On Determining the Importance of a Regressor with Small and Undersized Samples

University of Aarhus Department of Economics Working Paper No. 2006-8

42 Pages Posted: 18 Jun 2008

See all articles by Peter S. Jensen

Peter S. Jensen

University of Southern Denmark - Department of Business and Economics

Allan Wurtz

Aarhus University - Department of Economics and Business Economics

Date Written: 16-08-2006

Abstract

A problem encountered in, for instance, growth empirics is that the number of explanatory variables is large compared to the number of observations. This makes it infeasible to condition on all variables in order to determine the importance of a variable of interest. We prove identifying assumptions under which the problem is not ill-posed. Under these assumptions, we derive properties of the most commonly used methods: Extreme bounds analysis, Sala-i-Martin's method, BACE, generalto-specific, minimum t-statistics, BIC and AIC. We propose a new method and show that it has good finite sample properties.

Keywords: AIC, BACE, BIC, extreme bounds analysis, general-to-specific, identification

JEL Classification: C12, C51, C52

Suggested Citation

Jensen, Peter S. and Wurtz, Allan, On Determining the Importance of a Regressor with Small and Undersized Samples (16-08-2006). University of Aarhus Department of Economics Working Paper No. 2006-8, Available at SSRN: https://ssrn.com/abstract=1147067 or http://dx.doi.org/10.2139/ssrn.1147067

Peter S. Jensen (Contact Author)

University of Southern Denmark - Department of Business and Economics ( email )

Campusvej 55
DK-5230 Odense M, 5230
Denmark

HOME PAGE: http://www.sam.sdu.dk/staff/psj

Allan Wurtz

Aarhus University - Department of Economics and Business Economics ( email )

Universitetsparken
Building 350
DK-8000 Aarhus C
Denmark
+45 8942 1133 (Phone)
+45 8613 6334 (Fax)

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