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Learning and monetary policy shifts

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  • Frank Schorfheide

Abstract

This paper estimates a dynamic stochastic equilibrium model in which agents use a Bayesian rule to learn about the state of monetary policy. Monetary policy follows a nominal interest rate rule that is subject to regime shifts. The following results are obtained. First, the author's policy regime estimates are consistent with the popular view that policy was marked by a shift to a high-inflation regime in the early 1970s, which ended with Volcker's stabilization policy at the beginning of the 1980s. Second, while Bayesian posterior odds favor the "full-information" version of the model in which agents know the policy regime, the fall of inflation and interest rates in the disinflation episode in the early 1980s is better captured by the delayed response of the "learning" specification. Third, the author examines the magnitude of the expectations-formation effect of monetary policy interventions in the "learning" specification by comparing impulse responses to a version of the model in which agents ignore the information contained in current and past monetary policy shocks about the likelihood of a regime shift.

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Bibliographic Info

Paper provided by Federal Reserve Bank of Atlanta in its series Working Paper with number 2003-23.

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Date of creation: 2003
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Handle: RePEc:fip:fedawp:2003-23

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Keywords: Equilibrium (Economics) ; Monetary policy ; Macroeconomics ; Inflation (Finance) ; Forecasting;

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  1. Christopher Sims & Tao Zha, 2002. "Macroeconomic switching," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  2. Christopher J. Erceg & Andrew T. Levin, 2001. "Imperfect credibility and inflation persistence," Finance and Economics Discussion Series 2001-45, Board of Governors of the Federal Reserve System (U.S.).
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  9. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
  10. Jordi Galí & Mark Gertler, 1998. "Inflation dynamics: A structural econometric analysis," Economics Working Papers 341, Department of Economics and Business, Universitat Pompeu Fabra.
  11. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  12. Andolfatto, David & Scott Hendry & Kevin Moran, 2002. "Inflation Expectations and Learning about Monetary Policy," Working Papers 02-30, Bank of Canada.
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  15. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, 05.
  16. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
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  18. Kozicki, Sharon & Tinsley, P. A., 2001. "Shifting endpoints in the term structure of interest rates," Journal of Monetary Economics, Elsevier, vol. 47(3), pages 613-652, June.
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  23. Frank Schorfheide, 2000. "Loss function-based evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 645-670.
  24. 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.
  25. Thomas Lubik & Frank Schorfheide, 2002. "Testing for Indeterminacy in Linear Rational Expectations Models," Computing in Economics and Finance 2002 214, Society for Computational Economics.
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