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

Author

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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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Suggested Citation

  • Shachar Kariv & Syngjoo Choi & Douglas Gale, 2007. "Social Learning in Networks: A Quantal Response Equilibrium Analysis of Experimental Data," Levine's Bibliography 843644000000000107, UCLA Department of Economics.
  • Handle: RePEc:cla:levrem:843644000000000107
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    File URL: http://socrates.berkeley.edu/~kariv/CGK_I.pdf
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Förster, Manuel & Mauleon, Ana & Vannetelbosch, Vincent J., 2016. "Trust and manipulation in social networks," Network Science, Cambridge University Press, vol. 4(02), pages 216-243, June.
    2. Oswaldo Gressani, 2015. "Endogeneous Quantal Response Equilibrium for Normal Form Games," CREA Discussion Paper Series 15-18, Center for Research in Economic Analysis, University of Luxembourg.
    3. Jackson, Matthew O. & Zenou, Yves, 2015. "Games on Networks," Handbook of Game Theory with Economic Applications, Elsevier.
    4. Hahn, Youjin & Islam, Asadul & Patacchini, Eleonora & Zenou, Yves, 2015. "Network Structure and Education Outcomes: Evidence from a Field Experiment in Bangladesh," IZA Discussion Papers 8872, Institute for the Study of Labor (IZA).
    5. Jackson, Matthew O. & Zenou, Yves, 2012. "Games on Networks," CEPR Discussion Papers 9127, C.E.P.R. Discussion Papers.
    6. Youjin Hahn & Asadul Islam & Eleonora Patacchini & Yves Zenou, 2015. "Teams, Organization and Education Outcomes: Evidence from a field experiment in Bangladesh," Monash Economics Working Papers 35-15, Monash University, Department of Economics.
    7. Matthew O. Jackson & Benjamin Golub, 2007. "Naïve Learning in Social Networks: Convergence, Influence and Wisdom of Crowds," Working Papers 2007.64, Fondazione Eni Enrico Mattei.
    8. Zhang, Boyu & Hofbauer, Josef, 2016. "Quantal response methods for equilibrium selection in 2×2 coordination games," Games and Economic Behavior, Elsevier, vol. 97(C), pages 19-31.
    9. Mobius, Markus & Phan, Tuan & Szeidl, Adam, 2015. "Treasure Hunt: Social Learning in the Field," CEPR Discussion Papers 10493, C.E.P.R. Discussion Papers.
    10. He, Simin & Wu, Jiabin, 2018. "Compromise and Coordination: An Experimental Study," MPRA Paper 84713, University Library of Munich, Germany.
    11. repec:hal:journl:halshs-00881145 is not listed on IDEAS
    12. Corazzini, Luca & Pavesi, Filippo & Petrovich, Beatrice & Stanca, Luca, 2012. "Influential listeners: An experiment on persuasion bias in social networks," European Economic Review, Elsevier, vol. 56(6), pages 1276-1288.
    13. Ganga Shreedhar, Alessandro Tavoni, Carmen Marchiori, 2018. "Monitoring and punishment networks in a common-pool resource dilemma: experimental evidence," GRI Working Papers 292, Grantham Research Institute on Climate Change and the Environment.
    14. Yann Algan & Quoc-Anh Do & Nicolò Dalvit & Alexis Le Chapelain & Yves Zenou, 2015. "How Social Networks Shape Our Beliefs: A Natural Experiment among Future French Politicians," Sciences Po publications info:hdl:2441/78vacv4udu9, Sciences Po.
    15. Syngjoo Choi & Edoardo Gallo & Shachar Kariv, 2015. "Networks in the laboratory," Cambridge Working Papers in Economics 1551, Faculty of Economics, University of Cambridge.

    More about this item

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior

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