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Adaptive Social Learning

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  • Christoph March

Abstract

The paper investigates social-learning when the information structure is not commonly known. Individuals repeatedly interact in social-learning settings with distinct information structures. In each round of interaction, they use their experience gained in past rounds to draw inferences from their predecessors’ current decisions. Such adaptation yields rational behavior in the long-run if and only if individuals distinguish social-learning settings and receive rich feedback after each round. Limited feedback may lead individuals to imitate uninformed predecessors. Moreover, adaptation across social-learning settings renders Bayes’ rule payoff-inferior compared to non-Bayesian belief updating rules and suggests that belief-updating rules are heterogeneous in the population.

Suggested Citation

  • Christoph March, 2016. "Adaptive Social Learning," CESifo Working Paper Series 5783, CESifo.
  • Handle: RePEc:ces:ceswps:_5783
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    Cited by:

    1. Christoph March & Sebastian Krügel & Anthony Ziegelmeyer, 2012. "Do We Follow Private Information when We Should? Laboratory Evidence on Naive Herding," Working Papers halshs-00671378, HAL.
    2. Christoph March & Anthony Ziegelmeyer, 2018. "Excessive Herding in the Laboratory: The Role of Intuitive Judgments," CESifo Working Paper Series 6855, CESifo.

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    More about this item

    Keywords

    informational herding; adaptation; analogy-based expectations equilibrium; Non-Bayesian updating;
    All these keywords.

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • 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

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