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Managing disinflation under uncertainty

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  • Tesfaselassie, M.F.
  • Schaling, E.

Abstract

In this paper we analyze disinflation policy when a central bank has imperfect information about private sector inflation expectations but learns about them from economic outcomes, which are in part the result of the disinflation policy itself. The form of uncertainty is manifested as uncertainty about the effect of past disinflation policy on the current output gap. This differs from other studies on learning and control in a monetary policy context (e.g., [Ellison, 2006] and [Svensson and Williams, 2007]) that assume uncertainty about the effects of current policy actions on the economy. We derive the central bank's optimal disinflation strategy under active learning (DOP) and compare it with two limiting cases--certainty equivalence policy (CEP), or passive learning, and a Brainard-style cautionary monetary policy (CP). It turns out that under the DOP inflation stays between the levels implied by the CEP and the CP. A novel result--e.g., unlike Beck and Wieland (2002)--is that this holds irrespective of the initial level of inflation. At high levels of inherited inflation the DOP moves closer to the CEP, at low levels of inherited inflation the DOP resembles the CP.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 34 (2010)
Issue (Month): 12 (December)
Pages: 2568-2577

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Handle: RePEc:eee:dyncon:v:34:y:2010:i:12:p:2568-2577

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Web page: http://www.elsevier.com/locate/jedc

Related research

Keywords: Learning Inflation expectations Disinflation policy Separation principle Kalman filter Optimal control Dynamic programming;

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References

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  1. Easley, David & Kiefer, Nicholas M, 1988. "Controlling a Stochastic Process with Unknown Parameters," Econometrica, Econometric Society, vol. 56(5), pages 1045-64, September.
  2. 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.
  3. Wieland, Volker, 2000. "Learning by doing and the value of optimal experimentation," Journal of Economic Dynamics and Control, Elsevier, vol. 24(4), pages 501-534, April.
  4. Mewael F. Tesfaselassie & Eric Schaling & Sylvester Eijffinger, 2007. "Learning About the Term Structure and Optimal Rules for Inflation Targeting," Working Papers 62, Economic Research Southern Africa.
  5. Balvers, Ronald J & Cosimano, Thomas F, 1994. "Inflation Variability and Gradualist Monetary Policy," Review of Economic Studies, Wiley Blackwell, vol. 61(4), pages 721-38, October.
  6. Eric Schaling, 2004. "Learning, inflation expectations and optimal monetary policy," Macroeconomics 0404035, EconWPA.
  7. Bertocchi, Graziella & Spagat, Michael, 1991. "Learning, Experimentation and Monetary Policy," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 1991018, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  8. Bomfim, Antulio N & Rudebusch, Glenn D, 2000. "Opportunistic and Deliberate Disinflation under Imperfect Credibility," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(4), pages 707-21, November.
  9. 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.
  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. Timothy Cogley & Riccardo Colacito & Thomas J. Sargent, 2007. "Benefits from U.S. Monetary Policy Experimentation in the Days of Samuelson and Solow and Lucas," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 67-99, 02.
  12. Noah Williams & Lars E.O. Svensson, 2007. "Bayesian and Adaptive Optimal Policy under Model Uncertainty," 2007 Meeting Papers 446, Society for Economic Dynamics.
  13. Ellison, Martin & Valla, Natacha, 2000. "Learning, uncertainty and central bank activism in an economy with strategic interactions," Working Paper Series 0028, European Central Bank.
  14. Ellison, Martin, 2003. "The Learning Cost of Interest Rate Reversals," CEPR Discussion Papers 4135, C.E.P.R. Discussion Papers.
  15. 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.
  16. James Yetman, 2000. "Probing Potential Output: Monetary Policy, Credibility And Optimal Learning Under Uncertainty," Computing in Economics and Finance 2000 181, Society for Computational Economics.
  17. 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.
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Cited by:
  1. Matthias Neuenkirch & Peter Tillmann, 2012. "Inflation Targeting, Credibility, and Non-Linear Taylor Rules," MAGKS Papers on Economics 201235, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  2. Mewael F. Tesfaselassie, 2008. "Central Bank Learning and Monetary Policy," Kiel Working Papers 1444, Kiel Institute for the World Economy.

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