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Coalitions, tipping points and the speed of evolution

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  • Newton, Jonathan
  • Angus, Simon D.

Abstract

This study considers pure coordination games on networks and the waiting time for an adaptive process of strategic change to achieve efficient coordination. Although it is in the interest of every player to coordinate on a single globally efficient norm, coalitional behavior at a local level can greatly slow, as well as hasten convergence to efficiency. For some networks, when one action becomes efficient enough relative to the other, the effect of coalitional behavior changes abruptly from a conservative effect to a reforming effect. These effects are confirmed for a variety of stylized and empirical social networks found in the literature. For coordination games in which the Pareto efficient and risk dominant equilibria differ, polymorphic states can be the only stochastically stable states.

Suggested Citation

  • Newton, Jonathan & Angus, Simon D., 2013. "Coalitions, tipping points and the speed of evolution," Working Papers 2013-02, University of Sydney, School of Economics.
    • Handle: RePEc:syd:wpaper:2123/8895
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    Cited by:

    1. Newton, Jonathan & Sercombe, Damian, 2020. "Agency, potential and contagion," Games and Economic Behavior, Elsevier, vol. 119(C), pages 79-97.
    2. Sung-Ha Hwang & Jonathan Newton, 2017. "Payoff-dependent dynamics and coordination games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 64(3), pages 589-604, October.
    3. Jonathan Newton, 2019. "Agency Equilibrium," Games, MDPI, vol. 10(1), pages 1-15, March.
    4. Cui, Zhiwei, 2023. "Linking friction, social coordination and the speed of evolution," Games and Economic Behavior, Elsevier, vol. 140(C), pages 410-430.
    5. Rusch, Hannes, 2019. "The evolution of collaboration in symmetric 2×2-games with imperfect recognition of types," Games and Economic Behavior, Elsevier, vol. 114(C), pages 118-127.
    6. Sawa, Ryoji & Wu, Jiabin, 2023. "Statistical inference in evolutionary dynamics," Games and Economic Behavior, Elsevier, vol. 137(C), pages 294-316.
    7. 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.
    8. Newton, Jonathan & Wait, Andrew & Angus, Simon D., 2019. "Watercooler chat, organizational structure and corporate culture," Games and Economic Behavior, Elsevier, vol. 118(C), pages 354-365.
    9. 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.
    10. Newton, Jonathan & Angus, Simon D., 2015. "Coalitions, tipping points and the speed of evolution," Journal of Economic Theory, Elsevier, vol. 157(C), pages 172-187.
    11. Simon D Angus & Jonathan Newton, 2015. "Emergence of Shared Intentionality Is Coupled to the Advance of Cumulative Culture," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-12, October.
    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. Bary S. R. Pradelski & Heinrich H. Nax, 2020. "Market sentiments and convergence dynamics in decentralized assignment economies," International Journal of Game Theory, Springer;Game Theory Society, vol. 49(1), pages 275-298, March.
    14. Sanjeev Goyal & Penélope Hernández & Guillem Martínez-Cánovas & Frédéric Moisan & Manuel Muñoz-Herrera & Angel Sánchez, 2021. "Integration and diversity," Experimental Economics, Springer;Economic Science Association, vol. 24(2), pages 387-413, June.
      • Goyal, S. & Hernández, P. & Muñnez-Cánovasz, G. & Moisan, F. & Muñoz-Herrera, M. & Sánchez, A., 2017. "Integration and Diversity," Cambridge Working Papers in Economics 1721, Faculty of Economics, University of Cambridge.
      • Sanjeev Goyal & Penelope Hernandez & Guillem Martinez-Canovas & Frederic Moisan & Manuel Munoz-Herrera & Angel Sanchez, 2019. "Integration and Diversity," Working Papers 20190025, New York University Abu Dhabi, Department of Social Science, revised Sep 2020.
      • Sanjeev Goyal & Penélope Hernández & Guillem Martínez-Cánovas & Frederic Moisan & Manuel Muñoz-Herrera & Angel Sánchez, 2021. "Integration and Diversity," Post-Print hal-03188210, HAL.
      • Sanjeev Goyal & Pénélope Hernández & Guillem Martínez-Cánovas & Frédéric Moisan & Manuel Muñoz-Herrera & Ángel Sánchez, 2021. "Integration and diversity," Post-Print halshs-03051962, HAL.
    15. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
    16. Newton, Jonathan, 2017. "Shared intentions: The evolution of collaboration," Games and Economic Behavior, Elsevier, vol. 104(C), pages 517-534.
    17. Simon D Angus & Jonathan Newton, 2020. "Collaboration leads to cooperation on sparse networks," PLOS Computational Biology, Public Library of Science, vol. 16(1), pages 1-11, January.
    18. Bayer, Péter, 2023. "Evolutionarily stable networks," TSE Working Papers 23-1487, Toulouse School of Economics (TSE).
    19. Nax, Heinrich H. & Newton, Jonathan, 2019. "Risk attitudes and risk dominance in the long run," Games and Economic Behavior, Elsevier, vol. 116(C), pages 179-184.
    20. Newton, Jonathan & Naono, Miharu, 2025. "Maxmin, coalitions and evolution," Games and Economic Behavior, Elsevier, vol. 153(C), pages 474-498.
    21. 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.

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    JEL classification:

    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • 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

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