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

Lars Svensson and Noah Williams

No 13892, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: E42 E52 E58 (search for similar items in EconPapers)
Date: 2008-03
New Economics Papers: this item is included in nep-cba, nep-dge, nep-mac, nep-mon and nep-ore
Note: EFG ME
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Citations: View citations in EconPapers (9)

Published as Lars E.O. Svensson & Noah Williams, 2008. "Optimal monetary policy under uncertainty: a Markov jump-linear-quadratic approach," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 275-294.
Published as Lars E.O. Svensson & Noah Williams, 2009. "Optimal Monetary Policy under Uncertainty in DSGE Models: A Markov Jump-Linear-Quadratic Approach," Central Banking, Analysis, and Economic Policies Book Series, in: Klaus Schmidt-Hebbel & Carl E. Walsh & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series (ed.), Monetary Policy under Uncertainty and Learning, edition 1, volume 13, chapter 3, pages 077-114 Central Bank of Chile.

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Related works:
Chapter: Optimal Monetary Policy under Uncertainty in DSGE Models: A Markov Jump-Linear-Quadratic Approach (2009)
Working Paper: Optimal Monetary Policy Under Uncertainty in DSGE Models: A Markov Jump-Linear-Quadratic Approach (2008)
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