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Learning and the Great Moderation

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  • Bullard, James
  • Singh, Aarti

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 (1999a), 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 of the magnitude observed in the postwar U.S. data.

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File URL: http://hdl.handle.net/2123/7092
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Bibliographic Info

Paper provided by University of Sydney, School of Economics in its series Working Papers with number 2009-01.

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Date of creation: Feb 2009
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Handle: RePEc:syd:wpaper:2123/7092

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Keywords: business cycles; regime-switching; Bayesian learning; information;

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References

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  1. Owyang, Michael T. & Piger, Jeremy & Wall, Howard J., 2008. "A state-level analysis of the Great Moderation," Regional Science and Urban Economics, Elsevier, vol. 38(6), pages 578-589, November.
  2. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez, 2006. "Estimating Macroeconomic Models: A Likelihood Approach," Levine's Bibliography 122247000000000849, UCLA Department of Economics.
  3. 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..
  4. David Andolfatto & Paul Gomme, 2001. "Monetary policy regimes and beliefs," Working Paper 9905, Federal Reserve Bank of Cleveland.
  5. Richard Clarida & Jordi Gali & Mark Gertler, 1998. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," NBER Working Papers 6442, National Bureau of Economic Research, Inc.
  6. Fabio Milani, 2007. "Learning and Time-Varying Macroeconomic Volatility," Working Papers 070802, University of California-Irvine, Department of Economics.
  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. Margaret M. McConnell & Gabriel Perez Quiros, 1997. "Output fluctuations in the United States: what has changed since the early 1980s?," Research Paper 9735, Federal Reserve Bank of New York.
  9. James B. Bullard & John Duffy, 2004. "Learning and structural change in macroeconomic data," Working Papers 2004-016, Federal Reserve Bank of St. Louis.
  10. 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.
  11. 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.).
  12. Van Nieuwerburgh, Stijn & Veldkamp, Laura, 2006. "Learning asymmetries in real business cycles," Journal of Monetary Economics, Elsevier, vol. 53(4), pages 753-772, May.
  13. S. Boragan Aruoba & Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez, 2003. "Comparing Solution Methods for Dynamic Equilibrium Economies," PIER Working Paper Archive 04-003, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  14. Giorgio Primiceri & Alejandro Justiniano, 2006. "The Time Varying Volatility of Macroeconomic Fluctuations," 2006 Meeting Papers 353, Society for Economic Dynamics.
  15. Andres Arias & Gary D. Hansen & Lee E. Ohanian, 2006. "Why Have Business Cycle Fluctuations Become Less Volatile?," NBER Working Papers 12079, National Bureau of Economic Research, Inc.
  16. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  17. 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.
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Cited by:
  1. Murray, James, 2011. "Learning and judgment shocks in U.S. business cycles," MPRA Paper 29257, University Library of Munich, Germany.
  2. James Bullard, 2008. "Three funerals and a wedding," Speech 138, Federal Reserve Bank of St. Louis.
  3. Richard Harrison & George Kapetanios & Alasdair Scott & Jana Eklund, 2008. "Breaks in DSGE models," 2008 Meeting Papers 657, Society for Economic Dynamics.

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