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This research explores the balanced panel data to examine the level of capital adjustment for major insured commercial banks over the 2002-2018 period using a two-step GMM estimator. The findings show that the speed of adjustment of the large insured commercial banks is faster than that of non-financial companies. The results contribute to a slower average adjustment pace of a total capital ratio than the total risk-based capital and capital buffer ratios. The adjustment of capital is faster in the post-crisis period than during and before-crises era. The adequately capitalized banks adjust capital ratio faster than well-capitalized banks. In contrast, the under-capitalized banks adjust the total risk-based capital ratio and capital buffer ratio more quickly than that of others. The low liquid banks needed a higher time to restore equilibrium than high liquid banks. The results of this study have economic significance for policy implications and future regulations.

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Using GMM framework on the data of the US commercial banks spanning over 2002 to 2018, this study shows that banks adjust their regulatory capital ratios faster than traditional capital ratios. Our results show that the speed of adjustment of regulatory capital ratios and traditional capital ratios increases in bank capital adequacy and bank liquidity, respectively. We also find that the speed of adjustment of regulatory capital ratios of too-big-to-fail banks is lower than well-capitalized, adequately-capitalized, nationally-chartered, and state-chartered banks. In addition, the speed of adjustment of regulatory capital ratios of commercial banks is higher in the post-crisis period than the pre-crisis era. Although scholars suggest that adjustment of capital ratios through rebalancing liabilities is more beneficial to the banks, our findings show that banks also use their assets side of balance sheet to rebalance their capital ratios.

This study used a balanced panel data set of USA well, adequately, under, significantly under and critically undercapitalized large commercial banks in pre, during and post-crisis period to investigate the effect of the capital buffer, tier one capital buffer and common equity buffer on risk and net interest margin. The Generalized Method of Moment (GMM) two-step estimation was applied. The conclusions showed that the capital buffer, common equity buffer, tier one capital buffer and total risk are negatively correlated. The findings of period dummies and subgroups dummies showed that capital buffer is influencing the total risk and net interest margin differently in pre, during and postcrisis. The results indicated that the interest margin is lower in pre-crisis and during crisis period than in the post-crisis period, which signifies the impact of capital restrictions imposed by regulators in Basel-III. The outcomes showed that the influence of capital buffer on the net interest margin is not similar in all the subgroups. In addition, the results indicated that there is a positive relationship between bank risk and net interest margin. The findings also displayed that the lagged risk and current risk are positively related.

PurposeThis research explores the role of economic growth to influence the inter-relationship between capital, liquidity and profitability of commercial banks in selected asian emerging economies.Design/methodology/approachTo achieve the research purpose, an empirical model was constructed to examine the role of economic growth in the inter-relationship between banks' capital, liquidity and profitability. The empirical model was tested through two stage lease square (2SLS) regression analysis using annual data of Asian commercial banks ranges from 2011 to 2019.FindingsThe findings indicate that bank capital and liquidity are interdependent and determined simultaneously. The outcome demonstrates that the strength of the inter-relationship between banks' capital, liquidity, and profitability improves when economic growth is taken into account in the analysis. The results report that market funding, loan ratio, credit risk, bank size and bank efficiency are significant indicators to influence commercial banks' liquidity, profitability and capital in Asian emerging economies. The findings are heterogeneous across large, medium and small-sized banks in emerging economies of Asia.Practical implicationsThe results highlight that the model provides robust results with respect to sign and significance. However, the coefficient remains underestimated without incorporating economic growth, which has important implications for decision-makers and bankers.Originality/valueTo the best of authors’ knowledge, this is the first study that examines the role of economic growth to influence the inter-relationship between capital, liquidity and bank profitability in the emerging economies of Asia.

This study examines the impact of asset, income, and funding diversification on the risk and stability of US commercial banks ranges from 2002 to 2019 by using two-stage instrumental variables and GMM technique. The findings reveal that funding and asset (income) diversification decreases (increases) the banks' risks. The results indicated that income diversification has a significantly detrimental impact on the banks' stability, whereas funding and assets diversification positively contributes to banks' stability. The impact of diversification on risk-taking and stability is heterogeneous for various categories and crisis period. Our study provides useful insights to policymakers and bank regulators.

This study aims to examine the impact of different capital ratios on Non-Performing loans, Loan Loss Reserves, and Risk-Weighted Assets by studying large commercial banks of the United States. The study employed a two-step system generalized method of movement (GMM) approach by collecting the data over the period ranging from 2002 to 2018. The study finds that using Non-Performing loans and Loan Loss Reserves as a proxy for risk, results support moral hazard hypothesis theory, whereas the results support regulatory hypothesis theory when Risk-Weighted Assets is used as a proxy for risk. The results confirm that the influence of high-quality capital on Non-Performing loans, Loan Loss Reserves, and Risk-Weighted Assets is substantial. The distinctive signs of Non-Performing loans, Loan Loss Reserves, and Risk-Weighted Assets have indications for policymakers. The results are intimate for formulating new guidelines regarding risk mitigation to recognize Non-Performing loans and Loan Loss Reserves and the Risk-Weighted Assets for better results. JEL Classification: G21, G28, G29