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Robust Learning Stability with Operational Monetary Policy Rules

In: Monetary Policy under Uncertainty and Learning

  • George W. Evans

    (University of Oregon)

  • Seppo Honkapohja

    (Centre for Economic Policy Research)

We consider “robust stability†of a rational expectations equilibrium, which we define as stability under discounted (constant gain) least-squares learning, for a range of gain parameters. We find that for operational forms of policy rules, i.e. rules that do not depend on contemporaneous values of endogenous aggregate variables, many interest-rate rules do not exhibit robust stability. 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 reaction functions 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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This chapter was published in: Klaus Schmidt-Hebbel & Carl E. Walsh & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series Editor) (ed.) Monetary Policy under Uncertainty and Learning, , chapter 5, pages 145-170, 2009.
This item is provided by Central Bank of Chile in its series Central Banking, Analysis, and Economic Policies Book Series with number v13c05pp145-170.
Handle: RePEc:chb:bcchsb:v13c05pp145-170
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  1. M. H. Khalil Timamy, 2005. "Debate," Review of African Political Economy, Taylor & Francis Journals, vol. 32(104-105), pages 383-393, June.
  2. Duffy, John & Xiao, Wei, 2004. "The value of interest rate stabilization polices when agents are learning," Working Papers 2004-02, University of New Orleans, Department of Economics and Finance.
  3. George W. Evans & Seppo Honkapohja, 2002. "Monetary Policy, Expectations and Commitment," University of Oregon Economics Department Working Papers 2005-11, University of Oregon Economics Department, revised 06 Apr 2005.
  4. 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.
  5. Fabio Milani, 2005. "Adaptive Learning and Inflation Persistence," Working Papers 050607, University of California-Irvine, Department of Economics.
  6. Milani, Fabio, 2014. "Learning and time-varying macroeconomic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 94-114.
  7. George W. Evans & Seppo Honkapohja, 2001. "Expectations and the Stability Problem for Optimal Monetary Policies," University of Oregon Economics Department Working Papers 2001-6, University of Oregon Economics Department, revised 03 Aug 2001.
  8. Richard Clarida & Jordi Galí & Mark Gertler, 1997. "The science of monetary policy: A new Keynesian perspective," Economics Working Papers 356, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 1999.
  9. 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.
  10. 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.
  11. Woodford, Michael, 2000. "Optimal Monetary Policy Inertia," Seminar Papers 666, Stockholm University, Institute for International Economic Studies.
  12. Evans, G.W. & Honkapohja ,S. & Williams, N., 2005. "Generalized Stochastic Gradient Learning," Cambridge Working Papers in Economics 0545, Faculty of Economics, University of Cambridge.
  13. Branch, William A. & Evans, George W., 2006. "A simple recursive forecasting model," Economics Letters, Elsevier, vol. 91(2), pages 158-166, May.
  14. Evans George W. & Guesnerie Roger, 1993. "Rationalizability, Strong Rationality, and Expectational Stability," Games and Economic Behavior, Elsevier, vol. 5(4), pages 632-646, October.
  15. Bullard, James & Mitra, Kaushik, 2002. "Learning about monetary policy rules," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1105-1129, September.
  16. Fabio Milani, 2005. "Expectations, Learning and Macroeconomic Persistence," Macroeconomics 0510022, EconWPA.
  17. Athanasios Orphanides & John C. Williams, 2002. "Imperfect knowledge, inflation expectations, and monetary policy," Working Paper Series 2002-04, Federal Reserve Bank of San Francisco.
  18. James B. Bullard, 2006. "The learnability criterion and monetary policy," Review, Federal Reserve Bank of St. Louis, issue May, pages 203-217.
  19. George W. Evans & Seppo Honkapohja, 2009. "Learning and Macroeconomics," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 421-451, 05.
  20. 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.
  21. Bennett T. McCallum, 1997. "Issues in the Design of Monetary Policy Rules," NBER Working Papers 6016, National Bureau of Economic Research, Inc.
  22. George W. Evans & Seppo Honkapohja, . "Economic Dynamics with Learning: New Stability Results," Computing in Economics and Finance 1997 51, Society for Computational Economics.
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