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Learning the Hard Way: Expectations and the U.S. Great Depression

Author

Listed:
  • Pablo Aguilar

    (Bank of Spain and UNIVERSITE CATHOLIQUE DE LOUVAIN, Institut de Recherches Economiques et Sociales (IRES))

  • Luca Pensieroso

    (UNIVERSITE CATHOLIQUE DE LOUVAIN, Institut de Recherches Economiques et Sociales (IRES))

Abstract

We introduce adaptive learning – a parsimonious, convenient way to model uncertainty – in a dynamic general equilibrium model of the U.S. Great Depression. We show that even the smallest departure from rational expectations increases significantly the data mimicking ability of the model, in particular for what concerns the lack of recovery in detrended GDP after 1933. We conclude that in the case of big, traumatic events like the Great Depression, uncertainty is particularly unfavourable to the recovery phase.

Suggested Citation

  • Pablo Aguilar & Luca Pensieroso, 2022. "Learning the Hard Way: Expectations and the U.S. Great Depression," LIDAM Discussion Papers IRES 2022004, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    • Handle: RePEc:ctl:louvir:2022004
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    File URL: https://sites.uclouvain.be/econ/DP/IRES/2022004.pdf
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    References listed on IDEAS

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    1. Stefano Eusepi & Bruce Preston, 2011. "Expectations, Learning, and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 101(6), pages 2844-2872, October.
    2. Marcet, Albert & Sargent, Thomas J., 1989. "Convergence of least squares learning mechanisms in self-referential linear stochastic models," Journal of Economic Theory, Elsevier, vol. 48(2), pages 337-368, August.
    3. Mark Gertler, 2017. "Rethinking the Power of Forward Guidance: Lessons from Japan," IMES Discussion Paper Series 17-E-08, Institute for Monetary and Economic Studies, Bank of Japan.
    4. Christiano, Lawrence J & Eichenbaum, Martin, 1992. "Current Real-Business-Cycle Theories and Aggregate Labor-Market Fluctuations," American Economic Review, American Economic Association, vol. 82(3), pages 430-450, June.
    5. Bruce Preston, 2005. "Learning about Monetary Policy Rules when Long-Horizon Expectations Matter," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
    6. Ben S. Bernanke & Michael T. Kiley & John M. Roberts, 2019. "Monetary Policy Strategies for a Low-Rate Environment," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 421-426, May.
    7. Sergey Slobodyan & Raf Wouters, 2012. "Learning in a Medium-Scale DSGE Model with Expectations Based on Small Forecasting Models," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(2), pages 65-101, April.
    8. Greenwood, Jeremy & Hercowitz, Zvi & Huffman, Gregory W, 1988. "Investment, Capacity Utilization, and the Real Business Cycle," American Economic Review, American Economic Association, vol. 78(3), pages 402-417, June.
    9. De Vroey Michel R & Pensieroso Luca, 2006. "Real Business Cycle Theory and the Great Depression: The Abandonment of the Abstentionist Viewpoint," The B.E. Journal of Macroeconomics, De Gruyter, vol. 6(1), pages 1-26, November.
    10. Joines, Douglas H, 1981. "Estimates of Effective Marginal Tax Rates on Factor Incomes," The Journal of Business, University of Chicago Press, vol. 54(2), pages 191-226, April.
    11. Milani, Fabio, 2007. "Expectations, learning and macroeconomic persistence," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2065-2082, October.
    12. Harrison, Sharon G. & Weder, Mark, 2006. "Did sunspot forces cause the Great Depression?," Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1327-1339, October.
    13. Luca Pensieroso, 2007. "Real Business Cycle Models Of The Great Depression: A Critical Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 21(1), pages 110-142, February.
    14. Marimon, Ramon & Scott, Andrew (ed.), 1999. "Computational Methods for the Study of Dynamic Economies," OUP Catalogue, Oxford University Press, number 9780198294979, Decembrie.
    15. Gauti B. Eggertsson, 2008. "Great Expectations and the End of the Depression," American Economic Review, American Economic Association, vol. 98(4), pages 1476-1516, September.
    16. Carceles-Poveda, Eva & Giannitsarou, Chryssi, 2007. "Adaptive learning in practice," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2659-2697, August.
    17. Peter Temin, 2008. "Real Business Cycle Views of the Great Depression and Recent Events: A Review of Timothy J. Kehoe and Edward C. Prescott's Great Depressions of the Twentieth Century," Journal of Economic Literature, American Economic Association, vol. 46(3), pages 669-684, September.
    18. Harold L. Cole & Lee E. Ohanian, 1999. "The Great Depression in the United States from a neoclassical perspective," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 23(Win), pages 2-24.
    19. Lucas, Robert E., 1977. "Understanding business cycles," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 5(1), pages 7-29, January.
    20. Mark Gertler, 2017. "Rethinking the Power of Forward Guidance: Lessons from Japan Keynote Speech by Mark Gertler," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 35, pages 39-58, November.
    21. Bray, Margaret M & Savin, Nathan E, 1986. "Rational Expectations Equilibria, Learning, and Model Specification," Econometrica, Econometric Society, vol. 54(5), pages 1129-1160, September.
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    Cited by:

    1. Luca Pensieroso & Romain Restout, 2021. "The Gold Standard and the International Dimension of the Great Depression," Working Papers of BETA 2021-21, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    2. Cardi, Olivier & Restout, Romain, 2023. "Sectoral fiscal multipliers and technology in open economy," Journal of International Economics, Elsevier, vol. 144(C).

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    More about this item

    Keywords

    Learning; Great Depression; Dynamic general equilibrium; Bounded rationality;
    All these keywords.

    JEL classification:

    • E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • N10 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - General, International, or Comparative

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