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Optimal monetary policy under uncertainty: a Markov jump-linear-quadratic approach

  • Lars E. O. Svensson
  • Noah Williams

This paper studies the design of optimal monetary policy under uncertainty using a Markov jump-linear-quadratic (MJLQ) approach. To approximate the uncertainty that policymakers face, the authors use different discrete modes in a Markov chain and take mode-dependent linear-quadratic approximations of the underlying model. This allows the authors to apply a powerful methodology with convenient solution algorithms that they have developed. They apply their methods to analyze the effects of uncertainty and potential gains from experimentation for two sources of uncertainty in the New Keynesian Phillips curve. The examples highlight that learning may have sizable effects on losses and, although it is generally beneficial, it need not always be so. The experimentation component typically has little effect and in some cases it can lead to attenuation of policy.

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File URL: http://research.stlouisfed.org/publications/review/08/07/Svensson.pdf
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Article provided by Federal Reserve Bank of St. Louis in its journal Review.

Volume (Year): (2008)
Issue (Month): Jul ()
Pages: 275-294

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Handle: RePEc:fip:fedlrv:y:2008:i:jul:p:275-294:n:v.90no.4
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  1. Ellison, Martin, 2006. "The learning cost of interest rate reversals," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1895-1907, November.
  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. Volker W. Wieland, 1996. "Learning by doing and the value of optimal experimentation," Finance and Economics Discussion Series 96-5, Board of Governors of the Federal Reserve System (U.S.).
  4. Ellison, Martin & Valla, Natacha, 2000. "Learning, uncertainty and central bank activism in an economy with strategic interactions," Working Paper Series 0028, European Central Bank.
  5. Kiefer, Nicholas M., 1989. "A value function arising in the economics of information," Journal of Economic Dynamics and Control, Elsevier, vol. 13(2), pages 201-223, April.
  6. Glenn D. Rudebusch & Lars E. O. Svensson, 1998. "Policy Rules for Inflation Targeting," NBER Working Papers 6512, National Bureau of Economic Research, Inc.
  7. 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.
  8. Albert Marcet & Ramon Marimon, 2011. "Recursive Contracts," Economics Working Papers ECO2011/15, European University Institute.
  9. Wieland, Volker, 2003. "Monetary Policy and Uncertainty about the Natural Unemployment Rate," CEPR Discussion Papers 3811, C.E.P.R. Discussion Papers.
  10. Fabrizio Zampolli & Andrew P. Blake, 2005. "Time Consistent Policy in Markov Switching Models," Computing in Economics and Finance 2005 134, Society for Computational Economics.
  11. Fabrizio Zampolli, 2004. "Optimal monetary policy in a regime-switching economy," Computing in Economics and Finance 2004 166, Society for Computational Economics.
  12. Eijffinger, Sylvester C W & Schaling, Eric & Tesfaselassie, Mewael F., 2006. "Learning About the Term Structure and Optimal Rules for Inflation Targeting," CEPR Discussion Papers 5896, C.E.P.R. Discussion Papers.
  13. do Val, Joao B. R. & Basar, Tamer, 1999. "Receding horizon control of jump linear systems and a macroeconomic policy problem," Journal of Economic Dynamics and Control, Elsevier, vol. 23(8), pages 1099-1131, August.
  14. 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.
  15. Lindé, Jesper, 2001. "Estimating New-Keynesian Phillips Curves: A Full Information Maximum Likelihood Approach," Working Paper Series 129, Sveriges Riksbank (Central Bank of Sweden), revised 30 Apr 2001.
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