Forecasting statistical methods in business: a comparative study of discriminant and logit analysis in predicting business failure

Ana García-Gallego, María-Jesús Mures-Quintana and M. Eva Vallejo-Pascual

Global Business and Economics Review, 2015, vol. 17, issue 1, 76-92

Abstract: The application of statistics in business is essential in order to make decisions in a rigorous and reliable way. One of the fields where forecasting methods are important focuses on business failure. In a comparative study, discriminant analysis and logistic regression are applied on a sample of small and medium-sized firms with head offices in Castilla y León (Spain) in order to predict business failure using a set of financial ratios as independent variables to enter the corresponding models. The achieved results show that there are some differences in the variables becoming significant in each method, but factors related to resources generation are common to both. The classification results reveal that the two methods are appropriate to predict business failure, but logistic regression turns out to be somewhat better, since the percentages of correctly classified firms are higher.

Keywords: forecasting; statistical methods; comparison; discriminant analysis; logit analysis; logistic regression; Spain; financial ratios; business failure; bankruptcy; firm classification; failure prediction; statistics; small and medium-sized enterprises; SMEs; SME failure; resource generation. (search for similar items in EconPapers)
Date: 2015
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