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Monetary Policy With A Wider Information Set: A Bayesian Model Averaging Approach

  • Fabio Milani

Monetary policy has been usually analyzed in the context of small macroeconomic models where central banks are allowed to exploit a limited amount of information. Under these frameworks, researchers typically derive the optimality of aggressive monetary rules, contrasting with the observed policy conservatism and interest rate smoothing. This paper allows the central bank to exploit a wider information set, while taking into account the associated model uncertainty, by employing Bayesian Model Averaging with Markov Chain Model Composition (MC³). In this enriched environment, we derive the optimality of smoother and more cautious policy rates, together with clear gains in macroeconomic efficiency.

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Article provided by Scottish Economic Society in its journal Scottish Journal of Political Economy.

Volume (Year): 55 (2008)
Issue (Month): 1 (02)
Pages: 1-30

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Handle: RePEc:bla:scotjp:v:55:y:2008:i:1:p:1-30
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  1. Alexei Onatski & James H. Stock, 1999. "Robust monetary policy under model uncertainty in a small model of the U.S. economy," Proceedings, Federal Reserve Bank of San Francisco.
  2. Onatski, Alexei & Williams, Noah, 2002. "Modeling model uncertainty," Working Paper Series 0169, European Central Bank.
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  4. Svensson, Lars E. O. & Woodford, Michael, 2003. "Indicator variables for optimal policy," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 691-720, April.
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  7. Christopher A. Sims, 2002. "The Role of Models and Probabilities in the Monetary Policy Process," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2), pages 1-62.
  8. Fabio Milani, 2003. "Adaptive Learning, Model Uncertainty and Monetary Policy Inertia in a Large Information Environment," Computing in Economics and Finance 2003 280, Society for Computational Economics.
  9. Christopher A. Sims, 2001. "Pitfalls of a Minimax Approach to Model Uncertainty," American Economic Review, American Economic Association, vol. 91(2), pages 51-54, May.
  10. Amato, Jeffery D. & Laubach, Thomas, 2003. "Rule-of-thumb behaviour and monetary policy," European Economic Review, Elsevier, vol. 47(5), pages 791-831, October.
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  12. Rudebusch, Glenn D & Svensson, Lars E O, 2000. "Eurosystem Monetary Targeting: Lessons from US Data," CEPR Discussion Papers 2522, C.E.P.R. Discussion Papers.
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  14. Brian P. Sack & Volker W. 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.).
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  16. repec:cup:macdyn:v:6:y:2002:i:1:p:85-110 is not listed on IDEAS
  17. 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.
  18. Athanasios Orphanides, 1998. "Monetary policy rules based on real-time data," Finance and Economics Discussion Series 1998-03, Board of Governors of the Federal Reserve System (U.S.).
  19. Michael Woodford, 2003. "Optimal Interest-Rate Smoothing," Review of Economic Studies, Wiley Blackwell, vol. 70(4), pages 861-886, October.
  20. Sack, Brian, 2000. "Does the fed act gradually? A VAR analysis," Journal of Monetary Economics, Elsevier, vol. 46(1), pages 229-256, August.
  21. Glenn D. Rudebusch, 2001. "Term structure evidence on interest rate smoothing and monetary policy inertia," Working Paper Series 2001-02, Federal Reserve Bank of San Francisco.
  22. Favero, Carlo A. & Milani, Fabio, 2005. "Parameter Instability, Model Uncertainty and the Choice of Monetary Policy," CEPR Discussion Papers 4909, C.E.P.R. Discussion Papers.
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