Tractable likelihood-based estimation of non- linear DSGE models

Vol: 
55/2017
Author name: 
Kollmann R
Year: 
2017
Month: 
September
Abstract: 

This paper presents a simple and fast maximum likelihood estimation method for nonlinear DSGE models that are solved using a second- (or higher-) order accurate approximation. The method requires that the number of observables equals the number of exogenous shocks. Exogenous innovations are extracted recursively by inverting the observation equation, which allows easy computation of the likelihood function.

Publication file: 

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