One of the leading methods of estimating the structural parameters of DSGE models is the VAR-based impulse response … both weakly and strongly identified DSGE model parameters. We also show that under our assumptions special care is needed …

(DSGE) models that are solved using a second-order accurate approximation. I apply the Kalman filter to a state …-space representation of the second-order solution based on the ‘pruning’ scheme of Kim, Kim, Schaumburg and Sims (2008). By contrast to …

This paper develops a general perturbation methodology for constructing high-order approximations to the solutions of … Markov-switching DSGE models. We introduce an important and practical idea of partitioning the Markov-switching parameter …

(DSGE) models with recursive preferences such as those in Epstein and Zin (1989 and 1991). Models with these preferences …-order perturbation, Chebyshev polynomials, and value function iteration. We document the performance of the methods in terms of computing … time, implementation complexity, and accuracy. Our main finding is that a third-order perturbation is competitive in terms …

The Paper studies the inflation rate associated with optimal monetary policy in a standard suite of DSGE models, when …

frequentist confidence sets will not coincide asymptotically. This means that Bayesian DSGE estimation should not be interpreted … distribution. As an alternative, we develop new frequentist confidence sets for structural DSGE model parameters that remain …

Using Monte Carlo experiments, we examine the performance of indirect inference tests of DSGE models in small samples …