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Bankruptcy Discrimination With Real Variables

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  • Harlan D. Platt
  • Marjorie B. Platt
  • Jon Gunnar Pedersen

Abstract

This paper reconsiders the accepted usage of nondeflated financial ratios in statistical models to differentiate between failed and nonfailed firms. Non‐deflated ratios are hypothesized to inadequately reflect inter‐temporal macroeconomic fluctuations that affect the ability of firm's to survive. Using a sample of 124 oil and gas companies between the period 1982–1988, the going concern assumption is evaluated with statistical logit models using either nondeflated or deflated financial ratios. Deflated company ratios are created by transforming data with price indices or by creating market value ratios. Empirical results suggest that a superior bankruptcy early warning model is developed for the oil and gas industry by creating real financial and reserve ratios and by introducing external factors, such as oil prices, interest rates and accounting method, as independent predictors. Overall classification accuracy is approximately 95 percent.

Suggested Citation

  • Harlan D. Platt & Marjorie B. Platt & Jon Gunnar Pedersen, 1994. "Bankruptcy Discrimination With Real Variables," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 21(4), pages 491-510, June.
    • Handle: RePEc:bla:jbfnac:v:21:y:1994:i:4:p:491-510
    DOI: 10.1111/j.1468-5957.1994.tb00332.x
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    References listed on IDEAS

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    Cited by:

    1. McGurr, Paul T. & DeVaney, Sharon A., 1998. "Predicting Business Failure of Retail Firms: An Analysis Using Mixed Industry Models," Journal of Business Research, Elsevier, vol. 43(3), pages 169-176, November.
    2. Yang, Z. R. & Platt, Marjorie B. & Platt, Harlan D., 1999. "Probabilistic Neural Networks in Bankruptcy Prediction," Journal of Business Research, Elsevier, vol. 44(2), pages 67-74, February.

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