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Learning About the Term Structure and Optimal Rules for Inflation Targeting

  • Tesfaselassie, M.F.
  • Schaling, E.
  • Eijffinger, S.C.W.

In this paper we incorporate the term structure of interest rates in a standard inflation forecast targeting framework. We find that under flexible inflation targeting and uncertainty in the degree of persistence in the economy, allowing for active learning possibilities has effects on the optimal interest rate rule followed by the central bank. For a wide range of possible initial beliefs about the unknown parameter, the dynamically optimal rule is in general more activist, in the sense of responding aggressively to the state of the economy, than the myopic rule for small to moderate deviations of the state variable from its target. On the other hand, for large deviations, the optimal policy is less activist than the myopic and the certainty equivalence policies.

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File URL: http://repub.eur.nl/pub/8042/ERS-2006-058-F&A.pdf
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Paper provided by Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam in its series ERIM Report Series Research in Management with number ERS-2006-058-F&A.

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Date of creation: 30 Oct 2006
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Handle: RePEc:ems:eureri:8042
Contact details of provider: Postal: RSM Erasmus University & Erasmus School of Economics, PoBox 1738, 3000 DR Rotterdam
Phone: 31-10-408 1182
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  1. Athanasios Orphanides & John Williams, 2004. "Imperfect Knowledge, Inflation Expectations, and Monetary Policy," NBER Chapters, in: The Inflation-Targeting Debate, pages 201-246 National Bureau of Economic Research, Inc.
  2. Eijffinger, Sylvester C W & Schaling, Eric & Verhagen, Willem, 2000. "The Term Structure of Interest Rates and Inflation Forecast Targeting," CEPR Discussion Papers 2375, C.E.P.R. Discussion Papers.
  3. 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.
  4. Wieland, Volker, 2000. "Monetary policy, parameter uncertainty and optimal learning," Journal of Monetary Economics, Elsevier, vol. 46(1), pages 199-228, August.
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  6. Ellison, Martin & Valla, Natacha, 2001. "Learning, uncertainty and central bank activism in an economy with strategic interactions," Journal of Monetary Economics, Elsevier, vol. 48(1), pages 153-171, August.
  7. Richard Clarida & Jordi Gali & Mark Gertler, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," NBER Working Papers 7147, National Bureau of Economic Research, Inc.
  8. Thomas Sargent & Noah Williams & Tao Zha, 2006. "The conquest of South American inflation," Working Paper 2006-20, Federal Reserve Bank of Atlanta.
  9. James Bullard & Kaushik Mitra, 2002. "Learning about monetary policy rules," Working Papers 2000-001, Federal Reserve Bank of St. Louis.
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  11. Vitor Gaspar & Frank Smets & David Vestin, 2006. "Adaptive Learning, Persistence, and Optimal Monetary Policy," Journal of the European Economic Association, MIT Press, vol. 4(2-3), pages 376-385, 04-05.
  12. Levin, Andrew T. & Moessner, Richhild, 2005. "Inflation persistence and monetary policy design: an overview," Working Paper Series 0539, European Central Bank.
  13. James B. Bullard & Eric Schaling, 2006. "Monetary policy, determinacy, and learnability in a two-block world economy," Working Papers 2006-038, Federal Reserve Bank of St. Louis.
  14. Yetman, James, 2003. "Probing potential output: Monetary policy, credibility, and optimal learning under uncertainty," Journal of Macroeconomics, Elsevier, vol. 25(3), pages 311-330, September.
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  16. Bullard, James & Schaling, Eric, 2006. "Monetary policy, determinacy, and learnability in the open economy," Working Paper Series 0611, European Central Bank.
  17. Schaling, Eric, 2004. "The Nonlinear Phillips Curve and Inflation Forecast Targeting: Symmetric versus Asymmetric Monetary Policy Rules," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(3), pages 361-86, June.
  18. Beck, Gunter W. & Wieland, Volker, 2002. "Learning and control in a changing economic environment," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1359-1377, August.
  19. Stephen Pollock, 2002. "Recursive Estimation in Econometrics," Working Papers 462, Queen Mary University of London, School of Economics and Finance.
  20. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, June.
  21. Schaling , Eric & Eijffinger , Sylvester & Tesfaselassie , Mewael, 2004. "Heterogeneous information about the term structure, least-squares learning and optimal rules for inflation targeting," Research Discussion Papers 23/2004, Bank of Finland.
  22. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
  23. James B. Bullard, 1991. "Learning, rational expectations and policy: a summary of recent research," Review, Federal Reserve Bank of St. Louis, issue Jan, pages 50-60.
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