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Predicting determinants of industrial firms’ loan payment default: Logit model versus probit model

Author

Listed:
  • Lobna Abid
  • Saida Chibani
  • Afif Masmoudi

Abstract

Appropriate control and management of credit risk has become the main concern of financial institutions, which are constantly developing models for analyzing, assessing and predicting this risk, particularly in view of the prudential standards required by central banks. The current research paper aims to specify the determinants of payment defaults in Tunisian companies in the industrial sector so as to develop a model with the optimal predictive precision of forecasting payment default when it relates to industrial firms functioning in the Tunisian environment. Within this framework, we compared two generalized linear models which correspond to the logit and probit models based on a sample of Tunisian industrial companies. The results revealed that debt ratio is the most important variable that increases the probability of default payment, while the solvency ratio reduces the probability of default payment. This study highlights the vital contribution of macroeconomic agents, such as GDP growth rate and inflation rate, in terms of the prediction of default payment.

Suggested Citation

  • Lobna Abid & Saida Chibani & Afif Masmoudi, 2024. "Predicting determinants of industrial firms’ loan payment default: Logit model versus probit model," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 14(9), pages 683-694.
  • Handle: RePEc:asi:aeafrj:v:14:y:2024:i:9:p:683-694:id:5157
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