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Potential games in volatile environments

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  • Staudigl, Mathias

Abstract

This paper studies the co-evolution of networks and play in the context of finite population potential games. Action revision, link creation and link destruction are combined in a continuous-time Markov process. I derive the unique invariant distribution of this process in closed form, as well as the marginal distribution over action profiles and the conditional distribution over networks. It is shown that the equilibrium interaction topology is an inhomogeneous random graph. Furthermore, a characterization of the set of stochastically stable states is provided, generalizing existing results to models with endogenous interaction structures.

Suggested Citation

  • Staudigl, Mathias, 2011. "Potential games in volatile environments," Games and Economic Behavior, Elsevier, vol. 72(1), pages 271-287, May.
  • Handle: RePEc:eee:gamebe:v:72:y:2011:i:1:p:271-287
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    Cited by:

    1. Hellmann, Tim & Staudigl, Mathias, 2014. "Evolution of social networks," European Journal of Operational Research, Elsevier, vol. 234(3), pages 583-596.
    2. Anton Badev, 2014. "Discrete Games in Endogenous Networks: Theory and Policy," 2014 Meeting Papers 901, Society for Economic Dynamics.
    3. Markus Kinateder & Luca Paolo Merlino, 2021. "The Evolution of Networks and Local Public Good Provision: A Potential Approach," Games, MDPI, vol. 12(3), pages 1-12, July.
    4. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves & Lee, Lung-Fei, 2011. "Criminal Networks: Who is the Key Player?," Research Papers in Economics 2011:7, Stockholm University, Department of Economics.
    5. Staudigl, Mathias & Weidenholzer, Simon, 2014. "Constrained interactions and social coordination," Journal of Economic Theory, Elsevier, vol. 152(C), pages 41-63.
    6. Zhiwei Cui, 2019. "Matching, Imitation, and Coordination in Networks," Dynamic Games and Applications, Springer, vol. 9(1), pages 47-67, March.
    7. , D. & Tessone, Claudio J. & ,, 2014. "Nestedness in networks: A theoretical model and some applications," Theoretical Economics, Econometric Society, vol. 9(3), September.
    8. Pongou, Roland & Serrano, Roberto, 2016. "Volume of trade and dynamic network formation in two-sided economies," Journal of Mathematical Economics, Elsevier, vol. 63(C), pages 147-163.
    9. Péter Bayer & Ani Guerdjikova, 2020. "Optimism leads to optimality: Ambiguity in network formation," Working Papers hal-03005107, HAL.
    10. Mathias Staudigl, 2013. "Co-evolutionary dynamics and Bayesian interaction games," International Journal of Game Theory, Springer;Game Theory Society, vol. 42(1), pages 179-210, February.
    11. 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.
    12. Mathias Staudigl, 2010. "On a General class of stochastic co-evolutionary dynamics," Vienna Economics Papers 1001, University of Vienna, Department of Economics.
    13. Pongou, Roland & Serrano, Roberto, 2013. "Dynamic Network Formation in Two-Sided Economies," MPRA Paper 46021, University Library of Munich, Germany.
    14. Sawa, Ryoji, 2014. "Coalitional stochastic stability in games, networks and markets," Games and Economic Behavior, Elsevier, vol. 88(C), pages 90-111.
    15. repec:esx:essedp:747 is not listed on IDEAS
    16. Gerke, Stefanie & Gutin, Gregory & Hwang, Sung-Ha & Neary, Philip R., 2024. "Public goods in networks with constraints on sharing," Journal of Economic Theory, Elsevier, vol. 219(C).

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