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Learning and the Great Moderation

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  • 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.

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Bibliographic Info

Paper provided by Society for Economic Dynamics in its series 2007 Meeting Papers with number 523.

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Date of creation: 2007
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Handle: RePEc:red:sed007:523

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  1. Van Nieuwerburgh, Stijn & Veldkamp, Laura, 2006. "Learning asymmetries in real business cycles," Journal of Monetary Economics, Elsevier, vol. 53(4), pages 753-772, May.
  2. Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez, 2006. "Estimating Macroeconomic Models: A Likelihood Approach," NBER Technical Working Papers 0321, National Bureau of Economic Research, Inc.
  3. Michael T. Owyang & Jeremy Piger & Howard J. Wall & Federal Reserve Bank of St. Louis, 2006. "A State-Level Analysis of the Great Moderation," Computing in Economics and Finance 2006 131, Society for Computational Economics.
  4. Margaret M. McConnell & Gabriel Perez Quiros, 1998. "Output fluctuations in the United States: what has changed since the early 1980s?," Staff Reports 41, Federal Reserve Bank of New York.
  5. Giorgio Primiceri & Alejandro Justiniano, 2006. "The Time Varying Volatility of Macroeconomic Fluctuations," 2006 Meeting Papers 353, Society for Economic Dynamics.
  6. Shaghil Ahmed & Andrew Levin & Beth Anne Wilson, 2002. "Recent U.S. macroeconomic stability: good policies, good practices or good luck?," International Finance Discussion Papers 730, Board of Governors of the Federal Reserve System (U.S.).
  7. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 821-852.
  8. Marco Cagetti & Lars Peter Hansen & Thomas Sargent & Noah Williams, 2002. "Robustness and Pricing with Uncertain Growth," Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 363-404, March.
  9. David Andolfatto & Paul Gomme, 1997. "Monetary Policy Regimes and Beliefs," Cahiers de recherche CREFE / CREFE Working Papers 48, CREFE, Université du Québec à Montréal, revised Apr 2001.
  10. Lee Ohanian & Andres Arias & Gary Hansen, 2005. "Why have business cycle fluctuations become less volatile?," 2005 Meeting Papers 927, Society for Economic Dynamics.
  11. Richard Clarida & Jordi Galí & Mark Gertler, 1997. "Monetary policy rules and macroeconomic stability: Evidence and some theory," Economics Working Papers 350, Department of Economics and Business, Universitat Pompeu Fabra, revised May 1999.
  12. Christopher A. Sims & Tao Zha, 2005. "Were There Regime Switches in U.S. Monetary Policy?," Working Papers 92, Princeton University, Department of Economics, Center for Economic Policy Studies..
  13. S. B. Aruoba & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez, 2005. "Comparing Solution Methods for Dynamic Equilibrium Economies," Levine's Bibliography 122247000000000855, UCLA Department of Economics.
  14. Fabio Milani, 2007. "Learning and Time-Varying Macroeconomic Volatility," Working Papers 070802, University of California-Irvine, Department of Economics.
  15. Chang-Jin Kim & Charles Nelson & Jeremy Piger, 2001. "The less volatile U.S. economy: a Bayesian investigation of timing, breadth, and potential explanations," International Finance Discussion Papers 707, Board of Governors of the Federal Reserve System (U.S.).
  16. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
  17. James B. Bullard & John Duffy, 2004. "Learning and structural change in macroeconomic data," Working Papers 2004-016, Federal Reserve Bank of St. Louis.
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Cited by:
  1. Richard Harrison & George Kapetanios & Alasdair Scott & Jana Eklund, 2008. "Breaks in DSGE models," 2008 Meeting Papers 657, Society for Economic Dynamics.
  2. Murray, James, 2011. "Learning and judgment shocks in U.S. business cycles," MPRA Paper 29257, University Library of Munich, Germany.
  3. James Bullard, 2008. "Three funerals and a wedding," Speech 138, Federal Reserve Bank of St. Louis.

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