Science Journal of Business and Management

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Comparison Between Discriminant Analysis Model and Logistic Regression Model to Predict the Distress of the Algerian Economic Companies

Received: 06 February 2017    Accepted: 22 February 2017    Published: 27 March 2017
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Abstract

This study aims to select the appropriate method the most able to distinguish between distressed and non-distressed economic companies, which will lead us to know the most important variables that can detect the pre-distress for Algerian economic companies, specifically in the Algerian environment, through the comparison between the findings of the application of two of the most important statistical methods, i.e, discriminant and logistic analysis, on a sample of 60 companies; half of them is distressed and the other half is non-distressed according to four financial ratios selected among the financial ratios the most used by researchers, namely: sales to total assets, working capital to total assets, profit before interest and tax and the ratio of equity to total assets. We concluded, by comparing the findings of the discriminant model and logistic model classification, that the latter is more able to distinguish between distressed and non-distressed Algerian economic companies by 96.7%, compared to the findings of the Fischer discriminant model classification by 91.7%.

DOI 10.11648/j.sjbm.20170502.15
Published in Science Journal of Business and Management (Volume 5, Issue 2, April 2017)
Page(s) 70-77
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Discriminant Analysis, Logistics Analysis, Financial Distress, Algerian Economic Companies

References
[1] CRL: Coefficient of racial likness.
[2] Carl J. Huberty and Stephen Olejnik, Applied MANOVA and Discriminant Analysis, (Canada: John Wiley and Sons, 2006), p.3.
[3] Younes Boujelbene and Sihem Khemakhem, " Credit Risk Prediction: A Comparative Study between Discriminant Analysis and the Neural Approach ", p.3, available at: http://arxiv.org/ftp/arxiv/papers/1311/1311.4266.pdf.
[4] Sai Vamshidhar Nudurupati, "Robust Nonparametric Discriminant Analysis Procedures", Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy, Auburn University, 2009, p.1.
[5] Mohamed Dahmani, "Prediction of the Distress of Companies by Scoring Method", End of study dissertation to obtain the higher diploma of Banking studies, 9th class, October 2007, p.40.
[6] Mireille Bardos, " Scoring on Business Data: An individual Diagnostic Instrument and a Portfolio Analysis Tool for a Clientele ", MODULAD Review, No. 38, 2008, p.165.
[7] Joseph M. Hilbe, Logistic regression models, (United state of America: CRC press, 2009), p.3.
[8] Hamadi Matoussi, Rim Mouelhi and Salah Sayah, "The Prediction of bankruptcy of Tunisian Companies by the logistic regression", 20th congress of "AFC", France, 1999, p.07.
[9] Scott A. Czepiel, "Maximum Likelihood Estimation of Logistic Regression Models: Theory and Implementation", p.01. visit http://czep.net/contact.html.
[10] Rajaa Mahmoud Abou Alam, “Statistical Analysis of data using SPSS”, 1st ed., (Egypt: Publishing House for Universities, 2002), p. 224.
Author Information
  • Faculty of Economic, Commercial and Management Sciences, Batna University, Batna, Algeria

  • Faculty of Economic, Commercial and Management Sciences, Batna University, Batna, Algeria

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  • APA Style

    Nedjema Abbas, Intissar Slimani. (2017). Comparison Between Discriminant Analysis Model and Logistic Regression Model to Predict the Distress of the Algerian Economic Companies. Science Journal of Business and Management, 5(2), 70-77. https://doi.org/10.11648/j.sjbm.20170502.15

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    ACS Style

    Nedjema Abbas; Intissar Slimani. Comparison Between Discriminant Analysis Model and Logistic Regression Model to Predict the Distress of the Algerian Economic Companies. Sci. J. Bus. Manag. 2017, 5(2), 70-77. doi: 10.11648/j.sjbm.20170502.15

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    AMA Style

    Nedjema Abbas, Intissar Slimani. Comparison Between Discriminant Analysis Model and Logistic Regression Model to Predict the Distress of the Algerian Economic Companies. Sci J Bus Manag. 2017;5(2):70-77. doi: 10.11648/j.sjbm.20170502.15

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  • @article{10.11648/j.sjbm.20170502.15,
      author = {Nedjema Abbas and Intissar Slimani},
      title = {Comparison Between Discriminant Analysis Model and Logistic Regression Model to Predict the Distress of the Algerian Economic Companies},
      journal = {Science Journal of Business and Management},
      volume = {5},
      number = {2},
      pages = {70-77},
      doi = {10.11648/j.sjbm.20170502.15},
      url = {https://doi.org/10.11648/j.sjbm.20170502.15},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.sjbm.20170502.15},
      abstract = {This study aims to select the appropriate method the most able to distinguish between distressed and non-distressed economic companies, which will lead us to know the most important variables that can detect the pre-distress for Algerian economic companies, specifically in the Algerian environment, through the comparison between the findings of the application of two of the most important statistical methods, i.e, discriminant and logistic analysis, on a sample of 60 companies; half of them is distressed and the other half is non-distressed according to four financial ratios selected among the financial ratios the most used by researchers, namely: sales to total assets, working capital to total assets, profit before interest and tax and the ratio of equity to total assets. We concluded, by comparing the findings of the discriminant model and logistic model classification, that the latter is more able to distinguish between distressed and non-distressed Algerian economic companies by 96.7%, compared to the findings of the Fischer discriminant model classification by 91.7%.},
     year = {2017}
    }
    

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    AB  - This study aims to select the appropriate method the most able to distinguish between distressed and non-distressed economic companies, which will lead us to know the most important variables that can detect the pre-distress for Algerian economic companies, specifically in the Algerian environment, through the comparison between the findings of the application of two of the most important statistical methods, i.e, discriminant and logistic analysis, on a sample of 60 companies; half of them is distressed and the other half is non-distressed according to four financial ratios selected among the financial ratios the most used by researchers, namely: sales to total assets, working capital to total assets, profit before interest and tax and the ratio of equity to total assets. We concluded, by comparing the findings of the discriminant model and logistic model classification, that the latter is more able to distinguish between distressed and non-distressed Algerian economic companies by 96.7%, compared to the findings of the Fischer discriminant model classification by 91.7%.
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