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Learning, inflation expectations and optimal monetary policy

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  • Eric Schaling

    (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 EconWPA in its series Macroeconomics with number 0404035.

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Date of creation: 29 Apr 2004
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Handle: RePEc:wpa:wuwpma:0404035

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

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References

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  1. 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.
  2. Wieland, Volker, 2000. "Monetary policy, parameter uncertainty and optimal learning," Journal of Monetary Economics, Elsevier, vol. 46(1), pages 199-228, August.
  3. 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.
  4. 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.
  5. 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.
  6. David Andolfatto & Scott Hendry & Kevin Moran, 2004. "Inflation Expectations and Learning about Monetary Policy," DNB Staff Reports (discontinued) 121, Netherlands Central Bank.
  7. 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.
  8. Bertocchi, Graziella & Spagat, Michael, 1993. "Learning, experimentation, and monetary policy," Journal of Monetary Economics, Elsevier, vol. 32(1), pages 169-183, August.
  9. Eric Schaling, 1999. "The non-linear Phillips curve and inflation forecast targeting," Bank of England working papers 98, Bank of England.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
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Cited by:
  1. 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.
  2. Mewael F. Tesfaselassie & Eric Schaling, 2008. "Managing Disinflation under Uncertainty," Kiel Working Papers 1429, Kiel Institute for the World Economy.
  3. Mewael Tesfaselassie & Eric Schaling & Sylvester Eijffinger, 2004. "Heterogeneous Information about the Term Structure of Interest Rates, Least-Squares Learning and Optimal Interest Rate Rules for Inflation Forecast Targeting," Econometric Society 2004 North American Summer Meetings 78, Econometric Society.
  4. Mewael F. Tesfaselassie, 2008. "Central Bank Learning and Monetary Policy," Kiel Working Papers 1444, Kiel Institute for the World Economy.
  5. Llewellyn, David T. & Mayes , David G., 2003. "The role of market discipline in handling problem banks," Research Discussion Papers 21/2003, Bank of Finland.
  6. 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.

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