Estimating DSGE models with unknown data persistence
Recent empirical literature shows that key macro variables such as GDP and productivity display long memory dynamics. For DSGE models, we propose a ï¿½Generalizedï¿½ Kalman Filter to deal effectively with this problem: our method connects to and innovates upon data-filtering techniques already used in the DSGE literature. We show our method produces more plausible estimates of the deep parameters as well as more accurate out-of-sample forecasts of macroeconomic data.
|Date of creation:||Mar 2010|
|Date of revision:|
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