Selection of Variables in Small Business Failure Analysis
Journal of Quantitative Methods for Economics and Business Administration - Revista de Métodos Cuantitativos para la Economía y la Empresa, 2017, Forthcoming
43 Pages Posted: 5 May 2016 Last revised: 19 Apr 2017
Date Written: April 18, 2017
This paper focuses on one of the most determinant processes in business failure assessment: variable selection. We apply first-level variable selection based on previous literature on SMEs. Next, we perform a statistical variable selection on a sample of 3210 small firms using both mean and median differences. As the resulting variables differ, we run a varied group of business failure assessment methods (linear discriminant analysis, quadratic discriminant analysis, logistic discriminant analysis, kth-nearest-neighbor discriminant analysis, logit, probit, and data envelopment analysis) to identify the implications of using both tests of differences. Our results show that median differences outperform mean differences in selecting variables, and non-parametric methods outperform parametric ones in identifying failed and not-failed firms by avoiding the effects of dispersion and skewness. Additionally, we contribute new evidence on the addition of qualitative information (payment incidents), with previous evidence for SMEs being scarce.
Keywords: Small business failure, Variable selection, Discriminant analysis, Probit/Logit, Data envelopment analysis (DEA)
JEL Classification: G33, L25, G17
Suggested Citation: Suggested Citation