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A Theory of Learning with Heterogeneous Agents

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  • Bala, Venkatesh
  • Goyal, Sanjeev

Abstract

The authors study learning in organizations comprised of short-lived agents with heterogeneous beliefs. It is shown that the sequence of actions converges in probability to the set of ex-post optimal actions. Under some identifiability conditions, beliefs also converge in probability to point mass on the truth. Moreover, while actions and posterior beliefs converge in probability, they can simultaneously almost surely fail to converge. The authors' simulations of N. Kiefer's 1989 monopoly learning model suggest that, if the firm is operated by a sequence of short-lived managers with heterogeneous beliefs, then complete learning of the demand curve obtains. Copyright 1995 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

Suggested Citation

  • Bala, Venkatesh & Goyal, Sanjeev, 1995. "A Theory of Learning with Heterogeneous Agents," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 36(2), pages 303-323, May.
  • Handle: RePEc:ier:iecrev:v:36:y:1995:i:2:p:303-23
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    Cited by:

    1. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 595-621.
    2. Sanjeev Goyal, 2015. "Networks in Economics: A Perspective on the Literature," Cambridge Working Papers in Economics 1548, Faculty of Economics, University of Cambridge.
    3. Piergiuseppe Morone & Richard Taylor, 2004. "A Laboratory Experiment of Knowledge Diffusion Dynamics," Experimental 0407004, EconWPA.
    4. Thomas Ahn & Jacob L. Vigdor, 2014. "When Incentives Matter Too Much: Explaining Significant Responses to Irrelevant Information," NBER Working Papers 20321, National Bureau of Economic Research, Inc.

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