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Small, alone and poor: a merciless portrait of insolvent French firms, 2007-2010

Author

Listed:
  • Nadine Levratto

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Luc Tessier
  • Messaoud Zouikri

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

Abstract

This empirical paper investigates the path to bankruptcy for a sample of French firms in default, in particular the decision to file a petition for bankruptcy, the arbitrage between rescuing and liquidation and the effective survival. The procedure is depicted as a sequence of three steps in which judges play a crucial role as they decide whether a company is insolvent or not and determine whether an insolvent company deserves to be rescued or, on the contrary, should be liquidated, the market having the last word since the effective success depends on the capability of the firm to recover from the judicial proceedings. We test different hypotheses about the variables influencing each possibility which include i) the role of the market in the firm's health, ii) the influence of financial structures, iii) the importance of corporate governance and iv) the inherent corporate factors of probable survival. Using three linked LOGIT models, our first finding is that the probability to default depends mainly on the market. Secondly the probability to be rescued depends essentially on the financial structure. Finally, the probability for the firm to remain in business in the long term is largely influenced by the market and profitability. Our results also support the idea that governance, size and resources are the main determinants of exit from the market or success of any company.

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  • Nadine Levratto & Luc Tessier & Messaoud Zouikri, 2011. "Small, alone and poor: a merciless portrait of insolvent French firms, 2007-2010," Working Papers hal-04140945, HAL.
    • Handle: RePEc:hal:wpaper:hal-04140945
    Note: View the original document on HAL open archive server: https://hal.science/hal-04140945
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    References listed on IDEAS

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    1. Stewart C. Myers & Nicholas S. Majluf, 1984. "Corporate Financing and Investment Decisions When Firms Have InformationThat Investors Do Not Have," NBER Working Papers 1396, National Bureau of Economic Research, Inc.
    2. Myers, Stewart C. & Majluf, Nicholas S., 1984. "Corporate financing and investment decisions when firms have information that investors do not have," Journal of Financial Economics, Elsevier, vol. 13(2), pages 187-221, June.
    3. Casey, C & Bartczak, N, 1985. "Using Operating Cash Flow Data To Predict Financial Distress - Some Extensions," Journal of Accounting Research, Wiley Blackwell, vol. 23(1), pages 384-401.
    4. Stijn Claessens & Leora F. Klapper, 2005. "Bankruptcy around the World: Explanations of Its Relative Use," American Law and Economics Review, American Law and Economics Association, vol. 7(1), pages 253-283.
    5. Bose, Indranil & Pal, Raktim, 2006. "Predicting the survival or failure of click-and-mortar corporations: A knowledge discovery approach," European Journal of Operational Research, Elsevier, vol. 174(2), pages 959-982, October.
    6. 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.
    7. Terry J. Ward & Benjamin P. Foster, 1997. "A Note on Selecting a Response Measure for Financial Distress," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 24(6), pages 869-879, July.
    8. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    9. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    10. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
    11. Harlan Platt & Marjorie Platt, 2002. "Predicting corporate financial distress: Reflections on choice-based sample bias," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 184-199, June.
    12. Gentry, Ja & Newbold, P & Whitford, Dt, 1985. "Classifying Bankrupt Firms With Funds Flow Components," Journal of Accounting Research, Wiley Blackwell, vol. 23(1), pages 146-160.
    13. Peel, M. J. & Peel, D. A., 1988. "A multilogit approach to predicting corporate failure--Some evidence for the UK corporate sector," Omega, Elsevier, vol. 16(4), pages 309-318.
    14. Murugan Anandarajan & Picheng Lee & Asokan Anandarajan, 2001. "Bankruptcy prediction of financially stressed firms: an examination of the predictive accuracy of artificial neural networks," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 10(2), pages 69-81, June.
    15. Terry J. Ward & Benjamin P. Foster, 1997. "A Note on Selecting a Response Measure for Financial Distress," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 24(6), pages 869-879.
    16. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
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