Forecasting VARs, model selection, and shrinkage

Preview

PDF
Kascha_und_Trenkler_15-07.pdf - Published
Download (376kB)

URL:	https://ub-madoc.bib.uni-mannheim.de/38872
URN:	urn:nbn:de:bsz:180-madoc-388724
Document Type:	Working paper
Year of publication:	2015
The title of a journal, publication series:	Working Paper Series
Volume:	15-07
Place of publication:	Mannheim
Publication language:	English
Institution:	School of Law and Economics > Zeitreihenökonometrie (Trenkler 2007-)
MADOC publication series:	Department of Economics > Working Paper Series
Subject:	330 Economics
Classification:	JEL: C32 , C53 , E47,
Keywords (English):	VAR Models , Forecasting , Model Selection , Shrinkage
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.