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Learning About the Term Structure and Optimal Rules for Inflation Targeting

Listed author(s):
  • 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: https://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
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
Fax: 31-10-408 9020
Web page: http://www.erim.eur.nl/
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  1. Rudebusch, Glenn D. & Svensson, Lars E. O., 1999. "Eurosystem Monetary Targeting: Lessons from U.S. Data," Working Paper Series 92, Sveriges Riksbank (Central Bank of Sweden).
  2. James B. Bullard & Eric Schaling, 2000. "New economy - new policy rules?," Working Papers 2000-019, Federal Reserve Bank of St. Louis.
  3. Volker W. Wieland, 1999. "Monetary policy, parameter uncertainty and optimal learning," Finance and Economics Discussion Series 1999-48, Board of Governors of the Federal Reserve System (U.S.).
  4. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, September.
  5. 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.
  6. Ellison, Martin & Valla, Natacha, 2000. "Learning, uncertainty and central bank activism in an economy with strategic interactions," Working Paper Series 0028, European Central Bank.
  7. Stephen Pollock, 2002. "Recursive Estimation in Econometrics," Working Papers 462, Queen Mary University of London, School of Economics and Finance.
  8. Thomas Sargent & Noah Williams & Tao Zha, 2009. "The Conquest of South American Inflation," Journal of Political Economy, University of Chicago Press, vol. 117(2), pages 211-256, 04.
  9. Ellison, Martin, 2006. "The learning cost of interest rate reversals," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1895-1907, November.
  10. Levin, Andrew T. & Moessner, Richhild, 2005. "Inflation persistence and monetary policy design: an overview," Working Paper Series 0539, European Central Bank.
  11. 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 361-386, June.
  12. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
  13. Lars E O Svensson, 1996. "Inflation Forecast Targeting: Implementing and Monitoring Inflation Targets," Bank of England working papers 56, Bank of England.
  14. Bullard, James & Mitra, Kaushik, 2002. "Learning about monetary policy rules," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1105-1129, September.
  15. Athanasios Orphanides & John C. Williams, 2003. "Imperfect Knowledge, Inflation Expectations, and Monetary Policy," NBER Working Papers 9884, National Bureau of Economic Research, Inc.
  16. Yetman, James, 2000. "Probing Potential Output: Monetary Policy, Credibility, and Optimal Learning under Uncertainty," Staff Working Papers 00-10, Bank of Canada.
  17. Gaspar, Vítor & Smets, Frank & Vestin, David, 2006. "Adaptive learning, persistence, and optimal monetary policy," Working Paper Series 0644, European Central Bank.
  18. Clarida, R. & Gali, J. & Gertler, M., 1999. "The Science of Monetary Policy: A New Keynesian Perspective," Working Papers 99-13, C.V. Starr Center for Applied Economics, New York University.
  19. 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.
  20. Schaling, Eric & Eijffinger, Sylvester & Tesfaselassie, Mewael, 2004. "Heterogenous information about the term structure, least-squares learning and optimal rules for inflation targeting," Research Discussion Papers 23/2004, Bank of Finland.
  21. Eric Schaling & James Bullard, 2005. "Monetary Policy, Determinacy, and Learnability in the Open Economy," Computing in Economics and Finance 2005 362, Society for Computational Economics.
  22. 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.
  23. Kiefer, Nicholas M & Nyarko, Yaw, 1989. "Optimal Control of an Unknown Linear Process with Learning," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 571-586, August.
  24. James Bullard & Eric Schaling, 2009. "Monetary Policy, Determinacy, and Learnability in a Two-Block World Economy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(8), pages 1585-1612, December.
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