Tractable Likelihood-Based Estimation of Non- Linear DSGE Models

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.