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Social Learning in Networks: A Quantal Response Equilibrium Analysis of Experimental Data

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  • Shachar Kariv
  • Syngjoo Choi
  • Douglas Gale

Abstract

Individuals living in society are bound together by a social network and, in many social and economic situations, individuals learn by observing the behavior of others in their local environment. This process is called social learning. Learning in incomplete networks, where different individuals have different information, is especially challenging: because of the lack of common knowledge individuals must draw inferences about the actions others have observed, as well as about their private information. This paper reports an experimental investigation of learning in three-person networks and uses the theoretical framework of Gale and Kariv (Games Econ Behav 45:329–346, 2003 ) to interpret the data generated by the experiments. The family of three-person networks includes several non-trivial architectures, each of which gives rise to its own distinctive learning patterns. To test the usefulness of the theory in interpreting the data, we adapt the Quantal Response Equilibrium (QRE) model of Mckelvey and Palfrey (Games Econ Behav 10:6–38, 1995 ; Exp Econ 1:9–41, 1998 ). We find that the theory can account for the behavior observed in the laboratory in a variety of networks and informational settings. This provides important support for the use of QRE to interpret experimental data. Copyright Springer-Verlag 2012

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Bibliographic Info

Paper provided by UCLA Department of Economics in its series Levine's Bibliography with number 843644000000000107.

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Date of creation: 22 Jul 2007
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Handle: RePEc:cla:levrem:843644000000000107

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  1. Matthew O. Jackson, 2003. "A survey of models of network formation: Stability and efficiency," Working Papers, California Institute of Technology, Division of the Humanities and Social Sciences 1161, California Institute of Technology, Division of the Humanities and Social Sciences.
  2. Duflo, Esther & Saez, Emmanuel, 2002. "Participation and investment decisions in a retirement plan: the influence of colleagues' choices," Journal of Public Economics, Elsevier, Elsevier, vol. 85(1), pages 121-148, July.
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  25. repec:rne:rneart:v:3:y:2004:i:1:p:19-41 is not listed on IDEAS
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Cited by:
  1. Corazzini, Luca & Pavesi, Filippo & Petrovich, Beatrice & Stanca, Luca, 2012. "Influential listeners: An experiment on persuasion bias in social networks," European Economic Review, Elsevier, Elsevier, vol. 56(6), pages 1276-1288.
  2. Manuel Förster & Ana Mauleon & Vincent J. Vannetelbosch, 2014. "Trust and Manipulation in Social Networks," Working Papers, Fondazione Eni Enrico Mattei 2014.50, Fondazione Eni Enrico Mattei.
  3. Matthew O. Jackson & Benjamin Golub, 2007. "Naïve Learning in Social Networks: Convergence, Influence and Wisdom of Crowds," Working Papers, Fondazione Eni Enrico Mattei 2007.64, Fondazione Eni Enrico Mattei.

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