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Eductive Stability in Real Business Cycle Models

Author

Listed:
  • George Evans

    (OSU - Oregon State University, University of St Andrews [Scotland])

  • Roger Guesnerie

    (PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CdF (institution) - Collège de France)

  • Bruce Mcgough

    (OSU - Oregon State University)

Abstract

Within the standard real business cycle model, we examine issues of expectational coordination on the unique rational expectations equilibrium. We show sensitivity of agents' plans and decisions to their short‐run and long‐run expectations is too great to trigger eductive coordination in a world of rational agents who are endowed with knowledge of the economic structure and contemplate the possibility of small deviations from equilibrium: eductive stability never obtains. We conclude adaptive learning must play a role in real‐time dynamics. Our eductive instability theorem has a counterpart under adaptive learning: even with asymptotic stability, transition dynamics can involve large departures from rational expectations.

Suggested Citation

  • George Evans & Roger Guesnerie & Bruce Mcgough, 2019. "Eductive Stability in Real Business Cycle Models," PSE-Ecole d'économie de Paris (Postprint) halshs-02084319, HAL.
    • Handle: RePEc:hal:pseptp:halshs-02084319
    DOI: 10.1111/ecoj.12620
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    Cited by:

    1. Bao, Te & Dai, Yun & Duffy, John, 2025. "Least squares learning? Evidence from the laboratory," Journal of Economic Dynamics and Control, Elsevier, vol. 172(C).
    2. Gabriel Desgranges & Sayantan Ghosal, 2021. "Partial Consensus in Large Games and Markets," Working Papers 2021_02, Business School - Economics, University of Glasgow.
    3. Evans, George W. & Hommes, Cars & McGough, Bruce & Salle, Isabelle, 2022. "Are long-horizon expectations (de-)stabilizing? Theory and experiments," Journal of Monetary Economics, Elsevier, vol. 132(C), pages 44-63.
    4. Kuhle, Wolfgang, 2021. "Equilibrium with computationally constrained agents," Mathematical Social Sciences, Elsevier, vol. 109(C), pages 77-92.
    5. Evans, George & Honkapohja, Seppo, 2011. "Learning as a rational foundation for macroeconomics and finance," Bank of Finland Research Discussion Papers 8/2011, Bank of Finland.
    6. Gabriel Desgranges & Sayantan Ghosal, 2021. "Heterogeneous beliefs and approximately self-fulfilling outcomes," Working Papers 2021_07, Business School - Economics, University of Glasgow.

    More about this item

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium

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