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Optimal Monetary Policy under Uncertainty in DSGE Models: A Markov Jump-Linear-Quadratic Approach

In: Monetary Policy under Uncertainty and Learning

  • Lars E.O. Svensson

    (Central Bank of Sweden)

  • Noah Williams

    (National Bureau of Economic Research)

We study the design of optimal monetary policy under uncertainty in a dynamic stochastic general equilibrium models. We use a Markov jump-linear-quadratic (MJLQ) approach to study policy design, approximating the uncertainty by different discrete modes in a Markov chain, and by taking mode-dependent linear-quadratic approximations of the underlying model. This allows us to apply a powerful methodology with convenient solution algorithms that we have developed. We apply our methods to a benchmark New Keynesian model, analyzing how policy is affected by uncertainty, and how learning and active experimentation affect policy and losses.

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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 3, pages 077-114, 2009.
This item is provided by Central Bank of Chile in its series Central Banking, Analysis, and Economic Policies Book Series with number v13c03pp077-114.
Handle: RePEc:chb:bcchsb:v13c03pp077-114
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  1. Noah Williams & Lars E.O. Svensson, 2007. "Bayesian and Adaptive Optimal Policy under Model Uncertainty," 2007 Meeting Papers 446, Society for Economic Dynamics.
  2. 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.
  3. Rudebusch, G.D. & Svensson, L.E.O., 1998. "Policy Rules for Inflation Targeting," Papers 637, Stockholm - International Economic Studies.
  4. Martin Ellison & Natacha Valla, 2000. "Learning, Uncertainty And Central Bank Activism In An Economy With Strategic Interactions," Computing in Economics and Finance 2000 183, Society for Computational Economics.
  5. 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.
  6. Wieland, Volker, 2000. "Learning by doing and the value of optimal experimentation," Journal of Economic Dynamics and Control, Elsevier, vol. 24(4), pages 501-534, April.
  7. Mewael F. Tesfaselassie & Eric Schaling & Sylvester Eijffinger, 2007. "Learning About the Term Structure and Optimal Rules for Inflation Targeting," Working Papers 62, Economic Research Southern Africa.
  8. Wieland Volker, 2006. "Monetary Policy and Uncertainty about the Natural Unemployment Rate: Brainard-Style Conservatism versus Experimental Activism," The B.E. Journal of Macroeconomics, De Gruyter, vol. 6(1), pages 1-34, March.
  9. 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.
  10. 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.
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