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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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References

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  1. George W. Evans & Seppo Honkapohja & Noah Williams, 2005. "Generalized Stochastic Gradient Learning," University of Oregon Economics Department Working Papers 2005-17, University of Oregon Economics Department, revised 18 May 2008.
  2. George W. Evans & Seppo Honkapohja, 2002. "Monetary policy; expectations and commitment," Working Paper Series 124, European Central Bank.
  3. James B. Bullard, 2006. "The learnability criterion and monetary policy," Review, Federal Reserve Bank of St. Louis, issue May, pages 203-217.
  4. George W. Evans & Seppo Honkapohja, 2003. "Expectations and the Stability Problem for Optimal Monetary Policies," Review of Economic Studies, Oxford University Press, vol. 70(4), pages 807-824.
  5. Fabio Milani, 2005. "Adaptive Learning and Inflation Persistence," Working Papers 050607, University of California-Irvine, Department of Economics.
  6. 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.
  7. Bennett T. McCallum & Edward Nelson, 2000. "Timeless Perspectives vs. Discretionary Monetary Policy In Forward-Looking Models," NBER Working Papers 7915, National Bureau of Economic Research, Inc.
  8. Bullard, James & Mitra, Kaushik, 2002. "Learning about monetary policy rules," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1105-1129, September.
  9. George Evans & Seppo Honkapohja, 2008. " Expectations, Learning and Monetary Policy: An Overview of Recent Research," CDMA Working Paper Series 0802, Centre for Dynamic Macroeconomic Analysis.
  10. Fabio Milani, 2005. "Expectations, Learning and Macroeconomic Persistence," Macroeconomics 0510022, EconWPA.
  11. Evans George W. & Guesnerie Roger, 1993. "Rationalizability, Strong Rationality, and Expectational Stability," Games and Economic Behavior, Elsevier, vol. 5(4), pages 632-646, October.
  12. Athanasios Orphanides & John C. Williams, 2002. "Imperfect knowledge, inflation expectations, and monetary policy," Working Papers in Applied Economic Theory 2002-04, Federal Reserve Bank of San Francisco.
  13. Sergey Slobodyan & Anna Bogomolova, & Dmitri Kolyuzhnov, 2006. "Stochastic Gradient versus Recursive Least Squares Learning," CERGE-EI Working Papers wp309, The Center for Economic Research and Graduate Education - Economic Institute, Prague.
  14. George W. Evans & Seppo Honkapohja, 2002. "Adaptive Learning and Monetary Policy Design," University of Oregon Economics Department Working Papers 2002-18, University of Oregon Economics Department, revised 04 Mar 2004.
  15. Wiliam Branch & George W. Evans, 2005. "A Simple Recursive Forecasting Model," University of Oregon Economics Department Working Papers 2005-3, University of Oregon Economics Department, revised 01 Feb 2005.
  16. John Duffy & Wei Xiao, 2006. "The Value of Interest Rate Stabilization Policies When Agents are Learning," Working Papers 284, University of Pittsburgh, Department of Economics, revised Oct 2006.
  17. Woodford, M., 1999. "Optimal Monetary Policy Inertia.," Papers 666, Stockholm - International Economic Studies.
  18. Bennett T. McCallum, 1997. "Issues in the Design of Monetary Policy Rules," NBER Working Papers 6016, National Bureau of Economic Research, Inc.
  19. George W. Evans & Seppo Honkapohja, . "Economic Dynamics with Learning: New Stability Results," Computing in Economics and Finance 1997 51, Society for Computational Economics.
  20. Fabio Milani, 2007. "Learning and Time-Varying Macroeconomic Volatility," Working Papers 070802, University of California-Irvine, Department of Economics.
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Cited by:
  1. George Evans & Seppo Honkapohja, 2008. " Expectations, Learning and Monetary Policy: An Overview of Recent Research," CDMA Working Paper Series 0802, Centre for Dynamic Macroeconomic Analysis.
  2. Gasteiger, Emanuel & Zhang, Shoujian, 2011. "Anticipation, learning and welfare: the case of distortionary taxation," MPRA Paper 30625, University Library of Munich, Germany.
  3. 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.

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