The Potential of Top Management Characteristics for Small Enterprise Default Prediction Modelling

Author: Francesco Ciampi

Abstract: The aim of this study is to verify the potential of top management characteristics for small enterprise (SE) default prediction modelling. Logistic regression was applied to a sample of 423 Italian SEs, as defined in the Base Capital Accords (firms with a turnover below 5 million Euro) in order to develop a SE default prediction model based on both financial ratios and SE top management characteristics. The predictive power of this model was then compared to that of a second model whose predictive variables were exclusively represented by balance sheet financial ratios. The main findings are: i) managerial characteristics significantly improve the SE default prediction accuracy rates; ii) the smaller is a firm the higher is the increase in prediction accuracy that can be obtained by using managerial characteristics as default predictors; iii) SEs belonging to different size groups need to be treated with different prediction models; iv) SE management’s over-confidence in its ability to control the outcome of all events, especially external events, reduces a firm’s capacity to survive.

WSEAS Transactions on Business and Economics, ISSN / E-ISSN: 1109-9526 / 2224-2899, Volume 14, 2017, Art. #41

PDF
DOI
XML
Cite
×
Citation Tools
Francesco Ciampi, "The Potential of Top Management Characteristics for Small Enterprise Default Prediction Modelling," WSEAS Transactions on Business and Economics, vol. 14, pp. 397-408, 2017
Copy to Clipboard
Citation copied to Clipboard

Certification

---