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Monetary Policy with a Wider Information Set: a Bayesian Model Averaging Approach

  • Fabio Milani

    (Princeton University)

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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File URL: http://econwpa.repec.org/eps/mac/papers/0401/0401004.pdf
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Paper provided by EconWPA in its series Macroeconomics with number 0401004.

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Length: 43 pages
Date of creation: 18 Jan 2004
Date of revision:
Handle: RePEc:wpa:wuwpma:0401004
Note: Type of Document - pdf; prepared on Win2000; pages: 43; figures: included
Contact details of provider: Web page: http://econwpa.repec.org

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  1. Lars E. O. Svensson & Michael Woodford, 2000. "Indicator variables for optimal policy," Proceedings, Federal Reserve Bank of San Francisco.
  2. 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.
  3. Glenn Rudebusch & Lars E.O. Svensson, 1999. "Policy Rules for Inflation Targeting," NBER Chapters, in: Monetary Policy Rules, pages 203-262 National Bureau of Economic Research, Inc.
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  8. Sack, Brian & Wieland, Volker, 2000. "Interest-rate smoothing and optimal monetary policy: a review of recent empirical evidence," Journal of Economics and Business, Elsevier, vol. 52(1-2), pages 205-228.
  9. Cogley, Timothy & Sargent, Thomas J., 2005. "The conquest of U.S. inflation: learning and robustness to model uncertainty," Working Paper Series 0478, European Central Bank.
  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.
  11. Robert Tetlow, 2000. "The Fed Is Not As Ignorant As You Think," Computing in Economics and Finance 2000 202, Society for Computational Economics.
  12. 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.
  13. Ben S. Bernanke & Jean Boivin, 2001. "Monetary Policy in a Data-Rich Environment," NBER Working Papers 8379, National Bureau of Economic Research, Inc.
  14. McCallum, Bennett T & Nelson, Edward, 1999. "An Optimizing IS-LM Specification for Monetary Policy and Business Cycle Analysis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 31(3), pages 296-316, August.
  15. Holtham, Gerald & Hughes Hallett, Andrew, 1992. "International Macroeconomic Policy Coordination When Policymakers Do Not Agree on the True Model: Comment," American Economic Review, American Economic Association, vol. 82(4), pages 1043-51, September.
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  17. 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.
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  19. Efrem Castelnuovo, 2004. "Taylor rules, omitted variables, and interest rate smoothing in the US," Macroeconomics 0403009, EconWPA.
  20. Onatski, Alexei & Williams, Noah, 2002. "Modeling model uncertainty," Working Paper Series 0169, European Central Bank.
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  23. Efrem Castelnuovo, 2007. "Taylor Rules And Interest Rate Smoothing In The Euro Area," Manchester School, University of Manchester, vol. 75(1), pages 1-16, 01.
  24. 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.
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  28. repec:cup:macdyn:v:6:y:2002:i:1:p:85-110 is not listed on IDEAS
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