The paper considers parameter identification, estimation and inference in medium scale DSGE models from a frequency domain perspective using the framework developed in Qu and Tkachenko (2010). The analysis uses Smets and Wouters (2007) as an illustrative example, motivated by the fact that it...

This paper considers inference and model diagnostics for log-linearized DSGE models allow- ing an unknown subset of parameters to be weakly (including un-) identified. The framework allows for latent state variables, measurement errors and also permits analysis using only part of the spectrum,...

The issue addressed in this paper is that of testing for common breaks across or within equations. Our framework is very general and allows integrated regressors and trends as well as stationary regressors. The null hypothesis is that some subsets of the parameters (either regression coecients...

This paper considers issues related to estimation, inference and computation with multiple structural changes occurring at unknown dates in a system of equations. Changes can occur in the regression coefficients and/or the covariance matrix of the errors. We also allow arbitrary restrictions on...