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Empirical calibration of adaptive learning

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  • Berardi, Michele
  • Galimberti, Jaqueson K.

Abstract

Adaptive learning introduces persistence in the evolution of agents’ beliefs over time, helping explain why economies present sluggish adjustments towards equilibrium. The pace of this learning process is directly determined by the gain parameter. We document and evaluate gain calibrations for a broad range of model specifications with macroeconomic data, also developing alternative approaches to the endogenous determination of time-varying gains in real-time. Our key findings are that learning gains are higher for inflation than for output growth and interest rates, and that calibrations to match survey forecasts are lower than those derived according to forecasting performance, suggesting some degree of bounded rationality in the speed with which agents update their beliefs.

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  • Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
    • Handle: RePEc:eee:jeborg:v:144:y:2017:i:c:p:219-237
    DOI: 10.1016/j.jebo.2017.10.004
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    2. Mayer, Alexander, 2023. "Two-step estimation in linear regressions with adaptive learning," Statistics & Probability Letters, Elsevier, vol. 195(C).
    3. Jaqueson K. Galimberti, 2020. "Information weighting under least squares learning," CAMA Working Papers 2020-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Michele Berardi, 2018. "Information aggregation and learning in a dynamic asset pricing model," Centre for Growth and Business Cycle Research Discussion Paper Series 241, Economics, The University of Manchester.
    5. Cars Hommes & Kostas Mavromatis & Tolga Özden & Mei Zhu, 2023. "Behavioral learning equilibria in New Keynesian models," Quantitative Economics, Econometric Society, vol. 14(4), pages 1401-1445, November.
    6. Kobielarz, Michal, 2018. "The economics of monetary unions," Other publications TiSEM b0293536-68ec-4905-bffd-6, Tilburg University, School of Economics and Management.
    7. Koursaros, Demetris, 2019. "Learning expectations using multi-period forecasts," Journal of Economics and Business, Elsevier, vol. 102(C), pages 1-25.
    8. Galimberti, Jaqueson K., 2019. "An approximation of the distribution of learning estimates in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 102(C), pages 29-43.
    9. Michele Berardi, 2020. "A probabilistic interpretation of the constant gain learning algorithm," Bulletin of Economic Research, Wiley Blackwell, vol. 72(4), pages 393-403, October.
    10. Cole, Stephen J. & Milani, Fabio, 2021. "Heterogeneity in individual expectations, sentiment, and constant-gain learning," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 627-650.
    11. Poledna, Sebastian & Miess, Michael Gregor & Hommes, Cars & Rabitsch, Katrin, 2023. "Economic forecasting with an agent-based model," European Economic Review, Elsevier, vol. 151(C).
    12. Michele Berardi, 2016. "Herding through learning in an asset pricing model," Centre for Growth and Business Cycle Research Discussion Paper Series 223, Economics, The University of Manchester.
    13. Alexander Mayer, 2022. "Estimation and inference in adaptive learning models with slowly decreasing gains," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 720-749, September.
    14. Berardi, Michele, 2019. "A probabilistic interpretation of the constant gain algorithm," MPRA Paper 94023, University Library of Munich, Germany.

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    More about this item

    Keywords

    Bounded rationality; Expectations; Forecasting; Real-time data; Recursive estimation;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • E03 - Macroeconomics and Monetary Economics - - General - - - Behavioral Macroeconomics
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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