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Inertia in social learning from a summary statistic

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  • Larson, Nathan

Abstract

We model normal-quadratic social learning with agents who observe a summary statistic over past actions, rather than complete action histories. Because an agent with a summary statistic cannot correct for the fact that earlier actions influenced later ones, even a small presence of old actions in the statistic can introduce very persistent errors. Depending on how fast these old actions fade from view, social learning can either be as fast as if agents’ private information were pooled (rate n) or it can slow to a crawl (rate ln n). We also examine extensions to learning from samples of actions, learning about a moving target, heterogeneous preferences, and biases toward own information.

Suggested Citation

  • Larson, Nathan, 2008. "Inertia in social learning from a summary statistic," MPRA Paper 32143, University Library of Munich, Germany, revised Jul 2011.
  • Handle: RePEc:pra:mprapa:32143
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    References listed on IDEAS

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    Cited by:

    1. Antonio Guarino & Philippe Jehiel, 2013. "Social Learning with Coarse Inference," American Economic Journal: Microeconomics, American Economic Association, vol. 5(1), pages 147-174, February.
    2. Monzón, Ignacio & Rapp, Michael, 2014. "Observational learning with position uncertainty," Journal of Economic Theory, Elsevier, vol. 154(C), pages 375-402.
    3. Vincent Mak & Rami Zwick, 2014. "Experimenting and learning with localized direct communication," Experimental Economics, Springer;Economic Science Association, vol. 17(2), pages 262-284, June.

    More about this item

    Keywords

    social learning; herding; speed of learning;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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