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Learning and the Great Moderation

Author

Listed:
  • Aarti Singh

    (Washington University in St. Louis)

  • James Bullard

    (Federal Reserve Bank of St. Louis)

Abstract

We study a stylized theory of the volatility reduction in the U.S. after 1984---the Great Moderation---which attributes part of the stabilization to less volatile shocks and another part to more difficult inference on the part of Bayesian households attempting to learn the latent state of the economy. We use a standard equilibrium business cycle model with technology following an unobserved regime-switching process. After 1984, according to Kim and Nelson (1999), the variance of U.S. macroeconomic aggregates declined because boom and recession regimes moved closer together, keeping conditional variance unchanged. In our model this makes the signal extraction problem more difficult for Bayesian households, and in response they moderate their behavior, reinforcing the effect of the less volatile stochastic technology and contributing an extra measure of moderation to the economy. We construct example economies in which this learning effect accounts for about 30 percent of a volatility reduction.

Suggested Citation

  • Aarti Singh & James Bullard, 2007. "Learning and the Great Moderation," 2007 Meeting Papers 523, Society for Economic Dynamics.
  • Handle: RePEc:red:sed007:523
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    Cited by:

    1. James B. Bullard, 2009. "Three funerals and a wedding," Review, Federal Reserve Bank of St. Louis, vol. 91(Jan), pages 1-12.
    2. Piero Ferri, 2011. "Macroeconomics of Growth Cycles and Financial Instability," Books, Edward Elgar Publishing, number 14260.
    3. Richard Harrison & George Kapetanios & Alasdair Scott & Jana Eklund, 2008. "Breaks in DSGE models," 2008 Meeting Papers 657, Society for Economic Dynamics.
    4. repec:zbw:rwirep:0509 is not listed on IDEAS
    5. Mathias Klein & Christopher Krause, 2014. "Income Redistribution, Consumer Credit,and Keeping up with the Riches," Ruhr Economic Papers 0509, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    6. Murray, James, 2011. "Learning and judgment shocks in U.S. business cycles," MPRA Paper 29257, University Library of Munich, Germany.
    7. Suda, J., 2013. "Belief shocks and the macroeconomy," Working papers 434, Banque de France.
    8. Emilio Abad-Segura & Mariana-Daniela González-Zamar & Juan C. Infante-Moro & Germán Ruipérez García, 2020. "Sustainable Management of Digital Transformation in Higher Education: Global Research Trends," Sustainability, MDPI, vol. 12(5), pages 1-24, March.
    9. Mathias Klein & Christopher Krause, 2020. "Income Redistribution, Consumer Credit, and Keeping Up with the Riches," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(8), pages 1937-1971, December.
    10. Aguirre, Idoia & Vázquez, Jesús, 2020. "Learning, parameter variability, and swings in US macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 66(C).
    11. Tortorice, Daniel L, 2018. "The business cycle implications of fluctuating long run expectations," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 266-291.
    12. Luigi Bocola & Nils M. Gornemann, 2013. "Risk, economic growth and the value of U.S. corporations," Working Papers 13-10, Federal Reserve Bank of Philadelphia.
    13. Andrew Foerster & Christian Matthes, 2022. "Learning About Regime Change," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1829-1859, November.
    14. Fillon, Romain & Guivarch, Céline & Taconet, Nicolas, 2023. "Optimal climate policy under tipping risk and temporal risk aversion," Journal of Environmental Economics and Management, Elsevier, vol. 121(C).
    15. Gilbert Mbara, 2017. "Business Cycle Dating after the Great Moderation: A Consistent Two – Stage Maximum Likelihood Method," Working Papers 2017-13, Faculty of Economic Sciences, University of Warsaw.
    16. Milani, Fabio, 2014. "Learning and time-varying macroeconomic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 94-114.
    17. James Bullard & Jacek Suda & Aarti Singh & Costas Azariadis, 2014. "Debt Overhang and Monetary Policy," 2014 Meeting Papers 948, Society for Economic Dynamics.
    18. McClung, Nigel, 2020. "E-stability vis-à-vis determinacy in regime-switching models," Journal of Economic Dynamics and Control, Elsevier, vol. 121(C).

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    More about this item

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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