Determinants influencing capital adequacy ratio of Vietnamese commercial banks

366 0.805 1.070 -0.569 0.324 1.989 1.238 1.015 2.392 
Sharpness (Kurtosis) 18.797 3.271 4.604 3.650 4.619 2.906 3.907 8.015 4.821 3.739 8.377 
Jarque-Bera 3082.272 12.790 103.746 31.157 74.419 13.488 12.831 423.431 97.622 48.258 535.327 
Probability 0.000 0.002 0.000 0.000 0.000 0.001 0.002 0.000 0.000 0.000 0.000 
No. of observations 248 248 248 248 248 248 248 248 248 248 248 
Source: Compilations by the authors 
 6
Descriptive statistics are compiled to show the basic characteristics of these variables. Table 2 summarizes the descriptive 
statistics of the variables including sample mean, median, maximum, minimum, standard deviation, deviation, Kurtosis, Jarque-
Bera statistics and probability (p value). All variables are asymmetric. More precisely, the deviations are positive for nine strings, 
whereas DEP and LOA have negative deviations. Kurtosis values of all variables show that the data is not normal distributed 
because the values of kurtosis are skewed from 3. Jarque-Bera statistics and the corresponding p values are calculated to test the 
assumption that data is standard normal distribution. Based on Jarque-Bera's statistics and p values, this assumption is rejected 
at the 1% significance level for all variables. The dependent and independent variables are tested for polymorphism based on a 
simple correlation matrix. As described in Table 3, they all have no collinearity problems evidenced by the fact that no specific 
variables are highly inter-correlated and there is no multicollinearity among these variables. This research employs the Feasible 
Generalized Least Square method for the panel data analysis. This method corrects the phenomenon of variance and auto 
correlation, which is superior to the method of fixed effects and the random effects model. 
Table 3 
Correlation Matrix Between Variables 
Source: Compilations by the authors 
4. Results and discussion 
𝐶𝐴መ𝑅 = 0.154 +(଴.଴ଶଽହ) 0.418(଴.ଷ଴଺)𝑁𝐼𝑀 + 6.01𝑒 − 09𝑆𝐼𝑍𝐸(ଵ.ସ଺௘ି଴଼) − 0.162 ∗∗(଴.଴଻଻) 𝐿𝐸𝑉 − 1.474 ∗∗ 𝐿𝐿𝑅 +(଴.଴଻଻) 0.018𝐷𝐸𝑃(଴.଴ଶଽ) − 0.023𝐿𝑂𝐴(଴.଴ଶ଼) − 0.008(଴.଴ସଷ଺)𝐿𝐼𝑄+ 3.425 ∗∗ 𝑅𝑂𝐴(ଵ.ସ଴଴) − 0.047(଴.ଶଵସ)𝑁𝑃𝐿 − 0.318 ∗∗∗ 𝑅𝑂𝐸(଴.ଵଵ଼) 
Note: i) Standard- errors are reported in brackets; (ii) ***/**/* Statistical significance at 1%, 5% and 10% levels, respectively. 
Table 4 
Summary of hypothesis testing results 
No. Variables Reject the 
hypothesis H0 
Sig. No. Variables Reject the 
hypothesis H0 
Sig. 
1 SIZE Yes - 6 ROA Yes 5% 
2 DEP No - 7 ROE Yes 1% 
3 LOA No - 8 NIM No - 
4 LLR Yes 5% 9 NPL No - 
5 LIQ No - 10 LEV Yes 5% 
Estimated results from the FGLS detailed regressions results are presented in above equation, in which all variables potentially 
affecting the capital adequacy ratio (CAR) are included in the regression model. The results show that LEV, LLR, ROA, and 
ROE. The ROA variable a positive effect on the CAR. The coefficient of the ROA variable indicates that if the profitability 
increases by 1 unit (expressed through an increase of 1 unit of ROA) will increase the bank's capital by 3.425 units. The LLR 
variable has a negative effect on the bank's capital adequacy ratio. This result shows the better the financial capability of the 
bank (the lower the rate of loan provision), the higher the capital adequacy ratio. This also shows that ensuring the quality of 
loans and avoiding loss of capital are the key factors that can help banks to maintain their capital adequacy. However, interesting 
results are found that the LEV and ROE variables have a negative impact (contrary to expectation) on the bank's capital adequacy 
ratio at a significant level of 1%. The coefficient of ROE variable shows that increase in the bank's profitability by 1 unit 
(represented by an additional 1 unit in ROE) reduces the bank's capital adequacy ratio 0.318 units, as shown in the estimation 
equation. The coefficients of the remaining variables are not statistically significant at the 10% level. This suggests that there is 
no sufficient evidence to conclude on the impact of NIM, SIZE, DEP, LOA, LIQ and NPL on the capital adequacy ratio of 
banks. The insignificance of these variables may be due to limited number of samples and period. In summary, LLR, ROA, 
ROE and LEV are shown to have significant effect on CAR. On the other hand, SIZE, DEP, LIQ, NPL and NIM do not have a 
significant impact on the capital adequacy ratio. The hypothesis test results are summarized in Table 4. The results of the study 
indicate that the variables LEV, LLR, ROE have a negative impact on CAR while ROA has a positive impact on CAR. The 
remaining variables SIZE, DEP, LOA, LIQ, NIM, and NPL do not significantly affect CAR. 
