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Robust Learning Stability with Operational Monetary Policy Rules

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  • George W. Evans
  • Seppo Honkapohja

Abstract

We consider robust stability under learning of alternative interest-rate rules. By “robust stability” we mean stability of the rational expectations equilibrium, under discounted (constant gain) least-squares learning, for a range of gain parameters. We find that many interest-rate rules are not robust, in this sense, when operational forms of policy rules are employed. Rules are considered operational if they do not depend on contemporaneous values of endogenous aggregate variables. We consider a variety of interest-rate rules, including instrument rules, optimal reaction functions under discretion or commitment, and rules that approximate optimal policy under commitment. For some of the rules that aim to achieve optimal policy, we allow for an interest-rate stabilization motive in the policy objective. The expectations-based rules proposed in Evans and Honkapohja (2003, 2006) deliver robust learning stability. In contrast, many proposed alternatives become unstable under learning even at small values of the gain parameter.

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Bibliographic Info

Paper provided by Central Bank of Chile in its series Working Papers Central Bank of Chile with number 504.

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Date of creation: Nov 2008
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Handle: RePEc:chb:bcchwp:504

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  1. Michael Woodford, 1999. "Optimal monetary policy inertia," Proceedings, Federal Reserve Bank of San Francisco, Federal Reserve Bank of San Francisco.
  2. Fabio Milani, 2005. "Adaptive Learning and Inflation Persistence," Macroeconomics, EconWPA 0506013, EconWPA.
  3. Evans, George W. & Honkapohja, Seppo, 2002. "Monetary policy, expectations and commitment," Working Paper Series 0124, European Central Bank.
  4. George W. Evans & Seppo Honkapohja, 2003. "Expectations and the Stability Problem for Optimal Monetary Policies," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 70(4), pages 807-824, October.
  5. James Bullard & Kaushik Mitra, 2002. "Learning about monetary policy rules," Working Papers 2000-001, Federal Reserve Bank of St. Louis.
  6. John Duffy & Wei Xiao, 2007. "The Value of Interest Rate Stabilization Policies When Agents Are Learning," Journal of Money, Credit and Banking, Blackwell Publishing, Blackwell Publishing, vol. 39(8), pages 2041-2056, December.
  7. Richard Clarida & Jordi Gali & Mark Gertler, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," NBER Working Papers 7147, National Bureau of Economic Research, Inc.
  8. Branch, William A. & Evans, George W., 2006. "A simple recursive forecasting model," Economics Letters, Elsevier, vol. 91(2), pages 158-166, May.
  9. George W. Evans & Seppo Honkapohja, 2002. "Adaptive Learning and Monetary Policy Design," University of Oregon Economics Department Working Papers, University of Oregon Economics Department 2002-18, University of Oregon Economics Department, revised 04 Mar 2004.
  10. Evans , George W & Honkapohja, Seppo, 2007. "Expectations, learning and monetary policy: an overview of recent research," Research Discussion Papers 32/2007, Bank of Finland.
  11. Evans, G.W. & Guesnerie, R., 1992. "Rationalizability, Strong Rationality and Expectational Stability," DELTA Working Papers 92-03, DELTA (Ecole normale supérieure).
  12. George W. Evans & Seppo Honkapohja & Noah Williams, 2010. "Generalized Stochastic Gradient Learning," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 51(1), pages 237-262, 02.
  13. George W. Evans & Seppo Honkapohja, 2009. "Learning and Macroeconomics," Annual Review of Economics, Annual Reviews, Annual Reviews, vol. 1(1), pages 421-451, 05.
  14. Bennett T. McCallum & Edward Nelson, 2004. "Timeless perspective vs. discretionary monetary policy in forward-looking models," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 43-56.
  15. Fabio Milani, 2005. "Expectations, Learning and Macroeconomic Persistence," Macroeconomics, EconWPA 0510022, EconWPA.
  16. Fabio Milani, 2007. "Learning and Time-Varying Macroeconomic Volatility," Working Papers 070802, University of California-Irvine, Department of Economics.
  17. Evans, George W & Honkapohja, Seppo, 1998. "Economic Dynamics with Learning: New Stability Results," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 65(1), pages 23-44, January.
  18. James B. Bullard, 2006. "The learnability criterion and monetary policy," Review, Federal Reserve Bank of St. Louis, issue May, pages 203-217.
  19. McCallum, Bennett T., 1999. "Issues in the design of monetary policy rules," Handbook of Macroeconomics, Elsevier, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 23, pages 1483-1530 Elsevier.
  20. Sergey Slobodyan & Anna Bogomolova & Dmitri Kolyuzhnov, 2006. "Stochastic Gradient versus Recursive Least Squares Learning," Computing in Economics and Finance 2006 446, Society for Computational Economics.
  21. M. H. Khalil Timamy, 2005. "Debate," Review of African Political Economy, Taylor & Francis Journals, vol. 32(104-105), pages 383-393, June.
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Cited by:
  1. Emanuel, Gasteiger & Shoujian, Zhang, 2013. "Anticipation, Learning and Welfare: the Case of Distortionary Taxation," SIRE Discussion Papers, Scottish Institute for Research in Economics (SIRE) 2013-50, Scottish Institute for Research in Economics (SIRE).
  2. Ippei Fujiwara & Kazuo Fukuda & Ichiro Muto & Yosuke Shigemi & Wataru Takahashi, 2008. "Frontiers in Monetary Theory and Policy: Summary of the 2008 International Conference Organized by the Institute for Monetary and Economic Studies of the Bank of Japan," IMES Discussion Paper Series 08-E-18, Institute for Monetary and Economic Studies, Bank of Japan.
  3. George W. Evans & Seppo Honkapohja, 2008. "Expectations, Learning and Monetary Policy: An Overview of Recent Research," CDMA Working Paper Series 200802, Centre for Dynamic Macroeconomic Analysis.

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