Credit Risk Prediction: A comparative study between logistic regression and logistic regression with random effects (original) (raw)

The aim of this paper is to compare the model of logistic regression versus logistic regression with random effects in order to predict the credit risk of Tunisian banks. To do this, a battery of 26 ratios was calculated from balance sheets and income statements of 528 Tunisian firms from different sectors of activities for the fiscal years 1999-2006. By using information about the activity sector of each firms, we applied the logistic regression model with random effects to take into account the presence of unobserved heterogeneity. The obtained results show that the integration of sectoral effect improves the quality of model predictions in terms of good classification as well as by the ROC curve results.