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- Title
Predicting Private Company Failures in Italy Using Financial and Non‐financial Information.
- Authors
Wang, Timothy
- Abstract
The study assesses the use of non‐financial information in predicting financial distress in private companies by developing credit risk models tailored to Italian private companies. The in‐sample and out‐of‐sample prediction test results are indicative of the incremental predictive ability of the two new non‐financial variables, that is, number of shareholders and number of subsidiaries, over accounting ratios and other widely used non‐financial information, including firm age and industry dummies. To be more specific, number of shareholders and number of subsidiaries are negatively associated with private company failures, and the models augmented by the two non‐financial variables improve forecasting performance from acceptable discrimination to excellent discrimination over one‐ to three‐year time horizons. This study develops financial distress prediction models in the context of Italian private companies. It extends prior studies by investigating the incremental predictive ability of number of shareholders and number of subsidiaries over accounting ratios and other explanatory variables. The study finds that the two new variables improve predictive accuracy from acceptable discrimination to excellent discrimination.
- Subjects
ITALY; PRIVATE companies; DISTRESSED securities; CREDIT risk management; STOCKHOLDERS
- Publication
Australian Accounting Review, 2019, Vol 29, Issue 1, p143
- ISSN
1035-6908
- Publication type
Article
- DOI
10.1111/auar.12245