Tractable likelihood-based estimation of non- linear DSGE models

Vol: 
CAMA Working Paper 55/2017
Author name: 
Robert Kollmann
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.

Updated:  24 March 2017/Responsible Officer:  Crawford Engagement/Page Contact:  CAP Web Team