The Determinants of Profitability in the City Commercial Banks: Case of China

This study uses a panel data regression model to investigate how internal and external factors affect the profitability of city commercial banks in China. The research sample consists of 16 listed city commercial banks with an unbalanced dataset covering the time period within the period of 2008-2020. A panel data regression method is utilized to investigate the factors that influence the profitability of city commercial banks in China. There are several estimation methods in panel data, and the most commonly employed models are the fixed effects and random effects models. The pooled OLS model is often used for comparison for panel data regression, and the appropriate model will be determined by statistical hypothesis testing. The results show that internal explanatory variables such as bank size, capital adequacy, credit quality, and operating efficiency and external explanatory variables such as province GDP and inflation have a significant impact on the profitability of city commercial banks, while liquidity has no significant effect on the bank's profitability. The paper contributes to the relevant literature by identifying the determinants of city commercial banks' profitability considering the latest situation of the banking sector in China and provides practical implications from the perspective of improving bank profitability, which are important for both banking management and regulators and for the municipal and state.