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Imitation and Efficient Contagion

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  • Boyer, Tristan
  • Jonard, Nicolas

Abstract

In this paper we study the conditions under which efficient behavior can spread from a finite initial seed group to an infinite population living on a network. We formulate conditions on payoffs and network structure under which overall contagion occurs in arbitrary regular networks. Central in this process is the communication pattern among players who are confronted with the same decision, i.e. who are at the same distance from the initial seed group. The extent to which these agents interact among themselves (rather than with players who already have faced or subsequently will face the decision problem) is critical in the Prisoner’s Dilemma. In the Coordination Game the key element is the cohesion of the efficient cluster, a property which is different from the one identified in the Prisoner’s Dilemma. Additional results are obtained when we distinguish the interaction and information neighborhoods. Specifically, we find that contagion tends to be favored by fast neighborhood growth if an assumption of conservative behavior is made. We discuss our findings in relation to the notions of clustering, transitivity and cohesion.

Suggested Citation

  • Boyer, Tristan & Jonard, Nicolas, 2010. "Imitation and Efficient Contagion," MPRA Paper 23430, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:23430
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    Cited by:

    1. Cartwright, Edward & Singh, Thomas B., 2018. "Observation and contagion effects in cooperation: An experimental investigation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 74(C), pages 151-160.
    2. Bailey, Warren B. & Cao, Xiaping & Yang, Zhenyi & Zhou, Sili, 2024. "Who leads and who follows? The cross-border peer effect in investment by Chinese and US firms," Journal of International Economics, Elsevier, vol. 147(C).
    3. Yanlong Zhang & Wolfram Elsner, 2020. "Social leverage, a core mechanism of cooperation. Locality, assortment, and network evolution," Journal of Evolutionary Economics, Springer, vol. 30(3), pages 867-889, July.
    4. Widad Guechtouli, 2008. "How Do Communication Structures Shape The Process Of Knowledge Transfer? - An Agent-Based Model," Working Papers halshs-00349033, HAL.
    5. Widad Guechtouli, 2006. "Learning in a community of practice : Complete vs. incomplete information," Working Papers halshs-00410764, HAL.
    6. Edgar J. Sánchez Carrera & Elena Gubar & Andrey F. Oleynik, 2019. "Network Structures and Poverty Traps," Dynamic Games and Applications, Springer, vol. 9(1), pages 236-253, March.
    7. Amparo Urbano, 2011. "SEA Presidential address: Group connectivity and cooperation," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 2(2), pages 139-158, June.
    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.

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    Keywords

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    JEL classification:

    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

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