Prediction of insolvency using logistic regression: The case of the Republic of Srpska
Prediction of insolvency using logistic regression: The case of the Republic of Srpska

Summary/Abstract: Purpose: In this paper, the authors try to develop a model for predicting the insolvency of trading companies from the Republic of Srpska. The research seeks to determine the statistically most significant financial indicator in predicting the insolvency of trading companies in the Republic of Srpska. Methodology: The research data sample in this paper consists of yearly data from 2017 to 2020 for two hundred trading companies from the Republic of Srpska. Binary logistic regression was used to develop the model. Results: As a result of the research, a model was created that successfully classifies 82.9% of solvent and 80% of insolvent companies, with a general efficiency rate of 81.4%. Conclusion: Based on the empirical research results, we can conclude that the hypothesis has been confirmed that the LR model can be formed on the basis of selected financial indicators as a tool for predicting the insolvency of trading companies in the Republic of Srpska.

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