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Learning From The Expectations Of Others

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  • GRANATO, JIM
  • GUSE, ERAN A.
  • WONG, M. C. SUNNY

Abstract

This paper explores the equilibrium properties of boundedly rational heterogeneous agents under adaptive learning. In a modified cobweb model with a Stackelberg framework, there is an asymmetric information diffusion process from leading to following firms. It turns out that the conditions for at least one learnable equilibrium are similar to those under homogeneous expectations. However, the introduction of information diffusion leads to the possibility of multiple equilibria and can expand the parameter space of potential learnable equilibria. In addition, the inability to correctly interpret expectations will cause a “boomerang effect” on the forecasts and forecast efficiency of the leading firms. The leading firms' mean square forecast error can be larger than that of following firms if the proportion of following firms is sufficiently large.

Suggested Citation

  • Granato, Jim & Guse, Eran A. & Wong, M. C. Sunny, 2008. "Learning From The Expectations Of Others," Macroeconomic Dynamics, Cambridge University Press, vol. 12(3), pages 345-377, June.
  • Handle: RePEc:cup:macdyn:v:12:y:2008:i:03:p:345-377_07
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    References listed on IDEAS

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    Cited by:

    1. Michele Berardi, 2009. "Monetary Policy with Heterogeneous and Misspecified Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(1), pages 79-100, February.
    2. Eran Guse & M. C. Sunny Wong, 2022. "Communication and Learning: The Bilateral Information Transmission in the Cobweb Model," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 693-723, August.
    3. Muto, Ichiro, 2011. "Monetary policy and learning from the central bank's forecast," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 52-66, January.
    4. Junyi Xu, 2021. "Reinforcement Learning in a Cournot Oligopoly Model," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1001-1024, December.
    5. Cone, Thomas E., 2006. "Learning with limited bandwidth and attention to others' learning," Economics Letters, Elsevier, vol. 93(1), pages 132-136, October.
    6. Jim Granato & Melody Lo & M. C. Sunny Wong, 2010. "A Framework for Unifying Formal and Empirical Analysis," American Journal of Political Science, John Wiley & Sons, vol. 54(3), pages 783-797, July.
    7. repec:wvu:wpaper:11-04 is not listed on IDEAS
    8. Arthur Charpentier & Romuald Élie & Carl Remlinger, 2023. "Reinforcement Learning in Economics and Finance," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 425-462, June.

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    More about this item

    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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