In our study, logistic regression was applied to a sample of 760 Italian small enterprises (SEs) in order to test the accuracy of a company default prediction model based on both economic-financial ratios and variables regarding managerial characteristics. We then compared the results obtained to those from a similar model which used only economic-financial ratios. Our results show that: i) the model based on both financial ratios and managerial characteristics has a higher accuracy; ii) when logistic regression is applied separately according to size, geographical area and business sector, both models are significantly more accurate than when the decisional function is calculated on the aggregate sample; and iii) the greatest increase in accuracy (in point ii) is obtained when the decisional function is calculated separately according to firm size. These results suggest that including managerial variables gives a marked improvement to a SE default prediction model's success rate.

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Using Variables Regarding Managerial Characteristics for Small Enterprise Failure Prediction Modeling. Statistical Evidence from Italian Small Firms

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en

Release

2013

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About the Author

Francesco Ciampi

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