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Modelling Corporate Sector Distress in India

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  • Manjusha Senapathi
  • Saptarshi Ghosal

Abstract

The paper attempts to formulate a model to predict corporate financial distress of non-government non-financial public limited companies and estimate distressed bank debt due to the sample companies for the period 2006-07 to 2013-14. The model estimates probability of a company being financially distressed in the following year using the multivariate logistic regression based on three financial ratios viz., long term liabilities to total assets, operating profits to total liabilities, and current assets to current liabilities. The model was tested for some stressed industries/companies and was found to capture the underlying distress. Distressed bank debt for the sample companies was found to be increasing since 2011-12. [RBI WPS (DEPR): 10 / 2016].

Suggested Citation

  • Manjusha Senapathi & Saptarshi Ghosal, 2016. "Modelling Corporate Sector Distress in India," Working Papers id:11540, eSocialSciences.
  • Handle: RePEc:ess:wpaper:id:11540
    Note: Institutional Papers
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    References listed on IDEAS

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    1. Arellano, Manuel & Honore, Bo, 2001. "Panel data models: some recent developments," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 53, pages 3229-3296, Elsevier.
    2. Izan, H. Y., 1984. "Corporate distress in Australia," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 303-320, June.
    3. Andreas Charitou & Evi Neophytou & Chris Charalambous, 2004. "Predicting corporate failure: empirical evidence for the UK," European Accounting Review, Taylor & Francis Journals, vol. 13(3), pages 465-497.
    4. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    5. Laitinen, Erkki K. & Laitinen, Teija, 2000. "Bankruptcy prediction: Application of the Taylor's expansion in logistic regression," International Review of Financial Analysis, Elsevier, vol. 9(4), pages 327-349.
    6. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    7. Eisenbeis, Robert A, 1977. "Pitfalls in the Application of Discriminant Analysis in Business, Finance, and Economics," Journal of Finance, American Finance Association, vol. 32(3), pages 875-900, June.
    8. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    9. Hsin-Hung Chen, 2008. "The Timescale Effects of Corporate Governance Measure on Predicting Financial Distress," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 35-46.
    10. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 225-238.
    11. Zong-Jun Wang & Xiao-Lan Deng, 2006. "Corporate Governance and Financial Distress: Evidence from Chinese Listed Companies," Chinese Economy, Taylor & Francis Journals, vol. 39(5), pages 5-27, October.
    12. Ran Barniv & Anurag Agarwal & Robert Leach, 2002. "Predicting Bankruptcy Resolution," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 29(3&4), pages 497-520.
    13. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    14. Libby, R, 1975. "Accounting Ratios And Prediction Of Failure - Some Behavioral Evidence," Journal of Accounting Research, Wiley Blackwell, vol. 13(1), pages 150-161.
    15. Peter Lindner & Sung Eun Jung, 2014. "Corporate Vulnerabilities in India and Banks' Loan Performance," IMF Working Papers 2014/232, International Monetary Fund.
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    Cited by:

    1. Bose, Udichibarna & Filomeni, Stefano & Mallick, Sushanta, 2021. "Does bankruptcy law improve the fate of distressed firms? The role of credit channels," Journal of Corporate Finance, Elsevier, vol. 68(C).

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