CREDIT RISK ASSESSMENT OF AGRICULTURAL COMPANIES IN THE REPUBLIC OF SERBIA: COMPARISON OF LOGISTIC REGRESSION AND DISCRIMINANT ANALYSIS - Tekić, Dragana; Mutavdžić, Beba; Milić, Dragan; Novković, Nebojša; Zekić, Vladislav; Novaković, Tihomir (Economics of Agriculture, 2021)
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.