The mismatch between the time scale of DSGE models and the data used in their estimation translates into identi cation problems, estimation bias, and distortions in policy analysis. We propose an estimation strategy based on mixed-ferquency data to alleviate these shortcomings. The virtues of our approache are explored for two monetary policy models.
Mixed-frequency structural models: identification, estimation, and policy analysis
MARCELLINO, MASSIMILIANO
2014
Abstract
The mismatch between the time scale of DSGE models and the data used in their estimation translates into identi cation problems, estimation bias, and distortions in policy analysis. We propose an estimation strategy based on mixed-ferquency data to alleviate these shortcomings. The virtues of our approache are explored for two monetary policy models.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
