Predicting contractor failure using stochastic dynamics of economic and financial variables

This paper examines the pattern of stochastic dynamics, which includes percentage changes, trends, and volatility for economic and financial variables of failed and nonfailed contractors and uses them to predict contractor failure. Contractor failure is defined as the termination of a contractor's operation. Monthly economic data were collected from publicly available economic reports such as the Federal Reserve Bulletin. Contractor financial data were obtained from five insurance companies. The total sample consisted of 430 financial statements representing 120 contractors (49 failed and 71 nonfailed). Statistic analysis reveals that failed contractors have a negative trend and larger volatility in the percentage changes of net worth, gross profit, and net working capital. A random coefficient method is proposed to describe the stochastic dynamics, i.e., the future position, the trend, and the volatility. A discriminant function for detecting failed contractors has been developed using step wise regression. The discrimination function includes the following variables: (1) trend-prime interest rate; (2) future position-new construction value in-place; (3) trend-new construction value in place; (4) future position-net worth/total asset; (5) trend-gross profit/total asset; and (6) volatility-net working capital/total asset. An additional 23 contractors (10 failed, 13 nonfailed) were used to validate the developed model. The model misclassified five contractors. Example applications of the model are also provided.