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An analysis of the determinants of financial distress in Italy: A competing risks approach

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  • Amendola, Alessandra
  • Restaino, Marialuisa
  • Sensini, Luca

Abstract

This paper investigates the influence and the effect of micro-economic indicators and firm-specific factors on different states of financial distress. In particular, a competing risks model is estimated taking into account the differences among variables leading firms to exit the market through bankruptcy, liquidation and inactivity. The determinants of financial distress for any exit route are identified on the basis of the influence on the hazard ratios of the significant variables selected for each state. Furthermore, the predictive performance of the competing-risks model over the single-risk framework is evaluated, with respect to different time windows, by means of some accuracy measures. The results reached on a sample of Italian firms provide support for the hypothesis that the factors influencing firms' way out strongly depend on the exit routes and highlighting the need to distinguish among them by means of a multiple-state approach.

Suggested Citation

  • Amendola, Alessandra & Restaino, Marialuisa & Sensini, Luca, 2015. "An analysis of the determinants of financial distress in Italy: A competing risks approach," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 33-41.
    • Handle: RePEc:eee:reveco:v:37:y:2015:i:c:p:33-41
    DOI: 10.1016/j.iref.2014.10.012
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    2. Ben Jabeur, Sami, 2017. "Bankruptcy prediction using Partial Least Squares Logistic Regression," Journal of Retailing and Consumer Services, Elsevier, vol. 36(C), pages 197-202.
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    4. Marialuisa Restaino & Marco Bisogno, 2019. "A Business Failure Index Using Rank Transformation," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(1), pages 56-65, January.
    5. Mateusz Heba & Marcin Chlebus, 2020. "Impact of using industry benchmark financial ratios on performance of bankruptcy prediction logistic regression model," Working Papers 2020-30, Faculty of Economic Sciences, University of Warsaw.
    6. Şaban Çelik & Bora Aktan & Bruce Burton, 2022. "Firm dynamics and bankruptcy processes: A new theoretical model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 567-591, April.
    7. Tian, Shaonan & Yu, Yan, 2017. "Financial ratios and bankruptcy predictions: An international evidence," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 510-526.
    8. Mselmi, Nada & Lahiani, Amine & Hamza, Taher, 2017. "Financial distress prediction: The case of French small and medium-sized firms," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 67-80.
    9. Fedorova, Elena & Ledyaeva, Svetlana & Drogovoz, Pavel & Nevredinov, Alexandr, 2022. "Economic policy uncertainty and bankruptcy filings," International Review of Financial Analysis, Elsevier, vol. 82(C).
    10. A. N. Adi & Z. Baridwan & E. Mardiati, 2018. "Profitability, Liquidity, Leverage and Corporate Governance Impact on Financial Statement Fraud and Financial Distress as Intervening Variable," Вестник Киевского национального университета имени Тараса Шевченко. Экономика., Socionet;Киевский национальный университет имени Тараса Шевченко, vol. 5(200), pages 66-74.
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    More about this item

    Keywords

    Financial distress; Firm's exit; Competing risks model; Forecasting;
    All these keywords.

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance

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