A retail failure prediction model

Abstract

Financial ratios have long been used for business analysis. Researchers have formulated business failure prediction models utilizing financial ratios. This study focuses on the use of financial ratios to discriminate between failed and non-failed firms in the retail industry. Using a matched sample of sixty-six failed and sixty-six non-failed retail firms obtained from the COMPUSTAT database, multiple discriminant analysis was utilized to develop a retail prediction model which accurately classified 78 per cent of the sample firms as failed or non-failed. Hotelling's T 2 test determined that the mean vector of the discriminant function for failed firms differed from that of non-failed firms. The model was further validated using a jackknife procedure and split sample analysis. Failed or non-failed classification accuracy was found to be significantly better than chance.