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Financial predictors for different phases of the failure process

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  • Laitinen, Ek

Abstract

The purpose of the study is to find financial predictors for alternative phases of failure process. For this purpose the typical process is divided into starting, intervening and final phases. The hypotheses presuppose that the differences, trends and levels are significant predictors in these phases, respectively. The aim is to use a separate model to identify the beginning of each phase. This kind of warning system makes it possible to identify the phase in which the firm possibly lives and to assess its risk to fail already years before failure. The main statistical method is regression analysis since both survival status and survival time are used as the dependent variable. The hypotheses were supported by empirical evidence.

Suggested Citation

  • Laitinen, Ek, 1993. "Financial predictors for different phases of the failure process," Omega, Elsevier, vol. 21(2), pages 215-228, March.
    • Handle: RePEc:eee:jomega:v:21:y:1993:i:2:p:215-228
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    Citations

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    Cited by:

    1. Tamás Kristóf & Miklós Virág, 2020. "A Comprehensive Review of Corporate Bankruptcy Prediction in Hungary," JRFM, MDPI, vol. 13(2), pages 1-20, February.
    2. Mosqueda, Rubén, 2010. "Fallibility Of The Rough Set Method In The Formulation Of The Failure Prediction Index Model Of Dynamic Risk," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 15(28), pages 65-88.
    3. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    4. 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.
    5. 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.
    6. Mashhour Hathloul Maharmah & Esraa Ali Khalil, 2015. "Models Ability to Predict Bankruptcy Before it Happens," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 4(7), pages 479-491.
    7. H. Ooghe & S. De Prijcker, 2006. "Failure process and causes of company bankruptcy: a typology," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/388, Ghent University, Faculty of Economics and Business Administration.
    8. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    9. T H Moon & Y Kim & S Y Sohn, 2011. "Technology credit rating system for funding SMEs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(4), pages 608-615, April.
    10. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    11. Erkki K. Laitinen & Oliver Lukason, 2014. "Do firm failure processes differ across countries: evidence from Finland and Estonia," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 15(5), pages 810-832, November.
    12. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    13. Barniv, Ran & Mehrez, Abraham & Kline, Douglas M., 2000. "Confidence intervals for controlling the probability of bankruptcy," Omega, Elsevier, vol. 28(5), pages 555-565, October.
    14. Mário Santiago Céu & Raquel Medeiros Gaspar, 2022. "Vegetative cycle and bankruptcy predictors of agricultural firms," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(12), pages 445-454.
    15. Onofrei, Mihaela & Lupu, Dan, 2014. "The modelling of forecasting the bankruptcy in Romania," MPRA Paper 95511, University Library of Munich, Germany.
    16. Moon, Tae Hee & Sohn, So Young, 2008. "Technology scoring model for reflecting evaluator's perception within confidence limits," European Journal of Operational Research, Elsevier, vol. 184(3), pages 981-989, February.

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