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Learning, inflation expectations and optimal monetary policy


  • Eric Schaling

    (Department of Economics, RAU)


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.

Suggested Citation

  • Eric Schaling, 2004. "Learning, inflation expectations and optimal monetary policy," Macroeconomics 0404035, EconWPA.
  • Handle: RePEc:wpa:wuwpma:0404035 Note: Type of Document - pdf

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    References listed on IDEAS

    1. Wieland, Volker, 2000. "Monetary policy, parameter uncertainty and optimal learning," Journal of Monetary Economics, Elsevier, vol. 46(1), pages 199-228, August.
    2. 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 1306-1322, December.
    3. Andolfatto, David & Scott Hendry & Kevin Moran, 2002. "Inflation Expectations and Learning about Monetary Policy," Staff Working Papers 02-30, Bank of Canada.
    4. Mervyn A. King, 1996. "How should central banks reduce inflation? - Conceptual issues," Economic Review, Federal Reserve Bank of Kansas City, issue Q IV, pages 25-52.
    5. Bertocchi, Graziella & Spagat, Michael, 1993. "Learning, experimentation, and monetary policy," Journal of Monetary Economics, Elsevier, vol. 32(1), pages 169-183, August.
    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. Mervyn A. King, 1996. "How should central banks reduce inflation? conceptual issues," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 53-91.
    8. 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 357-384, March.
    9. Marcet, Albert & Sargent, Thomas J, 1988. "The Fate of Systems with "Adaptive" Expectations," American Economic Review, American Economic Association, vol. 78(2), pages 168-172, May.
    10. James B. Bullard & Eric Schaling, 2001. "New economy-new policy rules," Review, Federal Reserve Bank of St. Louis, issue May, pages 57-66.
    11. 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.
    12. 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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    Cited by:

    1. Llewellyn, David T. & Mayes, David G., 2003. "The role of market discipline in handling problem banks," Research Discussion Papers 21/2003, Bank of Finland.
    2. 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.
    3. Tesfaselassie, M.F. & Schaling, E., 2010. "Managing disinflation under uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 34(12), pages 2568-2577, December.
    4. 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.
    5. repec:eee:reveco:v:50:y:2017:i:c:p:196-244 is not listed on IDEAS
    6. Tesfaselassie, Mewael F., 2008. "Central bank learning and monetary policy," Kiel Working Papers 1444, Kiel Institute for the World Economy (IfW).
    7. 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.

    More about this item


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

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • F33 - International Economics - - International Finance - - - International Monetary Arrangements and Institutions

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