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

Lars E.O. Svensson () and Noah Williams ()

Working Papers Central Bank of Chile from Central Bank of Chile

Abstract: We study the design of optimal monetary policy under uncertainty in a dynamic stochastic general equilibrium model. We use a Markov jump-linear-quadratic (MJLQ) approach to study policy design, proxying 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 testing affect policy and losses.

Date: 2008-09
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Working Paper: Optimal Monetary Policy under Uncertainty in DSGE Models: A Markov Jump-Linear-Quadratic Approach (2008)
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