Exact Likelihood Computation For Nonlinear DSGE Models With Heteroskedastic Innovations
Phenomena such as the Great Moderation have increased the attention of macro-economists towards models where shock processes are not (log-) normal. This paper studies a class of discrete-time rational expectations models where the variance of exogenous innovations is subject to stochastic regime shifts. The authors first show that, up to a second-order approximation using perturbation methods, regime switching in the variances has an impact only on the intercept coefficients of the decision rules. They then demonstrate how to derive the exact model likelihood for the second-order approximation of the solution when there are as many shocks as observable variables.