Determinants of the credit risk in developing countries: a case of Kosovo banking sector

In this research, the authors proposed a new method to evaluate borrowers’ credit risk and quality of financial statements information provided. They use qualitative and quantitative criteria to measure the quality and the reliability of its credit customers. Under this statement, the authors evaluate 35 features that are empirically utilized for forecasting the borrowers’ credit behavior of a Greek Bank. These features are initially selected according to universally accepted criteria. A set of historical data was collected and an extensive data analysis is performed by using non parametric models. Our analysis revealed that building simplified model by using only three out of the thirty five initially selected features one can achieve the same or slightly better forecasting accuracy when compared to the one achieved by the model uses all the initial features. Also, experimentally verified claim that universally accepted criteria can’t be globally used to achieve optimal results is discussed.

This study investigates the effect of credit risk and macroeconomic factors on profitability of 20 ASEAN banks, particularly from Indonesia, Malaysia, Thailand and Philippines, covering the period of 2012 to 2017. The unbalanced panel data were tested for heteroscedasticity and normality. A fixed effects model and a random effects model were utilized followed by simple ordinary least squares (OLS) regression. The obtained results show that credit risk and GDP growth negatively affect Return on Equity (ROE) at 5% level of significance. The inflation rate increases ROE by 0.323%. In terms of influence, inflation has the highest impact on ROE followed by GDP growth and credit risk. Credit risk and GDP growth negatively affect Return on Assets (ROA) at 5% level of significance. ROA was also influenced by an increase in inflation rate. Therefore, this study will help banks and bank managers, depositors, investors, policy makers and governments to identify factors affecting bank profitability.

The study investigates the impacts of firms-, industry-, and country-level covariates on the financing structure amongst the Indonesian listed companies. Using artificial nested testing procedure, the preferred models were selected that could illustrate the association between debt ratio and its determinants. By making use of the full sample, it was found that these three levels of determinants explain approximately 73% of leverage variations.
Further, the importance of these determinants on leverages across sectors is also investigated in this study. The sectoral behavior plays a crucial role as the firm- and sector-level covariates indicate more important variables than country-level covariates, which implies that the firm-level covariates become the main factors in firm financing structure determination.
The artificial nested testing procedure (F-test) was used choose the preferred models, which is suitable for each sector. The selection of models depends on the sectoral characteristics, which indirectly control the orientation and magnitude of relationships. Those three levels of determinants have different impacts on capital structure across sectors, which provides evidence that the sectoral behaviors indirectly tend to influence the association between determinants and firm financing pattern in the Indonesian context.