Corporate failure prediction : assessing the accuracy of different bankruptcy prediction models on Maltese SMEs

Abstract

Purpose: The study aims at examining which Maltese economic characteristics best forecast the potential for bankruptcy. The dissertation also tested different bankruptcy models developed through different statistical techniques and assessed their performance when applied to the Maltese context. Design: To tackle the objectives of this study, a quantitative approach was adopted. A paired-sample design was employed comprising of twenty-eight pairs of failed and non-failed local Small and Medium-sized Entities (SMEs). The necessary financial data was extracted from the financial statements of the last three years prior to the submission of the declaration of voluntary dissolution and winding up. Based upon the availability of financial data, the Altman Z”-score Model (2000) and the Zmijewski’s X-score Model (1984) were selected for the scope of this study. Statistical testing was carried out using discriminant analysis and probit regression analysis respectively. This enabled the development of models using a data set which better reflected the local economic environment. Findings: Findings suggest that both models are unstable and sensitive to changes in time periods. Moreover, profitability ratios are identified as the sole contributors in predicting financial distress within the local context. Between the two statistical techniques employed, evidence obtained favours the probit analysis technique for having the better predictive ability amongst local entities. Conclusions: The research concludes that the development of a bankruptcy prediction model using probit regression analysis as a statistical technique is the most suited for Maltese SMEs. Furthermore, the incorporation of profitability ratios in bankruptcy prediction models should yield higher predictive accuracy. Value: The study provides a better understanding of the statistical technique that best incorporates local traits into an effective bankruptcy prediction model specifically developed for Maltese SMEs.