A Logistic Regression Model for Credit Risk of Companies in the Service Sector

Abstract

Credit risk prediction is a vital issue in empirical studies as it has attracted the interests of many researchers. In the current study, a logistic regression model is used to evaluate determinants of payment default risks of companies in the service sector. Data, which consist of six financial variables and two macro-economic variables, have been collected from the Tunisian Central Bank and World Development Indicators. The obtained results show that debt, solvency and profitability ratios and a loan amount are the key firm-specific factor determining credit risk. Moreover, we further find that high level of inflation and the decrease of GDP growth rate are able to increase corporate credit risk.