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

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.

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Publication Details

Journal
Asian Economic and Financial Review
Published
2024-08-15
DOI
https://doi.org/10.55493/5002.v14i9.5157
Primary Topic
Financial Distress and Bankruptcy Prediction
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Lobna Abid, Afif Masmoudi, Saida Chibani
Asian Economic and Financial Review
Financial Distress and Bankruptcy Prediction
article

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

Lobna Abid, Afif Masmoudi, Saida Chibani
article en

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.

Asian Economic and Financial ReviewVol. 14(9)
University of Sfax (TN)
Decent work and economic growth
Openalex Percentile: Top 76%
Financial Distress and Bankruptcy Prediction
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Predicting determinants of industrial firms’ loan payment default: Logit model versus probit model — Lobna Abid, Afif Masmoudi, et al. · Asian Economic and Financial Review (2024) | TGRS Research Map | TGRS