 CAR DEP LEV LIQ LLR LOA NIM NPL ROA ROE SIZE 
CAR 1 
DEP -0.002 1 
LEV 0.023 -0.350 1 
LIQ -0.026 -0.481 0.132 1 
LLR -0.088 -0.143 -0.020 0.078 1 
LOA 0.054 0.579 -0.153 -0.507 -0.238 1 
NIM 0.118 0.045 0.339 -0.098 -0.034 0.323 1 
NPL -0.053 -0.151 0.231 -0.098 0.426 -0.128 -0.013 1 
ROA 0.056 -0.140 0.242 0.055 -0.017 0.092 0.651 -0.150 1 
ROE -0.004 0.044 -0.200 0.049 -0.021 0.184 0.466 -0.269 0.830 1 
SIZE -0.004 0.337 -0.455 -0.249 0.073 0.414 0.050 -0.161 0.054 0.340 1 
H.V. Vu and N.D. Dang /Accounting 6 (2020) 7
5. Policy implications 
5.1. Vietnamese State Bank 
Credit Risk 
Continue to build and improve the bank information system: The State Bank needs to require commercial banks to build a 
system for information gathering and transmission safeguarded by a network security algorithm. The information collection, 
data transmission and links to networks for assessment are also to be improved to increase the autonomy and information sharing 
in the banking system. Need to develop a comprehensive Risk Management System for the Vietnamese commercial banking 
system, under a unified legal framework. Improve the banking inspection and supervision system, in a coordinated effort of 
inspection agencies, for the supervision of the financial markets and institutions in the economy, both domestically and 
internationally. 
Leverage, Return on Equity and Return on Asset in the Banks - mainly expressed in terms of operational risks 
The State Bank should improve a system of measuring, documenting, and regulating the operational risk management of banks. 
Build a database of operation risk throughout the banking system in order to detect and check on any operational risk events so 
that the new types of operational risks, their trends, and illegal behaviours can be identified, supervisory consultancy can be 
provided and information can be shared. 
Strengthen the role of the State Bank of Vietnam for supervising credit risk management activities of commercial banks 
Improve the effectiveness of inspection and supervision by the State Bank of Vietnam, as well as offering guidelines to 
commercial banks for compliances. 
5.2. Commercial Banks 
Provisions for potential loan losses 
Provisions for bad debts should be based on the risk characteristics of credit activities (lending activities) that a bank practices, 
the higher the credit risk, the larger the provisions will be required. Provisions for bad debt are also to be related to the bank’s 
capital position, as any unused provisions will be returned to equity based on the GAPP accounting standards. Loan loss 
provisions allow banks to have resources to deal with arising bad debts without affecting the bank's profitability. It is important 
that commercial banks assess the potential losses from credit activities and keep adequate provisions to pay for the losses resulted 
from credit risks. 
Equity and leverage 
To ensure the safety and soundness of a banking system, it requires banks to minimize risk taking and to increase capital of 
banks at the end. The basic principle is that as the level of risk taking by a bank increases, it should have a greater amount of 
capital reserves for payments. That is, the ratio of total equity to total assets is should be positively correlated with risk. This 
indicates that increasing equity is a necessary solution to maintain the safety of a bank, along with a reduction in risky assets. 
Currently Vietnamese commercial banks have now reached the required capital adequacy ratio of 9% of risky assets (according 
to Circular No. 36). It will be converted into 8% by 2020 comply with the Basel II standard. 
5.3. Other regulatory 
Ministries and industries need to take drastic measures in carrying out their functions and duties, to work out solutions to 
restructure the economy, to consolidate the banking system, and to develop and deepen the financial system further. 
Enhance the effectiveness of state supervision of commercial banks’ risk management activities for the purpose of minimizing 
risks in the course of business activities of commercial banks. 
Improve the quality of the stability analysis of the financial system and to develop an early warning system to prevent 
bankruptcies of commercial banks in the system. 
Ministry of Finance, Ministry of Justice, Ministry of Natural Resources and Environment, Ministry of Construction, Ministry 
of Planning and Investment, Ministry of Public Security, Supreme People's Procuracy, Court, Hanoi City People's Committee, 
Ho Chi Minh City and Vietnam Asset Management Company (VAMC) should coordinate to command the handling of rising 
bad debts situations and to resolve the large bad debt portfolio of the VAMC. Regulatory agencies should coordinate with the 
VAMC in handling and managing bad debts, these could include accelerating the process of completing legal documents, seizing 
and handling collateralized assets, improve the procedures for transferring collaterals and the tax requirements related to the 
transfer of collaterals. Recovery of bad debts can be done with different methods, such as urging debt recovery, seizing, selling 
collaterals, selling debt in accordance with the law through a public auction in a transparent manner. 
 8
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