Non-Linear DSGE Models and the Central Difference Kalman Filter
52 Pages Posted: 29 Aug 2010 Last revised: 14 Sep 2011
Date Written: September 14, 2011
This paper introduces a quasi maximum likelihood (QML) approach based on the central difference Kalman filter to estimate non-linear DSGE models with potentially non-Gaussian shocks. We argue that this estimator can be expected to be consistent and asymptotically normal for DSGE models solved up to third order. These properties are verified in a Monte Carlo study for a DSGE model solved to second and third order with structural shocks that are Gaussian, Laplace distributed, or display stochastic volatility.
Keywords: Non-linear filtering, Non-Gaussian shocks, Quasi Maximum Likelihood, Stochastic volatility, Third order perturbation
JEL Classification: C13, C15, E10, E32
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