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

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  • Premachandra, I.M.
  • Chen, Yao
  • Watson, John

Abstract

Using an additive super-efficiency data envelopment analysis (DEA) model, this paper develops a new assessment index based on two frontiers for predicting corporate failure and success. The proposed approach is applied to a random sample of 1001 firms, which is composed of 50 large US bankrupt firms randomly selected from Altman's bankruptcy database and 901 healthy matching firms. This sample represents the largest firms that went bankrupt over the period 1991-2004 and represents a full spectrum of industries. Our findings demonstrate that the DEA model is relatively weak in predicting corporate failures compared to healthy firm predictions, and the assessment index improves this weakness by giving the decision maker various options to achieve different precision levels of bankrupt, non-bankrupt, and total predictions.

Suggested Citation

  • Premachandra, I.M. & Chen, Yao & Watson, John, 2011. "DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment," Omega, Elsevier, vol. 39(6), pages 620-626, December.
  • Handle: RePEc:eee:jomega:v:39:y:2011:i:6:p:620-626
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    References listed on IDEAS

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    2. Premachandra, I.M. & Bhabra, Gurmeet Singh & Sueyoshi, Toshiyuki, 2009. "DEA as a tool for bankruptcy assessment: A comparative study with logistic regression technique," European Journal of Operational Research, Elsevier, vol. 193(2), pages 412-424, March.
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    Citations

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    Cited by:

    1. You, Yan Q. & Jie, Tao, 2016. "A study of the operation efficiency and cost performance indices of power-supply companies in China based on a dynamic network slacks-based measure model," Omega, Elsevier, vol. 60(C), pages 85-97.
    2. Liu, Wenbin & Zhou, Zhongbao & Liu, Debin & Xiao, Helu, 2015. "Estimation of portfolio efficiency via DEA," Omega, Elsevier, vol. 52(C), pages 107-118.
    3. Carlos Serrano-Cinca & Yolanda Fuertes-Callén & Begoña Gutiérrez-Nieto & Beatriz Cuellar-Fernández, 2014. "Path modelling to bankruptcy: causes and symptoms of the banking crisis," Applied Economics, Taylor & Francis Journals, vol. 46(31), pages 3798-3811, November.
    4. Du, Juan & Chen, Yao & Huo, Jiazhen, 2015. "DEA for non-homogenous parallel networks," Omega, Elsevier, vol. 56(C), pages 122-132.
    5. Chen, Yao & Du, Juan & Huo, Jiazhen, 2013. "Super-efficiency based on a modified directional distance function," Omega, Elsevier, vol. 41(3), pages 621-625.
    6. repec:spr:annopr:v:254:y:2017:i:1:d:10.1007_s10479-017-2431-5 is not listed on IDEAS
    7. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    8. Yang, Xiaopeng & Morita, Hiroshi, 2013. "Efficiency improvement from multiple perspectives: An application to Japanese banking industry," Omega, Elsevier, vol. 41(3), pages 501-509.
    9. Peng, Yi & Kou, Gang & Wang, Guoxun & Shi, Yong, 2011. "FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms," Omega, Elsevier, vol. 39(6), pages 677-689, December.
    10. Mousavi, Mohammad M. & Ouenniche, Jamal & Xu, Bing, 2015. "Performance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 64-75.
    11. Sahoo, Biresh K. & Tone, Kaoru, 2013. "Non-parametric measurement of economies of scale and scope in non-competitive environment with price uncertainty," Omega, Elsevier, vol. 41(1), pages 97-111.
    12. Li, Yongjun & Chen, Yao & Liang, Liang & Xie, Jianhui, 2012. "DEA models for extended two-stage network structures," Omega, Elsevier, vol. 40(5), pages 611-618.
    13. Zhang, Faming & Tadikamalla, Pandu R. & Shang, Jennifer, 2016. "Corporate credit-risk evaluation system: Integrating explicit and implicit financial performances," International Journal of Production Economics, Elsevier, vol. 177(C), pages 77-100.
    14. Edelstein, Barak & Paradi, Joseph C., 2013. "Ensuring units invariant slack selection in radial data envelopment analysis models, and incorporating slacks into an overall efficiency score," Omega, Elsevier, vol. 41(1), pages 31-40.

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