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Learning About the Term Structure and Optimal Rules for Inflation Targeting

  • Eijffinger, Sylvester C W
  • Schaling, Eric
  • Tesfaselassie, Mewael F.

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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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 5896.

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Date of creation: Oct 2006
Date of revision:
Handle: RePEc:cpr:ceprdp:5896
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  1. Mark Gertler & Jordi Gali & Richard Clarida, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," Journal of Economic Literature, American Economic Association, vol. 37(4), pages 1661-1707, December.
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  4. James Bullard & Kaushik Mitra, 2002. "Learning about monetary policy rules," Working Papers 2000-001, Federal Reserve Bank of St. Louis.
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  6. Wieland, Volker, 1999. "Monetary policy, parameter uncertainty and optimal learning," ZEI Working Papers B 09-1999, ZEI - Center for European Integration Studies, University of Bonn.
  7. 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.
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  13. Martin Ellison & Natacha Valla, 2000. "Learning, Uncertainty And Central Bank Activism In An Economy With Strategic Interactions," Computing in Economics and Finance 2000 183, Society for Computational Economics.
  14. Levin, Andrew T. & Moessner, Richhild, 2005. "Inflation persistence and monetary policy design: an overview," Working Paper Series 0539, European Central Bank.
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  17. Gaspar, Vítor & Smets, Frank & Vestin, David, 2006. "Adaptive learning, persistence, and optimal monetary policy," Working Paper Series 0644, European Central Bank.
  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. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
  20. 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.
  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. Stephen Pollock, 2002. "Recursive Estimation in Econometrics," Working Papers 462, Queen Mary University of London, School of Economics and Finance.
  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 571-86, August.
  24. 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.
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