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Bankruptcy Prediction: Application of Logit Analysis in Export Credit Risks

Author

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  • Li-Chiu Chi

    (Department of Finance, National Formosa University, 4 Wenhwa Road, Huwei, Yunlin County 632, Taiwan, ROC.)

  • Tseng-Chung Tang

    (Department of Finance, National Formosa University, 4 Wenhwa Road, Huwei, Yunlin County 632, Taiwan, ROC.)

Abstract

To date, relatively little empirical research has been conducted on the efficacy of the trade credit risk prediction model in the context of international trade applications. Using a sample of listed firms in seven Asia-Pacific capital markets (Hong Kong Japan, Korea, Malaysia Singapore, Thailand, and the Philippines) from 2001 to 2003 with available data, we have made a preliminary attempt at empirically studying a predictive export credit risk model based on financial ratios, firm-specific characteristics (size, maturity, R&D expenses, and depreciation expenses), and country risk measures. The results show that our Logit models demonstrate decent classification accuracy and robustness. Specifically, the prediction ability is approximately equal to classification ability when the model is applied to a testing sample. Furthermore, the results indicate that the closer the analysis is to the credit crisis occurrence, the more improved the classification accuracy and prediction accuracy are.

Suggested Citation

  • Li-Chiu Chi & Tseng-Chung Tang, 2006. "Bankruptcy Prediction: Application of Logit Analysis in Export Credit Risks," Australian Journal of Management, Australian School of Business, vol. 31(1), pages 17-27, June.
    • Handle: RePEc:sae:ausman:v:31:y:2006:i:1:p:17-27
    DOI: 10.1177/031289620603100102
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    References listed on IDEAS

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    Cited by:

    1. Situm Mario, 2014. "Inability of Gearing-Ratio as Predictor for Early Warning Systems," Business Systems Research, Sciendo, vol. 5(2), pages 23-45, September.
    2. Wikil Kwak & Yong Shi & Gang Kou, 2012. "Bankruptcy prediction for Korean firms after the 1997 financial crisis: using a multiple criteria linear programming data mining approach," Review of Quantitative Finance and Accounting, Springer, vol. 38(4), pages 441-453, May.
    3. Shih, Kuang Hsun & Cheng, Ching Chan & Wang, Yi Hsien, 2011. "Financial Information Fraud Risk Warning for Manufacturing Industry - Using Logistic Regression and Neural Network," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 54-71, March.
    4. Karen Benson & Peter M Clarkson & Tom Smith & Irene Tutticci, 2015. "A review of accounting research in the Asia Pacific region," Australian Journal of Management, Australian School of Business, vol. 40(1), pages 36-88, February.

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