Estimating DSGE Models with Unknown Data Persistence
46 Pages Posted: 1 Sep 2010
Date Written: March 22, 2010
Recent empirical literature shows that key macro variables such as GDP and productivity display long memory dynamics. For DSGE models, we propose a ‘Generalized’ 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.
Keywords: DSGE Models, Long Memory, Kalman Filter
JEL Classification: C51, C53, E37
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