Corporate Bankruptcy Measurement and Prediction: Evidence from Publicly Traded US Firms

Abstract

We develop a bankruptcy classification model combining financial ratio analysis, measurement theory, and logistic analysis from a sample of 258 bankrupt and non-bankrupt public companies in the United States. Transformed financial variables are developed to a bankruptcy classification measurement model using the confirmatory factor analysis, which is then refined to a four variable, logit bankruptcy model. The result shows that the model possesses high classification accuracy and relatively small differences in classification rates between in-sample and out-of-sample as compared to industry-relative analysis. As such, our findings help managers more accurately estimate bankruptcy risk and thus, have a better opportunity to take corrective actions early, enhancing corporate financial sustainability.