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Modelling corporate failure: A multinomial nested logit analysis for unordered outcomes

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  • Jones, Stewart
  • Hensher, David A.

Abstract

This study evaluates the theoretical and empirical significance of the multinomial nested logit (NL) model as an advanced closed-form model for the explanation and prediction of firm financial distress. Using a four-state failure model based on Australian company samples, we estimate an NL model and test its predictive performance on a holdout sample. Comparison of model fits and out-of-sample forecasts indicate that the unordered NL model statistically outperforms a standard logit model by substantial margins. NL may even be used as an effective practical alternative to more advanced open-form models such as mixed logit in the modelling of firm financial distress.

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  • Jones, Stewart & Hensher, David A., 2007. "Modelling corporate failure: A multinomial nested logit analysis for unordered outcomes," The British Accounting Review, Elsevier, vol. 39(1), pages 89-107.
    • Handle: RePEc:eee:bracre:v:39:y:2007:i:1:p:89-107
    DOI: 10.1016/j.bar.2006.12.003
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    3. Balcaen,S. & Buyze, J. & Ooghe,H., 2009. "Financial distress and firm exit: determinants of involuntary exits, voluntary liquidations and restructuring exits," Vlerick Leuven Gent Management School Working Paper Series 2009-21, Vlerick Leuven Gent Management School.
    4. Zhao, Qi & Xu, Weijun & Ji, Yucheng, 2023. "Predicting financial distress of Chinese listed companies using machine learning: To what extent does textual disclosure matter?," International Review of Financial Analysis, Elsevier, vol. 89(C).
    5. Sofie Balcaen & Sophie Manigart & Jozefien Buyze & Hubert Ooghe, 2012. "Firm exit after distress: differentiating between bankruptcy, voluntary liquidation and M&A," Small Business Economics, Springer, vol. 39(4), pages 949-975, November.
    6. Stewart Jones & David A. Hensher, 2007. "Evaluating the Behavioural Performance of Alternative Logit Models: An Application to Corporate Takeovers Research," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 34(7‐8), pages 1193-1220, September.
    7. Anton Gerunov, 2023. "Modern Approaches To Forecasting Firm Default Rates Over The Short To Medium Term: An Application To A Panel Of Polish Companies," Yearbook of the Faculty of Economics and Business Administration, Sofia University, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria, vol. 22(1), pages 5-15, October.
    8. Caro, Norma Patricia & Arias, Ver—nica & Ortiz, Pablo, 2017. "Predicci—n de fracaso en empresas latinoamericanas utilizando el mŽtodo del vecino más cercano para predecir efectos aleatorios en modelos mixtos || Prediction of Failure in Latin-American Companies U," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 24(1), pages 5-24, Diciembre.
    9. Haiyan Zhu & Hongzhi Guan & Yan Han & Wanying Li, 2022. "Study on Peak Travel Avoidance Behavior of Car Travelers during Holidays," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    10. Jie Sun, 2012. "Integration Of Random Sample Selection, Support Vector Machines And Ensembles For Financial Risk Forecasting With An Empirical Analysis On The Necessity Of Feature Selection," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(4), pages 229-246, October.
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    12. Salwa Kessioui & Michalis Doumpos & Constantin Zopounidis, 2023. "A Bibliometric Overview of the State-of-the-Art in Bankruptcy Prediction Methods and Applications," World Scientific Book Chapters, in: Emilios Galariotis & Alexandros Garefalakis & Christos Lemonakis & Marios Menexiadis & Constantin Zo (ed.), Governance and Financial Performance Current Trends and Perspectives, chapter 6, pages 123-153, World Scientific Publishing Co. Pte. Ltd..
    13. Caro, Norma Patricia, 2015. "Descripción de empresas en crisis financiera: el caso de Argentina en las décadas del 1990 y 2000," Revista de Dirección y Administración de Empresas, Universidad del País Vasco - Escuela Universitaria de Estudios Empresariales de San Sebastián.
    14. Fayçal Mraihi, 2016. "Distressed Company Prediction Using Logistic Regression: Tunisian’s Case," Quarterly Journal of Business Studies, Research Academy of Social Sciences, vol. 2(1), pages 34-54.
    15. Jiang, Xiaodan & Fan, Houming & Luo, Meifeng & Xu, Zhenlin, 2020. "Strategic port competition in multimodal network development considering shippers’ choice," Transport Policy, Elsevier, vol. 90(C), pages 68-89.
    16. Maurice Peat & Stewart Jones, 2012. "Using Neural Nets To Combine Information Sets In Corporate Bankruptcy Prediction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(2), pages 90-101, April.
    17. Alessandra Amendola & Marialuisa Restaino & Luca Sensini, 2013. "Corporate Financial Distress And Bankruptcy: A Comparative Analysis In France, Italy And Spain," Global Economic Observer, "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences;Institute for World Economy of the Romanian Academy, vol. 1(2), pages 131-142, November.
    18. Han, Yan & Zhang, Tiantian & Wang, Meng, 2020. "Holiday travel behavior analysis and empirical study with Integrated Travel Reservation Information usage," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 130-151.
    19. Peng XU, 2019. "Exit of Small Businesses: Differentiating between Insolvency, Voluntary Closures and M&A," Discussion papers 19051, Research Institute of Economy, Trade and Industry (RIETI).
    20. 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.
    21. Erdely, Arturo, 2017. "Value at Risk and the Diversification Dogma || Valor en riesgo y el dogma de la diversificación," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 24(1), pages 209-219, Diciembre.
    22. Fayçal Mraihi & Inane Kanzari & Mohamed Tahar Rajhi, 2015. "Development of a Prediction Model of Failure in Tunisian Companies: Comparison between Logistic Regression and Support Vector Machines," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 4(3), pages 184-205.

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