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The Impact of Business Groups on Bankruptcy Prediction Modeling

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  • N. Dewaelheyns
  • C. Van Hulle

Abstract

The bankruptcy prediction literature generally ignores corporate ownership and assumes companies are independent economic entities. In Continental Europe this latter assumption does not hold, due to the importance of business groups. Using a sample of mostly non-quoted Belgian medium and large sized companies, we show that the predictive power of several accounting ratios that are commonly used in bankruptcy prediction models (e.g. performance, leverage, liquidity and efficiency) is different for group member companies as compared to stand-alone companies. By exploiting these differences in relative importance, model fit can be improved without adding any new information. Performance can be increased further by directly adjusting for group related factors, e.g. by including a measure of financial health of the group as a whole. Finally, it is shown that group adjustments can also improve the fit of some well-known existing prediction models.

Suggested Citation

  • N. Dewaelheyns & C. Van Hulle, 2004. "The Impact of Business Groups on Bankruptcy Prediction Modeling," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(4), pages 623-645.
  • Handle: RePEc:ete:revbec:20040404
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    References listed on IDEAS

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    Cited by:

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    2. Steven W. Pottier & David W. Sommer, 2011. "Empirical Evidence on the Value of Group‐Level Financial Information in Insurer Solvency Surveillance," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 14(1), pages 73-88, March.
    3. Nico Dewaelheyns & Cynthia Van Hulle, 2006. "Corporate Failure Prediction Modeling: Distorted by Business Groups' Internal Capital Markets?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(5‐6), pages 909-931, June.
    4. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    5. Pasaribu, Rowland Bismark Fernando, 2008. "Penggunaan Binary Logit untuk Prediksi Financial Distress Perusahaan Yang Tercatat Di Bursa Efek Jakarta [Financial Distress Prediction In Indonesian Stock Exchange]," MPRA Paper 36980, University Library of Munich, Germany.

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