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

Author

Listed:
  • Ana García-Gallego
  • María-Jesús Mures-Quintana
  • M. Eva Vallejo-Pascual

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.

Suggested Citation

  • Ana García-Gallego & María-Jesús Mures-Quintana & M. Eva Vallejo-Pascual, 2015. "Forecasting statistical methods in business: a comparative study of discriminant and logit analysis in predicting business failure," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 17(1), pages 76-92.
    • Handle: RePEc:ids:gbusec:v:17:y:2015:i:1:p:76-92
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