vol. 12(2), pages 1-19, April.

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    More about this item

    Keywords

    Coordination games; Random matching; Local imitation; Stochastic stability; C73; D03;
    All these keywords.

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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