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Firm failure processes and components of failure risk: An analysis of European bankrupt firms

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  • Lukason, Oliver
  • Laitinen, Erkki K.

Abstract

This paper aims to extract firm failure processes (FFPs) by using failure risk and rank the importance of failure risk contributors for different stages of FFPs. The dataset is composed of 1234 bankrupt firms from different European countries and three theoretically motivated FFPs are detected. For the dominant FFP found (73% of cases), failure risk becomes high very shortly before bankruptcy is declared. Annual and accumulated profitability are the most important failure risk contributors for these stages of all FFPs, where failure probability exceeds 50%. The obtained results provide important implications for bankruptcy prediction research and practice, especially in terms of identifying the most important financial predictors.

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  • Lukason, Oliver & Laitinen, Erkki K., 2019. "Firm failure processes and components of failure risk: An analysis of European bankrupt firms," Journal of Business Research, Elsevier, vol. 98(C), pages 380-390.
    • Handle: RePEc:eee:jbrese:v:98:y:2019:i:c:p:380-390
    DOI: 10.1016/j.jbusres.2018.06.025
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    4. Wang, Qi & Zhang, Lin & Ma, Qianqun & Wu, Chong, 2024. "The impact of financial risk on boilerplate of key audit matters: Evidence from China," Research in International Business and Finance, Elsevier, vol. 70(PB).
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    6. Montserrat Manzaneque-Lizano & Esteban Alfaro-Cortés & Alba María Priego de la Cruz, 2019. "Stakeholders and Long-Term Sustainability of SMEs. Who Really Matters in Crisis Contexts, and When," Sustainability, MDPI, vol. 11(23), pages 1-27, November.
    7. Keijo Kohv & Oliver Lukason, 2021. "What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains," Risks, MDPI, vol. 9(2), pages 1-19, January.
    8. Gehan A. Mousa & Elsayed A. H. Elamir & Khaled Hussainey, 2022. "Using machine learning methods to predict financial performance: Does disclosure tone matter?," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 19(1), pages 93-112, March.
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    14. Camacho-Miñano, María-del-Mar & Muñoz-Izquierdo, Nora & Pincus, Morton & Wellmeyer, Patricia, 2024. "Are key audit matter disclosures useful in assessing the financial distress level of a client firm?," The British Accounting Review, Elsevier, vol. 56(2).
    15. du Jardin, Philippe, 2021. "Forecasting corporate failure using ensemble of self-organizing neural networks," European Journal of Operational Research, Elsevier, vol. 288(3), pages 869-885.
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    17. Lily Davies & Mark Kattenberg & Benedikt Vogt, 2023. "Predicting Firm Exits with Machine Learning: Implications for Selection into COVID-19 Support and Productivity Growth," CPB Discussion Paper 444, CPB Netherlands Bureau for Economic Policy Analysis.
    18. Ricarda B. Bouncken & Sascha Kraus & Antonio Lucas Ancillo, 2022. "Management in times of crises: reflections on characteristics, avoiding pitfalls, and pathways out," Review of Managerial Science, Springer, vol. 16(7), pages 2035-2046, October.

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