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Models and Anti-Models: The Structure of Payoff-Dependent Social Learning

Author

Listed:
  • Charles Efferson
  • Rafael Lalive
  • Peter J. Richerson,
  • Richard McElreath
  • Mark Lubell

Abstract

We conducted an experiment to describe how social learners use information about the relation between payoffs and behavior. Players chose between two technologies repeatedly. Payoffs were random, but one technology was better because its expected payoff was higher. Players were divided into two groups: 1) individual learners who knew their realized payoffs after each choice and 2) social learners, who had no private feedback about their own payoffs, but in each period could choose to learn which behavior had produced the lowest payoff among the individual learners or which behavior had produced the highest payoff. When social learners chose to know the behavior producing the highest payoff, a model of imitating this successful behavior matches the data very closely. When social learners chose to know the behavior producing the lowest payoff, they tended to choose the opposite behavior in early periods, while increasingly choosing the same behavior in late periods. This kind of rapid temporal heterogeneity in the use of social information has received little or no attention in the theoretical study of social learning.

Suggested Citation

  • Charles Efferson & Rafael Lalive & Peter J. Richerson, & Richard McElreath & Mark Lubell, 2006. "Models and Anti-Models: The Structure of Payoff-Dependent Social Learning," IEW - Working Papers 290, Institute for Empirical Research in Economics - University of Zurich.
  • Handle: RePEc:zur:iewwpx:290
    as

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    File URL: https://www.zora.uzh.ch/id/eprint/52246/1/iewwp290.pdf
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    References listed on IDEAS

    as
    1. Henrich, Joseph, 2004. "Cultural group selection, coevolutionary processes and large-scale cooperation," Journal of Economic Behavior & Organization, Elsevier, vol. 53(1), pages 3-35, January.
    2. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    3. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    4. Offerman, Theo & Sonnemans, Joep, 1998. "Learning by experience and learning by imitating successful others," Journal of Economic Behavior & Organization, Elsevier, vol. 34(4), pages 559-575, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    social learning; payoff information; gene-culture coevolution; laboratory experiment;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

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