Abstract

The study aimed at assessing the financial performance of the commercial banks in Afghanistan. It aims to examine the impact of Liquidity, Bank Size and Capital Ratio on Return on Assets (ROA) of commercial banks. The study takes the annual financial report of Afghan commercial banks for the period 2015–2024 and investigates the relationship between variables by using the mean of panel data regression analysis. For this study, ROA is considered as dependent variable, and the independent variables are Liquidity, Bank Size, and Capital Ratio. The data have been collected from the annual financial reports of banks, statistical reports of Da Afghanistan Bank and other official sources. The data were analyzed in Microsoft Excel and EViews software. The most important statistical tests used in order to achieve reliable econometric estimation are descriptive statistics, correlation and covariance analysis, cross sectional dependence tests and panel unit root tests. The findings showed that some variables are non-stationary, thus all variables were put in first difference to prevent spurious regression, and to ensure stationarity. Furthermore, it was found that there was heteroscedasticity and Panel Corrected Standard Errors (PCSE) obtained robust and reliable estimates. The model explains 4.47% of the variation in ROA (R² = 0.0447), while bank size has a positive and statistically significant effect on ROA (β = 0.0163, p = 0.026), while capital ratio (β = 0.0102, p = 0.173) and liquidity (β = −0.0147, p = 0.557) have no statistically significant effects. Explanatory power is not very high in the model, which is typical in banking research because of the effect of unobserved macroeconomic and institutional variables. The overall results indicate that the size of banks is a significant factor in the profitability of the Afghan banking sector and that the liquidity and capital strength have only minor influence. This study will be helpful for the policy makers, banking managers and researchers on the factors influencing banking performance in developing economies.

Keywords

Bank Size Capital Ratio Liquidity Panel Data Regression Analysis ROA