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Networks Emerging in a Volatile World

Author

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  • George Ehrhardt
  • Matteo Marsili
  • Fernando Vega-Redondo

Abstract

The paper proposes a model to study the conditions under which complex networks emerge (or not) when agents are involved in a dynamic coordination setup. The focus, however, is not on the classical issue of equilibrium selection - instead, our aim is to shed light on how agents' efforts to coordinate a¤ect the process of network formation in a large and complex environment. The model posits that, over time, new links are created if they are pro.table, and existing links disappear due to exogenous decay. Alongside this struggle between link creation and link destruction, agents' choices in the coordination game adapt to their current local conditions and thus coevolve with the social network. The dynamic behavior of the system is studied within di¤erent time scales (the long and ultralong runs), which di¤er in the role accorded to the noise that is induced by finite populations. We characterize analytically the evolution of the modelin each case and show that, depending on the time scale under consideration, the process displays discontinuous transitions in overall connectivity, resilient transformations in network topology, and equilibrium multiplicity. This behavior is akin to that observed concerning various network phenomena where coordination and network formation display mutually reinforcing roles.

Suggested Citation

  • George Ehrhardt & Matteo Marsili & Fernando Vega-Redondo, 2008. "Networks Emerging in a Volatile World," Economics Working Papers ECO2008/08, European University Institute.
  • Handle: RePEc:eui:euiwps:eco2008/08
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. , D. & Tessone, Claudio J. & ,, 2014. "Nestedness in networks: A theoretical model and some applications," Theoretical Economics, Econometric Society, vol. 9(3), September.
    3. Mathias Staudigl, 2010. "On a General class of stochastic co-evolutionary dynamics," Vienna Economics Papers vie1001, University of Vienna, Department of Economics.
    4. Staudigl, Mathias, 2011. "Potential games in volatile environments," Games and Economic Behavior, Elsevier, vol. 72(1), pages 271-287, May.
    5. M. Koenig & Claudio J. Tessone & Yves Zenou, "undated". "A Dynamic Model of Network Formation with Strategic Interactions," Working Papers CCSS-09-006, ETH Zurich, Chair of Systems Design.
    6. Bargigli, Leonardo & Tedeschi, Gabriele, 2014. "Interaction in agent-based economics: A survey on the network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 1-15.
    7. Mathias Staudigl, 2010. "On a General class of stochastic co-evolutionary dynamics," Vienna Economics Papers 1001, University of Vienna, Department of Economics.

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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
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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