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Behavioral Learning Equilibria

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  • Hommes, C.H.

    () (University of Amsterdam)

  • Zhu, M.

    () (University of Amsterdam)

Abstract

We propose behavioral learning equilibria as a plausible explanation of coordination of individual expectations and aggregate phenomena such as excess volatility in stock prices and high persistence in inflation. Boundedly rational agents use a simple univariate linear forecasting rule and correctly forecast the unconditional sample mean and first-order sample autocorrelation. In the long run, agents learn the best univariate linear forecasting rule, without fully recognizing the structure of the economy. The simplicity of behavioral learning equilibria makes coordination of individual expectations on such an aggregate outcome more likely. In a first application, an asset pricing model with AR(1) dividends, a unique behavioral learning equilibrium exists characterized by high persistence and excess volatility, and it is stable under learning. In a second application, the New Keynesian Phillips curve, multiple equilibria co-exist, learning exhibits path dependence and inflation may switch between low and high persistence regimes.

Suggested Citation

  • Hommes, C.H. & Zhu, M., 2012. "Behavioral Learning Equilibria," CeNDEF Working Papers 12-09, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  • Handle: RePEc:ams:ndfwpp:12-09
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    References listed on IDEAS

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    Cited by:

    1. Di Pace, Frederico & Mitra, Kaushik & Zhang, Shoujian, 2016. "Adaptive learning and labour market dynamics," Bank of England working papers 633, Bank of England.
    2. Gelain, Paolo & Lansing, Kevin J., 2014. "House prices, expectations, and time-varying fundamentals," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 3-25.
    3. Hommes, Cars H., 2014. "Behaviorally Rational Expectations and Almost Self-Fulfilling Equilibria," Review of Behavioral Economics, now publishers, vol. 1(1-2), pages 75-97, January.
    4. Lansing, Kevin J. & Ma, Jun, 2017. "Explaining exchange rate anomalies in a model with Taylor-rule fundamentals and consistent expectations," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 62-87.
    5. Cars Hommes, 2013. "Reflexivity, expectations feedback and almost self-fulfilling equilibria: economic theory, empirical evidence and laboratory experiments," Journal of Economic Methodology, Taylor & Francis Journals, vol. 20(4), pages 406-419, December.
    6. Pfajfar, Damjan & Žakelj, Blaž, 2015. "Inflation Expectations and Monetary Policy Design: Evidence from the Laboratory," Finance and Economics Discussion Series 2015-45, Board of Governors of the Federal Reserve System (U.S.).
    7. Dudek, Maciej K., 2014. "Living in an imaginary world that looks real," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 209-223.
    8. Nagel, Rosemarie & Bühren, Christoph & Frank, Björn, 2017. "Inspired and inspiring: Hervé Moulin and the discovery of the beauty contest game," Mathematical Social Sciences, Elsevier, vol. 90(C), pages 191-207.
    9. Michele Berardi, 2016. "Herding through learning in an asset pricing model," Centre for Growth and Business Cycle Research Discussion Paper Series 223, Economics, The Univeristy of Manchester.
    10. Kuang, Pei & Mitra, Kaushik, 2016. "Long-run growth uncertainty," Journal of Monetary Economics, Elsevier, vol. 79(C), pages 67-80.
    11. Hommes, C.H. & Zhu, M., 2016. "Behavioral Learning Equilibria, Persistence Amplification & Monetary Policy," CeNDEF Working Papers 16-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    12. Cars Hommes, 2017. "From self-fulfilling mistakes to behavioral learning equilibria," Tinbergen Institute Discussion Papers 17-018/II, Tinbergen Institute.
    13. Nakagawa, Ryuichi, 2015. "Learnability of an equilibrium with private information," Journal of Economic Dynamics and Control, Elsevier, vol. 59(C), pages 58-74.
    14. Branch, William A., 2016. "Imperfect knowledge, liquidity and bubbles," Journal of Economic Dynamics and Control, Elsevier, vol. 62(C), pages 17-42.
    15. Christian Schoder, 2015. "Methodological, internal and ontological inconsistencies in the conventional micro-foundation of post-Keynesian theory," Working Papers 1518, New School for Social Research, Department of Economics.
    16. Michele Berardi, 2015. "Expectations formation under adaptive learning and evolutionary dynamics," Centre for Growth and Business Cycle Research Discussion Paper Series 206, Economics, The Univeristy of Manchester.
    17. repec:kap:compec:v:50:y:2017:i:2:d:10.1007_s10614-016-9607-y is not listed on IDEAS
    18. Xiao, Wei & Xu, Junyi, 2014. "Expectations and optimal monetary policy: A stability problem revisited," Economics Letters, Elsevier, vol. 124(2), pages 296-299.
    19. Arifovic, J. & Hommes, C.H. & Salle, I., 2016. "Learning to believe in Simple Equilibria in a Complex OLG Economy - evidence from the lab," CeNDEF Working Papers 16-06, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    20. Federico di Pace & Kaushik Mitra & Shoujian Zhang, 2014. "Adaptive Learning and Labour Market Dynamics," CDMA Working Paper Series 201408, Centre for Dynamic Macroeconomic Analysis.

    More about this item

    JEL classification:

    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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