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Learning by Matching

Author

Listed:
  • Manuel Amador
  • Pierre-Olivier Weill

    (Finance New York University)

Abstract

We study how a continuum of agents learn about disseminated information in a dynamic beauty contest model when they do not observe aggregate variables, such as prices or quantities, but randomly observe each other's actions. We solve for the market equilibrium and find that the average learning curve is S-shaped: learning is slow initially, intensifies rapidly and finally converges slowly to the truth. We show that increasing public information always slows down learning in the long run. Under some conditions, even if agents have no coordination motive, it also reduces welfare. Lastly, optimal diffusion of information requires that agents ``strive to be different'': agents need to be rewarded for choosing actions away from the population average

Suggested Citation

  • Manuel Amador & Pierre-Olivier Weill, 2006. "Learning by Matching," 2006 Meeting Papers 373, Society for Economic Dynamics.
    • Handle: RePEc:red:sed006:373
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    Cited by:

    1. Pierre-Olivier Weill, 2020. "The search theory of OTC markets," NBER Working Papers 27354, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    Learning; Search and Matching;

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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