The banking sector plays a critical role in maintaining financial stability and supporting economic growth. In banking institutions, capital adequacy is a key determinant of financial resilience and operational performance. However, the relationship between capital adequacy and profitability remains debated, particularly regarding whether higher capital level consistently enhances bank performance or instead creates inefficiencies due to excess capital holdings. This study aims to examine the impact of capital structure on the profitability of convention banks in Indonesia while emphasizing the potential non-linear relationship between capital adequacy and bank profitability. The study utilizes panel data from 41 conventional banks in Indonesia over the period 2014 – 2024, comprising 451 observations. Bank profitability is measured using Return on Equity (ROE). The primary explanatory variables include Capital Adequacy Ratio (CAR) and its squared term (CAR2) to capture potential non-linear effects. Control variables include Non-Performing Loan (NPL), Operating Expenses to Operating Income (BOPO), Loan to Deposit Ratio (LDR) and Net Interest Margin (NIM), while macroeconomic variables include Gross Domestic Product Growth (GDP), Inflation (INF) and market concentration measured using the Herfindahl-Hirschman Index (HHI). The empirical analysis applies panel quantile regression using STATA to capture heterogeneous effects across different profitability levels. The results show the bank-specific factors significantly influence profitability. BOPO and NPL negatively affect ROE, while NIM positively contributes to profitability. Furthermore, the findings reveal a non-linear relationship between capital adequacy and profitability, indicating the existence of an optimal capital level in the banking sector. In contrast, macroeconomic factors such as GDP growth, INF and HHI do not significantly affect bank profitability. This study contributes to the literature by providing empirical evidence on heterogeneous capital-profitability dynamics using a quantile regression framework in the Indonesia banking industry.
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