ausman (1978) test to compare the fixed and random effects estimates of coefficients (Baltagi, 2001; Wooldridge, 2002) The intention is to find out whether there is a significant correlation between the unobserved individual specific random effects (αi) and the regressors The result of the Hausman test based on chi-squared statistics as reported in Table suggested that the corresponding effects are statistically LLR -0.244930* (0.098) NIM 1.423882*** (0.003) LOA -0.109049 ** (0.024) LIQ -1.565142 *** (0.008) Test that all u_i = 1.47 (0.0961) *, **, *** represent for 10%, 5%, 1% significance Source: Author’s Calculation P.T.X Thoa, N.N Anh / VNU Journal of Science: Economics and Business, Vol 33, No (2017) 51-60 58 Table Coefficient statistics Variable Sign Sigf.level SIZE - - LEV - - LLR - 10% NIM + 1% LOA - 5% LIQ - 1% Source: Author’s Calculation There are dependent variables that have effect on CAR at 1%, 5% and 10% SIZE and LEV have no statistically significant effect Hypothesis # The rationality lies in the fact that a larger SIZE can guarantee greater stability It is based on the assumption “too-big to concrete” The general opinion is that asset size is not inversely related to capital adequacy However, in this study, SIZE has no effect on CAR Hypothesis # The financial leverage of the bank is calculated by dividing its total assets by stockholders’ equity In general, the relationship between LEV and the capital adequacy ratio is expected to be positive because if we increase stockholders’ equity, we have to expect a higher capital adequacy ratio But for the Vietnamese banking industry in the period 2011-2015, LEV did not impact on CAR Hypothesis # The factor LLR has a coefficient of β= -0.244930 at a 10% level This means that when LLR increases unit, CAR will go down by -0.244930 units In general, LLR is expected to have impact in the same direction with CAR But it is not true in the Vietnamese banks in the model So a raised question is: Does the Vietnamese banking industry have to abide by regulations about the loans lost reserve or not? And are there disadvantages in SBV’s policies in this area? Hypothesis # The most significant factor is NIM with a coefficient of β = 1.423882 at 1% The net interest margin (NIM) has a positive coefficient The state-owned banks in Vietnam have been very profitable, retaining a lot of earnings So high revenues allow the banks to raise additional capital through retained earnings and to give a positive signal to the value of the company A high earnings or franchise value provides bank managers with easier access to equity capital and a selfregulatory incentive to minimize risk taking Hypothesis # The Beta coefficient of LOA ratio is negative at -0.109049, showing a negative relationship between LOA ratio and CAR The P -value is 0.0365 - smaller than 0.05 The negative sign of the beta coefficient shows that the increase of LOA ratio determines the reduction of CAR in the Vietnamese banking system This conclusion is in contrast with other studies in this field showing that a higher LOA ratio leads to higher CAR Hypothesis # The Beta coefficient of the LIQ ratio is positive at 1.565142, showing a positive relationship between the LIQ ratio and CAR The P-value is 0.0072 that is also smaller than 0.05 In this model, we analyze LIQ as a lag variable for one year as LIQ(-1) Cash and precious metals in the previous year have effect on the CAR ratio in the following year P.T.X Thoa, N.N Anh / VNU Journal of Science: Economics and Business, Vol 33, No (2017) 51-60 59 Table The results of hypotheses testing Hypotheses H1 Bank SIZE has a statistically significant impact on banks’ capital adequacy ratio H2 LEV ratio has a positive impact on banks’ capital adequacy ratio H3 Loan loss reserve LLR has a positive impact on banks’ capital adequacy ratio H4 Net interest margin NIM has a statistically significant impact on banks’ capital adequacy ratio Result Not H5 Loans ratio LOA has a negative impact on banks’ capital adequacy ratio H6 Liquidity ratio LIQ has a positive impact on banks’ capital adequacy ratio Supported Not Not Supported Not Source: Author’s Calculation Findings and conclusions The aim of this paper was to determine the relationship between some internal banking factors such as: assets of the bank, loans in total asset, leverage, net interest margin, loans lost reserve, cash and precious metals in total assets and the capital adequacy ratio in the Vietnamese banking system which is used as independent variable To test the relationship between the variables we use a linear regression analysis From the regression results we have come to the following conclusions: ● Bank size and Leverage have no impact on the capital adequacy ratio ● Net interest margin and Liquidity have a significant positive impact on the capital adequacy ratio ● Loans ratio is inversely related to the capital adequacy ratio in the Vietnamese banking system Limitations and future research In this paper, the author uses variables to indicate the effect on Capital Adequacy ratio However, there are only variables that have statistical 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