Predicting Construction Contractor Default with Market-based Credit Models - in Cases of North American Construction Contractors and Taiwan Construction Industry
Date Issued
2011
Date
2011
Author(s)
Tsai, Lung-Ken
Abstract
The prediction of construction contractor default has always been an important issue for construction owners and other stakeholders. Previous construction contractor default prediction models incorporated managerial or economic variables into traditional accounting-based models to enhance predicting power. However managerial variables are qualitative and depend on human judgment, while accounting numbers are subject to manipulation by management. Furthermore, both economic variables and accounting ratios are only available periodically and may not provide necessary information in time. Using these variables as model inputs has caused doubt among scholars.
The market-based default prediction models which use stock market information in predicting company default risk have appealed to scholars in recent years. Perhaps due to the unique industrial characteristics and accounting rules in the construction industry, the construction industry is usually excluded in their empirical validation. This is the first study applying market-based models to predict the default of American construction contractors and assert that the option-pricing framework is very suitable to describe the behavior of contractor default. Different from existing literature of contractor default prediction models, this research builds and validates models using a large cross-section of contractors, and uses all available firm-years data during sample selection period in empirical analyses to alleviate sample selection biases. The Receiver Operating Characteristics (ROC) curve is employed to assess the model performance in ranking contractors from riskiest to safest, as to choose the optimal model for construction owners and other stakeholders.
The empirical results of this study exhibit that the market-based models have a smaller misclassification rate in classifying defaulted and non-defaulted contractors than the enhanced accounting-based models, which, as proposed by Severson et al. (1994), and Russell and Zhai (1996), additionally incorporate managerial or economic variables into accounting-based models. Besides, the market-based models obviously outperforms traditional accounting-based model in ranking contractors from riskiest to safest. They also have markedly better discriminatory power than that of Reisz and Perlich (2007) based on the data set of all industries except the construction industry. The overall results conclude that the market-based models, which use stock market information in predicting company default risk, has significant advantage for the construction industry, and it provides an alternative to measure construction contractor default. The contribution of current research is that it proposes the possibility to explore the default risk of the construction industry using a more powerful new tool.
Subjects
construction industry
credit risk
default prediction
market-based model
accounting-based model
ROC curve
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