DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment

Omega

Volumn 39, Issue 6, 2011, Pages 620-626

  Premachandra, I M ^a   Chen, Yao ^b   Watson, John ^c  

^a UNIVERSITY OF OTAGO   (New Zealand)

^b UNIVERSITY OF MASSACHUSETTS LOWELL   (United States)

^c MONASH UNIVERSITY   (Australia)

Author keywords

Bankruptcy; Corporate failure; Corporate success; Data envelopment analysis (DEA)

Indexed keywords

EID: 79953161433     PISSN: 03050483     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.omega.2011.01.002     Document Type: Article

References (29)

1. Warner J. Bankruptcy costs: some evidence. Journal of Finance 1977, 32:337-347.
2. Altman E.I. A further empirical investigation of the bankruptcy cost question. Journal of Finance 1984, 34:1067-1089.
3. Aziz M.A., Dar H.A. Predicting corporate bankruptcy: where we stand. Corporate Governance 2006, 6:18-33.
4. Collins R.A., Green R.D. Statistical methods of bankruptcy forecasting. Journal of Economics and Business 1982, 32:349-352.
5. Premachandra I.M., Bhabra G.S., Sueyoshi T. DEA as a tool for bankruptcy assessment: a comparative study with logistic regression technique. European Journal of Operational Research 2009, 193:412-424.
6. Altman E.I. Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance 1968, 23:589-609.
7. Eisenbeis R. Pitfalls in the application of discriminant analysis in business, finance and economics. Journal of Finance 1977, 32:875-900.
8. Grice S., Ingram R. Tests of the generalizability of Altman's bankruptcy prediction model. Journal of Business Research 2001, 54:53-61.
9. Keasey K., Watson R. Non-financial symptoms and the prediction of small company failure: a test of Argenti's hypothesis. Journal of Business Finance and Accounting 1987, 14:335-353.
10. Mensah Y. The differential bankruptcy predictive ability of specific price level adjustments: some empirical evidence. The Accounting Review 1983, 58:228-245.
11. Ohlson J. Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research 1980, 18:109-131.
12. Zavgren C.V. Assessing the vulnerability of failure of American industrial firms: a logistic analysis. Journal of Business Finance and Accounting 1985, 12:19-45.
13. Platt D., Platt B. Development of a class of stable predictive variables: the case of bankruptcy prediction. Journal of Business Finance and Accounting 1990, 17:31-51.
14. Press S.J., Wilson S. Choosing between logistic regression and discriminant analysis. Journal of American Statistical Association 1978, 73:699-705.
15. Demyanyk Y., Hasan I. Financial crises and bank failures: a review of prediction methods. Omega 2010, 38(5):315-324.
16. Tam K.Y. Neural network models and the prediction of bank bankruptcy. Omega 1991, 19(5):429-445.
17. Kahya E., Theodossiou P. Predicting corporate financial distress: a time-series CUSUM methodology. Review of Quantitative Finance and Accounting 1999, 13:323-345.
18. Molinero C.M., Ezzamel M. Multidimensional scaling applied to corporate failure. Omega 1991, 19(4):259-274.
19. Lindsay D., Campbell A. A chaos approach to bankruptcy prediction. Journal of Applied Business Research 1996, 12:1-9.
20. Cielen A., Peeters L., Vanhoof K. Bankruptcy prediction using a data envelopment analysis. European Journal of Operational Research 2004, 154:526-532.
21. Kao C., Liu S.-T. Prediction bank performance with financial forecasts: a case of Taiwan commercial banks. Journal of Banking and Finance 2004, 28:2353-2368.
22. Shanmugam R., Johnson C. At a crossroad of data envelopment and principal component analyses. Omega 2007, 35(3):351-364.
23. Charnes A., Cooper W.W., Seiford L.M., Stutz J. A multiplicative model for efficiency analysis. Socio-Economic Planning Sciences 1982, 16(5):223-224.
24. Avkiran N.K. Association of DEA super-efficiency estimates with financial ratios: investigating the case for Chinese banks. Omega 2011, 39(3):323-334.
25. Du J., Liang L., Zhu Joe A slacks-based measure of super-efficiency in data envelopment analysis: a comment. European Journal of Operational Research 2010, 204:694-697.
26. Charnes A., Cooper W.W., Rhodes E. Measuring the efficiency of decision making units. European Journal of Operation Research 1978, 2:429-444.
27. Zhu J. Quantitative models for performance evaluation and benchmarking: data envelopment analysis with spreadsheets 2009, Springer Science, Boston. 2nd edition.
28. Cooper W.W., Seiford L.M., Zhu J. Handbook on data envelopment analysis 2004, Springer, Boston.
29. Färe R., Grosskopf S., Roos P. Malmquist productivity indexes: a survey of theory and practice. Index numbers: essays in honour of Sten Malmquist 1998, Kluwer Academic Publishers, Boston. R. Färe, S. Grosskopf, R.R. Russell (Eds.).