Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/210038 
Year of Publication: 
2013
Series/Report no.: 
Working Paper No. 2013/15
Publisher: 
Norges Bank, Oslo
Abstract: 
In this paper we show analytically, with simulation experiments and with actual data that a mismatch between the time scale of a DSGE model and that of the time series data used for its estimation generally creates identfication problems, introduces estimation bias and distorts the results of policy analysis. On the constructive side, we prove that the use of mixed frequency data, combined with a proper estimation approach, can alleviate the temporal aggregation bias, mitigate the identfication issues, and yield more reliable policy conclusions. The problems and possible remedy are illustrated in the context of standard structural monetary policy models.
Subjects: 
DSGE models
structural VAR
temporal aggregation
mixed frequency data
identification
estimation
policy analysis
JEL: 
C32
C43
E32
Persistent Identifier of the first edition: 
ISBN: 
978-82-7553-760-5
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Working Paper
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