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Managing Disinflation under Uncertainty

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  • Mewael F. Tesfaselassie
  • Eric Schaling

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 ofpastdisinflation 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

Paper provided by Economic Research Southern Africa in its series Working Papers with number 145.

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Date of creation: 2009
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Handle: RePEc:rza:wpaper:145

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Keywords: Learning; Inflation Expectations; Disinflation Policy; Separation Principle; Kalman Filter; Optimal Control; Dynamic Programming;

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References

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  1. Tesfaselassie, M.F. & Schaling, E. & Eijffinger, S.C.W., 2006. "Learning about the Term Structure and Optimal Rules for Inflation Targeting," Discussion Paper, Tilburg University, Center for Economic Research 2006-88, Tilburg University, Center for Economic Research.
  2. Lars E.O. Svensson & Noah M. Williams, 2007. "Bayesian and Adaptive Optimal Policy under Model Uncertainty," NBER Working Papers 13414, National Bureau of Economic Research, Inc.
  3. Easley, David & Kiefer, Nicholas M, 1988. "Controlling a Stochastic Process with Unknown Parameters," Econometrica, Econometric Society, Econometric Society, vol. 56(5), pages 1045-64, September.
  4. Bomfim, Antulio N & Rudebusch, Glenn D, 2000. "Opportunistic and Deliberate Disinflation under Imperfect Credibility," Journal of Money, Credit and Banking, Blackwell Publishing, Blackwell Publishing, vol. 32(4), pages 707-21, November.
  5. Eric Schaling, 2004. "Learning, inflation expectations and optimal monetary policy," Macroeconomics, EconWPA 0404035, EconWPA.
  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. Balvers, Ronald J & Cosimano, Thomas F, 1994. "Inflation Variability and Gradualist Monetary Policy," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 61(4), pages 721-38, October.
  8. Ellison, Martin, 2006. "The learning cost of interest rate reversals," Journal of Monetary Economics, Elsevier, Elsevier, vol. 53(8), pages 1895-1907, November.
  9. Yetman, James, 2000. "Probing Potential Output: Monetary Policy, Credibility, and Optimal Learning under Uncertainty," Working Papers, Bank of Canada 00-10, Bank of Canada.
  10. Beck, Gunter W. & Wieland, Volker, 2002. "Learning and control in a changing economic environment," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 26(9-10), pages 1359-1377, August.
  11. Marcet, Albert & Sargent, Thomas J, 1988. "The Fate of Systems with "Adaptive" Expectations," American Economic Review, American Economic Association, American Economic Association, vol. 78(2), pages 168-72, May.
  12. Volker Wieland, 1996. "Learning by doing and the value of optimal experimentation," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 96-5, Board of Governors of the Federal Reserve System (U.S.).
  13. Bertocchi, Graziella & Spagat, Michael, 1993. "Learning, experimentation, and monetary policy," Journal of Monetary Economics, Elsevier, Elsevier, vol. 32(1), pages 169-183, August.
  14. 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, Blackwell Publishing, vol. 39(s1), pages 67-99, 02.
  15. Martin Ellison & Natacha Valla, 2000. "Learning, Uncertainty And Central Bank Activism In An Economy With Strategic Interactions," Computing in Economics and Finance 2000, Society for Computational Economics 183, Society for Computational Economics.
  16. Eric Schaling & Marco Hoeberichts, 2010. "Why Speed Doesn’t Kill: Learning to Believe in Disinflation," De Economist, Springer, Springer, vol. 158(1), pages 23-42, April.
  17. 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, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 571-86, August.
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Cited by:
  1. Neuenkirch, Matthias & Tillmann, Peter, 2014. "Inflation targeting, credibility, and non-linear Taylor rules," Journal of International Money and Finance, Elsevier, Elsevier, vol. 41(C), pages 30-45.
  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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