Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/129589 
Year of Publication: 
2015
Series/Report no.: 
Working Paper Series No. 15-07
Publisher: 
University of Mannheim, Department of Economics, Mannheim
Abstract: 
This paper provides an empirical comparison of various selection and penalized regression approaches for forecasting with vector autoregressive systems. In particular, we investigate the effect of the system size as well as the effect of various prior specification choices on the relative and overall forecasting performance of the methods. The data set is a typical macroeconomic quarterly data set for the US. We find that these specification choices are crucial for most methods. Conditional on certain choices, the variation across different approaches is relatively small. There are only a few methods which are not competitive under any scenario. For single series, we find that increasing the system size can be helpful - depending on the employed shrinkage method.
Subjects: 
VAR Models
Forecasting
Model Selection
Shrinkage
JEL: 
C32
C53
E47
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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