Huang, Y L (2009) Prediction of contractor default probability using structural models of credit risk: An empirical investigation. Construction Management and Economics, 27(6), pp. 581-596. ISSN 1466433X
Abstract
Structural models of credit risk can apply for quantitatively predicting contractor defaults and pricing performance guarantees. However, the application involves crucial empirical issues. Some of the empirical issues are investigated using market and accounting data of public construction firms in Taiwan. Statistical analyses are conducted using the Wilcoxon rank sum test, Shumway's discrete-time hazard model, and the receiver operating characteristic curve. Structural models are viable, and market value tends to dominate other measures of economic or financial distress in terms of prediction accuracy. However, when calibrated to minimize Type I and Type II errors, the default boundary of market value produces substantial residual errors. In addition, the calibrated boundary is at 151% of face debt, much higher than those suggested by previous empirical studies. This seems to reflect the idiosyncratic short-term debt structures of Taiwanese construction firms. Leland and Toft's model is recommended for further investigations, because their theory explains the higher than expected calibrated boundary.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | contractor default; prediction; probability; regression analysis; roc curve; structural model |
| Index terms: | pricing, statistical analysis, investigation, financial distress, public construction, empirical study, regression analysis, guarantee, default, Taiwan, construction firm, accuracy, face, accounting |
| Subjects: | statistical analysis, building construction, professional development, Geography, research methods, contract structure, economic analysis, data science, psychology, dispute resolution, organization, data collection methods |
| Topics: | Organizational Design, Legal Issues, Procurement, Business Strategy, Research Practice, Geographical Context, Engineering Principles, Information Management |
| Descriptive scope: | 3 PCA |
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