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Predicting Private Company Failures in Italy Using Financial and Non‐financial Information

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  • Timothy Wang

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.

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  • Timothy Wang, 2019. "Predicting Private Company Failures in Italy Using Financial and Non‐financial Information," Australian Accounting Review, CPA Australia, vol. 29(1), pages 143-157, March.
    • Handle: RePEc:bla:ausact:v:29:y:2019:i:1:p:143-157
    DOI: 10.1111/auar.12245
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    Cited by:

    1. Yu Zhao & Huaming Du & Qing Li & Fuzhen Zhuang & Ji Liu & Gang Kou, 2022. "A Comprehensive Survey on Enterprise Financial Risk Analysis from Big Data Perspective," Papers 2211.14997, arXiv.org, revised May 2023.

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