AI Summary & Key Takeaways
AI InsightAccording to the results, the banks’ performance is affected by several liability structure variables.
📌 3 Key Takeaways
Abstract
The Aim of this paper is to examine the possible relationship between liability structure and bank performance. In this context, panel data regression method is used to analyze relationship between bank performance and liability structure of banks. The main data source in this study is The Banks Association of Turkey’s banking statistics between 2005-2018. In the analysis, liability preferences of Turkish banks are used as independent variables and CAMELS performance scores of banks are used as dependent variable. Additionally, variables that are admitted in literature as bank performance determinants are taken into consideration in bank performance model as control variables. According to the results, the banks’ performance is affected by several liability structure variables. Use of loans-especially long term loans- and to have high saving deposits/total deposits positively affect bank performance; while extensive use of non-deposit liabilities, third alternative liability sources, long-term deposits, and foreign currency loansnegatively affect bank performance. As with other liability structure variables, high capital adequacy ratio and leverage also have negative effect on bank performance. Moreover, as control variables GDP per capita, inflation rate, interest rate, bank size, bank efficiency, bank liquidity, bank risk and bank market share have a statistically significant effect on bank performance.