Credit risk assessment of agricultural enterprises in the Republic of Serbia: Logistic regression vs discriminant analysis

Autor: Tekić Dragana, Mutavdžić Beba, Milić Dragan, Novković Nebojša, Zekić Vladislav, Novaković Tihomir
Jazyk: English<br />Serbian
Rok vydání: 2021
Předmět:
Zdroj: Ekonomika Poljoprivrede (1979), Vol 68, Iss 4, Pp 881-894 (2021)
Druh dokumentu: article
ISSN: 0352-3462
2334-8453
DOI: 10.5937/ekoPolj2104881T
Popis: Credit risk assessment of agricultural enterprises in the Republic of Serbia was analyzed in this research by applying discriminant analysis and logistic regressions. The aim of the research is to determine the financial indicators which financial analysts consider when analyzing a loan application that have the most influence on the decision to approve or reject a loan application. The internal determinants of credit risk of agricultural enterprises are analyzed, i.e., indicators of financial leverage, profitability, liquidity, solvency, financial stability and effectiveness. The analyzed models gave different results in significance of the observed indicators. The indicators that stood out as significant in both models are only indicators of profitability and solvency. The model of discriminant analysis has successfully classified rate 81.0%, while the logistic regression model has successfully classifies rate 89.8%. In modeling the credit risk of agricultural enterprises in the Republic of Serbia, the logistic regression model gives better results.
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