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Estimating financial distress likelihood

Author

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  • Pindado, Julio
  • Rodrigues, Luis
  • de la Torre, Chabela

Abstract

This study develops an ex-ante model for estimating financial distress likelihood (FDL), and contributes to the literature by presenting a financially-based definition of distress that is independent of its legal consequences, a theoretically supported model for the FDL, and an appropriate methodology that uses panel data to eliminate the unobservable heterogeneity. The model is then estimated cross-sectionally to obtain an indicator of the likelihood of financial distress that incorporates the specificity of each company. In doing so, this study provides a well-specified model that is stable in terms of magnitude, sign and significance of the coefficients and, more importantly, that yields a measure of the FDL that is more robust to time and the international context than the estimates of FDL that are based on seminal models. This measure could be appropriate for use in future research that deals with FDL, such as capital structure and the prevention of financial distress.

Suggested Citation

  • Pindado, Julio & Rodrigues, Luis & de la Torre, Chabela, 2008. "Estimating financial distress likelihood," Journal of Business Research, Elsevier, vol. 61(9), pages 995-1003, September.
  • Handle: RePEc:eee:jbrese:v:61:y:2008:i:9:p:995-1003
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    References listed on IDEAS

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    Cited by:

    1. Pindado, Julio & Rodrigues, Luis & de la Torre, Chabela, 2008. "How do insolvency codes affect a firm's investment?," International Review of Law and Economics, Elsevier, vol. 28(4), pages 227-238, December.
    2. Sami Ben Jabeur & Youssef Fahmi, 2014. "Les modèles de prévision de la défaillance des entreprises françaises : une approche comparative," Working Papers 2014-317, Department of Research, Ipag Business School.
    3. John Nkwoma Inekwe, 2016. "Financial Distress, Employees’ Welfare and Entrepreneurship Among SMEs," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 129(3), pages 1135-1153, December.
    4. repec:eee:ecmode:v:72:y:2018:i:c:p:8-21 is not listed on IDEAS
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    6. Pablo de Llano Monelos & Manuel Rodríguez López & Carlos Piñeiro Sánchez, 2013. "Bankruptcy Prediction Models in Galician companies. Application of Parametric Methodologies and Artificial Intelligence," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 117-136.
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    8. Sami BEN JABEUR & Youssef FAHMI, 2014. "Predicting Business Failure Using Data-Mining Methods," Working Papers 2014-308, Department of Research, Ipag Business School.
    9. repec:eee:ememar:v:37:y:2018:i:c:p:47-65 is not listed on IDEAS
    10. Pindado, Julio & Requejo, Ignacio & de la Torre, Chabela, 2011. "Family control and investment–cash flow sensitivity: Empirical evidence from the Euro zone," Journal of Corporate Finance, Elsevier, vol. 17(5), pages 1389-1409.
    11. Llano Monelos Pablo De & Piñeiro Sánchez Carlos & Rodríguez López Manuel, 2014. "DEA as a business failure prediction tool. Application to the case of galician SMEs," Contaduría y Administración, Accounting and Management, vol. 59(2), pages 65-96, abril-jun.
    12. repec:eee:finana:v:59:y:2018:i:c:p:276-289 is not listed on IDEAS
    13. Konstantaras, Konstantinos & Siriopoulos, Costas, 2011. "Estimating financial distress with a dynamic model: Evidence from family owned enterprises in a small open economy," Journal of Multinational Financial Management, Elsevier, vol. 21(4), pages 239-255, October.
    14. Hernandez Tinoco, Mario & Wilson, Nick, 2013. "Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 394-419.
    15. Bastos, Rafael & Pindado, Julio, 2013. "Trade credit during a financial crisis: A panel data analysis," Journal of Business Research, Elsevier, vol. 66(5), pages 614-620.
    16. repec:spr:annopr:v:271:y:2018:i:2:d:10.1007_s10479-018-2814-2 is not listed on IDEAS
    17. Sami BEN JABEUR & Youssef FAHMI, 2014. "Default Prediction for Small-Medium Enterprises in France: A comparative approach," Working Papers 2014-319, Department of Research, Ipag Business School.
    18. Ciampi, Francesco, 2015. "Corporate governance characteristics and default prediction modeling for small enterprises. An empirical analysis of Italian firms," Journal of Business Research, Elsevier, vol. 68(5), pages 1012-1025.
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    21. Keasey, Kevin & Martinez, Beatriz & Pindado, Julio, 2015. "Young family firms: Financing decisions and the willingness to dilute control," Journal of Corporate Finance, Elsevier, vol. 34(C), pages 47-63.
    22. repec:kap:sbusec:v:50:y:2018:i:2:d:10.1007_s11187-016-9833-7 is not listed on IDEAS
    23. repec:eee:ecosys:v:42:y:2018:i:4:p:616-624 is not listed on IDEAS

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