DSGE models in the frequency domain

We use frequency domain techniques to estimate a medium-scale DSGE model on different frequency bands. We show that goodness of t, forecasting performance and parameter estimates vary substantially with the frequency bands over which the model is estimated. Estimates obtained using subsets of frequencies are characterized by signicantly different parameters, an indication that the model cannot match all frequencies with one set of parameters. In particular, we find that: i) the low frequency properties of the data strongly affect parameter estimates obtained in the time domain; ii) the importance of economic frictions in the model changes when different subsets of frequencies are used in estimation.
This is particularly true for the investment cost friction and habit persistence: when low
frequencies are present in the estimation, the investment cost friction and habit persistence are estimated to be higher than when low frequencies are absent.