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Adaptive learning and survey data

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  • Markiewicz, Agnieszka
  • Pick, Andreas

Abstract

This paper investigates the ability of the adaptive learning approach to replicate the expectations of professional forecasters. For a range of macroeconomic and financial variables, we compare constant and decreasing gain learning models to simple, yet powerful benchmark models. We find that constant gain models provide a better fit for the expectations of professional forecasters. For macroeconomic series they usually perform significantly better than a naïve random walk forecast. In contrast, we find it difficult to beat the no-change benchmark using the adaptive learning models to forecast financial variables.

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  • Markiewicz, Agnieszka & Pick, Andreas, 2014. "Adaptive learning and survey data," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 685-707.
  • Handle: RePEc:eee:jeborg:v:107:y:2014:i:pb:p:685-707
    DOI: 10.1016/j.jebo.2014.04.005
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    3. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
    4. Jaqueson K. Galimberti, 2020. "Information weighting under least squares adaptive learning," Working Papers 2020-04, Auckland University of Technology, Department of Economics.
    5. Iliopulos, Eleni & Perego, Erica & Sopraseuth, Thepthida, 2021. "International business cycles: Information matters," Journal of Monetary Economics, Elsevier, vol. 123(C), pages 19-34.
    6. Norbert Christopeit & Michael Massmann, 2013. "Estimating Structural Parameters in Regression Models with Adaptive Learning," Tinbergen Institute Discussion Papers 13-111/III, Tinbergen Institute.
    7. Audzei, Volha, 2023. "Learning and cross-country correlations in a multi-country DSGE model," Economic Modelling, Elsevier, vol. 120(C).
    8. André, Marine Charlotte & Dai, Meixing, 2017. "Is central bank conservatism desirable under learning?," Economic Modelling, Elsevier, vol. 60(C), pages 281-296.
    9. Koursaros, Demetris, 2019. "Learning expectations using multi-period forecasts," Journal of Economics and Business, Elsevier, vol. 102(C), pages 1-25.
    10. 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.
    11. Gelfer, Sacha, 2020. "The effects of professional forecast dissemination on macroeconomic volatility," Journal of Economic Behavior & Organization, Elsevier, vol. 170(C), pages 131-156.
    12. Ilek, Alex, 2021. "Are monetary surprises effective? The view of professional forecasters in Israel," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 516-530.
    13. 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.
    14. Berardi, Michele & Galimberti, Jaqueson K., 2014. "A note on the representative adaptive learning algorithm," Economics Letters, Elsevier, vol. 124(1), pages 104-107.
    15. Alexander Mayer, 2022. "Two-step estimation in linear regressions with adaptive learning," Papers 2204.05298, arXiv.org, revised Nov 2022.
    16. Marine Charlotte André & Meixing Dai, 2015. "Central bank accountability under adaptive learning," Working Papers of BETA 2015-32, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    17. 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.
    18. Marine Charlotte André & Meixing Dai, 2017. "Learning, optimal monetary delegation and stock prices dynamics," Working Papers of BETA 2017-37, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.

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    More about this item

    Keywords

    Expectations; Survey of professional forecasters; Adaptive learning; Bounded rationality;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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