Determinants of Capital Adequacy of State-Owned Commercial Banks in Bangladesh.

Abstract

For establishing a healthy banking structure, and for comparing the ability of banks with global standard, banks must keep certain amount of CAR (Capital Adequacy Ratio) to ascertain that banks can manage their risk exposures. This CAR is set by Basel which is an international regulatory system of capital of banking industry. Bangladesh bank also implement Basel-3 from 2015, January. According to Basel-3 a bank has to keep minimum 10% of their capital and 2.5% capital conservation buffer, in total 10%+2.5%=12.5% of their risk weighted asset as CAR. This regulation of minimum capital requirement is kept to ensure that banks keep enough capital to face their risk. By this, Bangladesh banks lower the risk and protect the banks from being default. CAR is measured by tier-1 (core capital) plus tier-2 (supplementary capital) divided by banks RWA. This report aims to examine the relationship between CAR and determinants (Firm-Specific and Macroeconomic drivers) of CAR. This analysis of data is based on the sample of 5 State-Owned Commercial Banks namely Sonali, Basic, Agrani, BDBL, and Janata Bank for the duration of 2011 to 2021. This analysis has been done through a panel data regression by statistical software STATA in pooled OLS, Random Effect, Fixed effect, GLS, GMM, and Unit Root Test. Here, have highlighted how some bank-specific and macroeconomic factors affected the CAR throughout the period from 2010 to 2021. Firm-specific factors that influence CAR, including bank size, deposits, bank loans, loan deposit, loan loss provisions, ROA, NIM, Leverage, Cost to income, NPL to total loan. The macroeconomic factors are GDP, inflation, and foreign remittance. In OLS method 4 variables, in fixed effect one variable and in Random effect only 4 variables have been found significant. These models suffers from the problem of Multicollinearity, Heteroscedesticity, Model Specification Bias and Autocorrelation. That’s why GLS, GMM and Unit root test has been incorporated. GMM shows out of 13 variables 8 have been found significant in affecting CAR namely lag period CAR, bank-size, deposits, LA, LD, loan provisions, ROA, leverage, NPL, and constant. Unit root test suggest all variables are stationary to include in this model except deposits.