Model Selection Criteria for Factor‐Augmented Regressions

27 Pages Posted: 23 Dec 2012

See all articles by Jan J. Groen

Jan J. Groen

Federal Reserve Bank of New York

George Kapetanios

King's College, London

Multiple version iconThere are 2 versions of this paper

Date Written: February 2013

Abstract

Existing dynamic factor selection criteria determine the appropriate number of factors in a large‐dimensional panel of explanatory variables, but not all of these have to be relevant for modeling a specific dependent variable within a factor‐augmented regression. We develop theoretical conditions that selection criteria have to meet in order to get consistent estimates of the relevant factor dimension for such a regression. These incorporate factor estimation error and do not depend on specific factor estimation methodologies. Using this framework, we modify standard model selection criteria, and simulation and empirical applications indicate that these are useful in determining appropriate factor‐augmented regressions.

JEL Classification: C22, C52, E37

Suggested Citation

Groen, Jan J. and Kapetanios, George, Model Selection Criteria for Factor‐Augmented Regressions (February 2013). Oxford Bulletin of Economics and Statistics, Vol. 75, Issue 1, pp. 37-63, 2013, Available at SSRN: https://ssrn.com/abstract=2193208 or http://dx.doi.org/10.1111/j.1468-0084.2012.00721.x

Jan J. Groen (Contact Author)

Federal Reserve Bank of New York ( email )

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HOME PAGE: http://nyfedeconomists.org/groen/

George Kapetanios

King's College, London ( email )

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London, WC2B 4BG
United Kingdom
+44 20 78484951 (Phone)

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