Predicting Restaurant Bankruptcy: A Logit Model in Comparison with a Discriminant Model

Abstract

This article follows up on a previous study that developed a multiple discriminant model for predicting restaurant firm bankruptcy. Using the same data set, this study developed a logit model and compared its prediction accuracy with that of the discriminant model. The two-variable logit model, resulting from a forward stepwise selection procedure, correctly predicted 94% of the in-sample restaurant companies and 93% of the out-of-sample firms 1 year prior to bankruptcy. Although the results show that the two models are equally effective in predicting restaurant bankruptcy, the logit model is preferred for restaurant bankruptcy prediction because of its theoretical soundness. Our estimated logit model suggests that restaurant firms with low earnings before interest and taxes (EBIT) and high total liabilities are more likely to go bankrupt. To reduce bankruptcy risk, restaurant operators should not only adopt a prudent financing policy but also have tight operating cost control to increase EBIT.