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Learning, inflation expectations and optimal monetary policy

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Author Info

  • Schaling, Eric

    (Department of Economics, RAU)

Abstract

In this paper we analyse disinflation policy in two environments. In the first, the central bank has perfect knowledge, in the sense that it understands and observes the process by which private sector inflation expectations are generated; in the second, the central bank has to learn the private sector inflation forecasting rule. With imperfect knowledge, results depend on the learning scheme that is employed. Here, the learning scheme we investigate is that of least-squares learning (recursive OLS) using the Kalman filter. A novel feature of a learning-based policy – as against the central bank’s disinflation policy under perfect knowledge – is that the degree of monetary accommodation (the extent to which the central bank accommodates private sector inflation expectations) is no longer constant across the disinflation, but becomes state-dependent. This means that the central bank’s behaviour changes during the disinflation as it collects more information.

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Bibliographic Info

Paper provided by Bank of Finland in its series Research Discussion Papers with number 20/2003.

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Length: 53 pages
Date of creation: 18 Aug 2003
Date of revision:
Handle: RePEc:hhs:bofrdp:2003_020

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Postal: Bank of Finland, P.O. Box 160, FI-00101 Helsinki, Finland
Web page: http://www.suomenpankki.fi/en/
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Related research

Keywords: learning; rational expectations; separation principle; Kalman filter; time-varying parameters; optimal control;

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References

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  1. Eric Schaling & Marco Hoeberichts, 2010. "Why Speed Doesn’t Kill: Learning to Believe in Disinflation," De Economist, Springer, vol. 158(1), pages 23-42, April.
  2. Eric Schaling, 1999. "The non-linear Phillips curve and inflation forecast targeting," Bank of England working papers 98, Bank of England.
  3. Ellison, Martin & Valla, Natacha, 2000. "Learning, uncertainty and central bank activism in an economy with strategic interactions," Working Paper Series 0028, European Central Bank.
  4. 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.
  5. Marcet, Albert & Sargent, Thomas J, 1989. "Convergence of Least-Squares Learning in Environments with Hidden State Variables and Private Information," Journal of Political Economy, University of Chicago Press, vol. 97(6), pages 1306-22, December.
  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. Mervyn King, 1996. "How should central banks reduce inflation? - Conceptual issues," Economic Review, Federal Reserve Bank of Kansas City, issue Q IV, pages 25-52.
  8. Bertocchi, Graziella & Spagat, Michael, 1993. "Learning, experimentation, and monetary policy," Journal of Monetary Economics, Elsevier, vol. 32(1), pages 169-183, August.
  9. Marcet, Albert & Sargent, Thomas J, 1988. "The Fate of Systems with "Adaptive" Expectations," American Economic Review, American Economic Association, vol. 78(2), pages 168-72, May.
  10. 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.
  11. Klok, H.J. & Schaik, A.B.T.M. van & Smulders, J.A., 2001. "Economologues: Liber Amicorum voor Theo van de Klundert," Open Access publications from Tilburg University urn:nbn:nl:ui:12-86472, Tilburg University.
  12. Andolfatto, David & Scott Hendry & Kevin Moran, 2002. "Inflation Expectations and Learning about Monetary Policy," Working Papers 02-30, Bank of Canada.
  13. Marcet, Albert & Sargent, Thomas J., 1989. "Convergence of least squares learning mechanisms in self-referential linear stochastic models," Journal of Economic Theory, Elsevier, vol. 48(2), pages 337-368, August.
  14. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
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Citations

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Cited by:
  1. Schaling, E. & Eijffinger, S.C.W. & Tesfaselassie, M.F., 2004. "Heterogeneous Information about the Term Structure of Interest rates, Least-Squares Learning and Optimal Interest Rate Rules for Inflation Forecast Targeting," Discussion Paper 2004-14, Tilburg University, Center for Economic Research.
  2. Mewael F. Tesfaselassie, 2008. "Central Bank Learning and Monetary Policy," Kiel Working Papers 1444, Kiel Institute for the World Economy.
  3. Eijffinger, Sylvester C W & Schaling, Eric & Tesfaselassie, Mewael F., 2004. "Heterogenous Information About the Term Structure of Interest Rates, Least-Squares Learning and Optimal Interest Rate Rules," CEPR Discussion Papers 4279, C.E.P.R. Discussion Papers.
  4. David T. Llewellyn & David G. Mayes, 2004. "The role of market discipline in handling problem banks," Finance 0404020, EconWPA.
  5. Mewael F. Tesfaselassie & Eric Schaling, 2008. "Managing Disinflation under Uncertainty," Kiel Working Papers 1429, Kiel Institute for the World Economy.
  6. 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.

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