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Parameter Instability, Model Uncertainty and the Choice of Monetary Policy

  • Favero, Carlo A.
  • Milani, Fabio

This paper starts from the observation that parameter instability and model uncertainty are relevant problems for the analysis of monetary policy in small macroeconomic models. We propose to deal with these two problems by implementing a novel ‘thick recursive modelling’ approach. At each point in time we estimate all models generated by the combinations of a base-set of k observable regressors for aggregate demand and supply. We compute optimal monetary policies for all possible models and consider alternative ways of summarizing their distribution. Our main results show that thick recursive modelling delivers optimal policy rates that track the observed policy rates better than the optimal policy rates obtained under a constant parameter specification, with no role for model uncertainty.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 4909.

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Date of creation: Feb 2005
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Handle: RePEc:cpr:ceprdp:4909
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  1. 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.
  2. Robert J. Tetlow & Peter von zur Muehlen, 2000. "Robust monetary policy with misspecified models: does model uncertainty always call for attenuated policy?," Finance and Economics Discussion Series 2000-28, Board of Governors of the Federal Reserve System (U.S.).
  3. Lars Peter Hansen & Ellen R. McGrattan & Thomas J. Sargent, 1994. "Mechanics of forming and estimating dynamic linear economies," Staff Report 182, Federal Reserve Bank of Minneapolis.
  4. repec:cup:macdyn:v:6:y:2002:i:1:p:85-110 is not listed on IDEAS
  5. Gernot Doppelhofer & Ronald I. Miller & Xavier Sala-i-Martin, 2000. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (Bace) Approach," OECD Economics Department Working Papers 266, OECD Publishing.
  6. Glenn D. Rudebusch & Lars E.O. Svensson, 1999. "Eurosystem monetary targeting: lessons from U.S. data," Working Paper Series 99-13, Federal Reserve Bank of San Francisco.
  7. Brian Sack & Volker Wieland, 1999. "Interest-rate smoothing and optimal monetary policy: a review of recent empirical evidence," Finance and Economics Discussion Series 1999-39, Board of Governors of the Federal Reserve System (U.S.).
  8. Rudebusch, Glenn D., 2002. "Term structure evidence on interest rate smoothing and monetary policy inertia," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1161-1187, September.
  9. Alexei Onatski & James H. Stock, 2000. "Robust Monetary Policy Under Model Uncertainty in a Small Model of the U.S. Economy," NBER Working Papers 7490, National Bureau of Economic Research, Inc.
  10. repec:rus:hseeco:70719 is not listed on IDEAS
  11. Granger, Clive W. J. & Jeon, Yongil, 2004. "Thick modeling," Economic Modelling, Elsevier, vol. 21(2), pages 323-343, March.
  12. Sack, Brian, 2000. "Does the fed act gradually? A VAR analysis," Journal of Monetary Economics, Elsevier, vol. 46(1), pages 229-256, August.
  13. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, September.
  14. Pesaran, M. H. & Timmermann, A., 1996. "A Recursive Modelling Approach to Predicting UK Stock Returns'," Cambridge Working Papers in Economics 9625, Faculty of Economics, University of Cambridge.
  15. Pesaran, M Hashem & Timmermann, Allan, 1995. " Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-28, September.
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