Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/209952
Authors: 
Maih, Junior
Year of Publication: 
2010
Series/Report no.: 
Working Paper No. 2010/07
Publisher: 
Norges Bank, Oslo
Abstract: 
New-generation DSGE models are sometimes misspecified in dimensions that matter for their forecasting performance. The paper suggests one way to improve the forecasts of a DSGE model using a conditioning information that need not be accurate. The technique presented allows for agents to anticipate the information on the conditioning variables several periods ahead. It also allows the forecaster to apply a continuum of degrees of uncertainty around the mean of the conditioning information, making hard-conditional and unconditional forecasts special cases. An application to a small open-economy DSGE model shows that the benefits of conditioning depend crucially on the ability of the model to capture the correlation between the conditioning information and the variables of interest.
Subjects: 
DSGE model
conditional forecast
JEL: 
C53
F47
Persistent Identifier of the first edition: 
ISBN: 
978-82-7553-553-3
Creative Commons License: 
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.no
Document Type: 
Working Paper
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