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On determining the importance of a regressor with small and undersized samples

Research output: Working paperResearch

  • Afdeling for Nationaløkonomi
A problem encountered in, for instance, growth empirics is that the number ofexplanatory variables is large compared to the number of observations. This makesit infeasible to condition on all variables in order to determine the importance of avariable of interest. We prove identifying assumptions under which the problem isnot ill-posed. Under these assumptions, we derive properties of the most commonlyused methods: Extreme bounds analysis, Sala-i-Martin's method, BACE, generalto-specific, minimum t-statistics, BIC and AIC. We propose a new method and showthat it has good finite sample properties.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages39
Publication statusPublished - 2006

    Research areas

  • AIC, BACE, BIC, extreme bounds analysis, general-t

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