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Social Leanring with Course Inference

Author

Listed:
  • Antonio Guarino

    (University College London)

  • Philippe Jehiel

    (Paris School of Economics)

Abstract

We study social learning by boundedly rational agents. Agents take a decision in sequence, after observing their predecessors and a private signal. They are unable to understand their predecessors’ decisions in their finest details: they only understand the relation between the aggregate distribution of actions and the state of nature. We show that, in a continuous action space, compared to the rational case, agents put more weight on early signals. Despite this behavioral bias, beliefs converge to the truth. In a discrete action space, instead, convergence to the truth does not occur even if agents receive signals of unbounded precisions.

Suggested Citation

  • Antonio Guarino & Philippe Jehiel, 2009. "Social Leanring with Course Inference," WEF Working Papers 0050, ESRC World Economy and Finance Research Programme, Birkbeck, University of London.
    • Handle: RePEc:wef:wpaper:0050
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    References listed on IDEAS

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    Cited by:

    1. Antonio Guarino & Antonella Ianni, 2010. "Bayesian Social Learning with Local Interactions," Games, MDPI, vol. 1(4), pages 1-21, October.

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