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Coordination under global random interaction and local imitation

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  • Khan, A.

    (General Economics 0 (Onderwijs))

Abstract

We study stochastically stable behaviour in 2 x 2 coordination games where the risk-dominant equilibrium differs from the Pareto-efficient equilibrium. Individuals are randomly matched to another individual in the population (with full support) and they choose strategies by imitating the most successful individual they observe. So, while individuals interact globally, their observation, as determined by their social network, may be local. In the benchmark model, all individuals observe each other, and hence, an individual imitates the strategy of the most successful individual in the entire population; here, the stochastically stable outcome corresponds to the situation where everyone coordinates on the Pareto-efficient equilibrium. 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 individuals play 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.

Suggested Citation

  • Khan, A., 2013. "Coordination under global random interaction and local imitation," Research Memorandum 004, Maastricht University, Graduate School of Business and Economics (GSBE).
  • Handle: RePEc:unm:umagsb:2013004
    DOI: 10.26481/umagsb.2013004
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    Cited by:

    1. 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.
    2. Zhiwei Cui, 2019. "Matching, Imitation, and Coordination in Networks," Dynamic Games and Applications, Springer, vol. 9(1), pages 47-67, March.
    3. Cabrales, Antonio & Hauk, Esther, 2022. "Norms and the evolution of leaders’ followership," SocArXiv 8mect, Center for Open Science.
    4. Nicola Campigotto, 2021. "Pairwise imitation and evolution of the social contract," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1333-1354, September.
    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. Eugenio Vicario, 2021. "Imitation and Local Interactions: Long Run Equilibrium Selection," Games, MDPI, vol. 12(2), pages 1-19, April.
    7. 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.
    8. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
    9. Cui, Zhiwei & Wang, Rui, 2016. "Collaboration in networks with randomly chosen agents," Journal of Economic Behavior & Organization, Elsevier, vol. 129(C), pages 129-141.

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    More about this item

    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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