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Learning From the Expectations of Others

Author

Listed:
  • Jim Granato

    (University of Texas)

  • Eran Guse

    (University of Cambridge)

  • Sunny Wong

    (Southern Mississippi University)

Abstract

The assumption of perfectly rational representative agents is now commonly questioned. This paper explores the equilibrium properties of boundedly rational heterogeneous agents. We combine an adaptive learning process in a modified cobweb model within a Stackleberg framework. We assume that there is an asymmetric information diffusion process from leading to following firms. In contrast to a simple cobweb model which has a unique REE, our model may produce multiple restricted perceptions equilibria (RPE). However, a unique and learnable RPE, under certain conditions, can exist in our model. In addition, the following firms' forecasts can confound the leading firms' forecasts -- when the following firms misinterpret information coming from the leading firms. We refer this situation to the boomerang effect. We also find that the leading firms' mean squared forecast error can be even larger than that of following firms if the proportion of following firms is sufficiently large in the market

Suggested Citation

  • Jim Granato & Eran Guse & Sunny Wong, 2006. "Learning From the Expectations of Others," Computing in Economics and Finance 2006 449, Society for Computational Economics.
    • Handle: RePEc:sce:scecfa:449
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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. Junyi Xu, 2021. "Reinforcement Learning in a Cournot Oligopoly Model," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1001-1024, December.
    3. repec:wvu:wpaper:11-04 is not listed on IDEAS
    4. 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.
    5. 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.
    6. 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.
    7. Cone, Thomas E., 2006. "Learning with limited bandwidth and attention to others' learning," Economics Letters, Elsevier, vol. 93(1), pages 132-136, October.
    8. 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.

    More about this item

    Keywords

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    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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