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Research Results on the Impact of Competition on Banking Stability


Loans

8.43*

(1.93)

3.89**

(2.24)

12.75***

(3.51)

0.481

(1.49)

0.812**

(2.17)

Deposits

17.34***

(4.11)

0.00236

(0.36)

-3,418***

(-51.68)

-0.236

(-0.34)

0.617

(0.59)

GDP

-174.1***

(-15.97)

-0.0292**

(-2.07)

2,129***

(7.66)

18.17**

(2.24)

16.07*

(1.70)

INF

0.29

(0.31)

-0.0189***

(-13.03)

-0.365***

(-18.64)

-1,344*

(-1.76)

-2,911***

(-3.26)

Constant

219.6***

(17.73)

0.0646***

(13.37)

0.966***

(4.02)

-2,281**

(-2.49)

-2,927***

(-2.81)

N

300

300

300

300

300

VIF

1.39

1.36

1.34

1.38

1.31

R 2

0.6453

0.5739

0.5329

0.7567

0.4789

F (p-value)

66.17

Prob > F=0.0000

21.32

Prob > F=0.0000

44.35

Prob > F=0.0000

133.12

Prob > F=0.0000

33.44

Prob > F=0.0000

F-test

F(27, 264)=6.36

Prob > F=0.0000

F(27, 284)=16.42

Prob > F=0.0000

F(27, 284)=2.21

Prob > F=0.0008

F(27, 264)=3.34

Prob > F=0.0000

F(27, 264)=14.05

Prob > F=0.0000

Hausman test

p-value = 0.0000

p-value = 0.0000

p-value = 0.0000

p-value = 0.0000

p-value = 0.0000

PSTD Audit

Chi2 (28)=10074.11

Prob>chi2=0.0000

Chi2 (28)=3109.86

Prob>chi2=0.0000

Chi2 (28)=1530.80

Prob>chi2=0.0000

Chi2 (28)=105.79

Prob>chi2=0.0000

Chi2 (28)=102.28

Prob>chi2=0.0000

Wald test

Chi2(8)=13906.46

Prob>chi2=0.0000

Chi2(8)=2197.97

Prob>chi2=0.0000

Chi2(9)=464859.50

Prob>chi2=0.0000



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Research Results on the Impact of Competition on Banking Stability

Note: The symbols (***), (**), (*) represent statistical significance levels of 1%, 5%, 10% respectively.

Source: Author's synthesis from research results


4.2.2 Research results on the impact of competition on banking stability

To study the impact of competition on banking stability, the thesis conducted multiple model regressions and performed a series of related tests as mentioned in the previous section to test the regression coefficients of the variables in the model, while handling the phenomena of multicollinearity, heteroscedasticity and endogeneity of the model. The results shown in Table 4.5 show that the statistical significance of the regression coefficients reflects that the implementation of competitive strategies by banks has had a positive impact on stability at Vietnamese commercial banks. Thus, hypothesis H 2 is accepted.

The impact of competition on bank stability through Z-Score coefficient : The regression results show a statistical significance of 1% showing a negative correlation between the Lerner index and the stability of Vietnamese commercial banks, reflecting that the higher the Lerner index, the lower the level of market competition of the bank, causing the stability of the bank to also decrease. Thus, competition really has a significant impact on bank stability. The model results using the GMM method have estimated the impact of the Lerner index on the Z-Score coefficient with a high level of significance. Some authors in their research also show similar results and support the Competition - Stability viewpoint to encourage competitive activities in banks.

The impact of competition on bank stability through the Return on Assets Ratio: The regression model results of the impact of the Lerner index on ROA give a statistical significance level of 1%. Thereby, the positive correlation shows that when the level of bank competition decreases, bank profits also decrease. This is consistent with the initial research expectation. At the same time, it is consistent with the view that encourages banks to increase market power to seek profits and further improve the efficiency of using profitable assets (Soedarmono and Tarazi, 2015; Fiordelisi and Mare, 2014; Fernandez and Garza-Garcia, 2012; Ariss, 2010).

The impact of competition on banking stability through the Return on Equity ratio: Similar to the initial expectation of the thesis, the Lerner index has a relationship


inversely with the return on equity. That is, the level of competition in the bank positively affects the efficiency of using equity. When a bank carries out activities to increase competitiveness in its business strategy, shareholders will pay more attention and closely monitor the bank's capital, requiring bank managers to be more cautious in the process of using equity. As a result, the average return on equity also increases effectively and sustainably.

Impact of competition on risk-adjusted return on assets (RAR ) and equity (RAR ) : The regression model results measuring the impact of competition, showing the Lerner coefficient, on risk-adjusted return on assets (TAR) and equity (Equity) show a statistical significance of 1%. This estimate reflects that increased bank competition will have the effect of promoting bank profits. This profit level under the positive influence of bank competition activities after adjusting for fluctuations in income caused by risks still shows that it brings certain financial efficiency to the bank, proving that the bank's competitive strategies have really contributed to further strengthening the stability of Vietnamese commercial banks.


Table 4.5: Results of estimating the impact of competition on banking stability through the indicators Z-Score, ROA, ROE, RAR ROA , RAR ROE

Dependent variables: Z-Score – Bank default risk assessment coefficient; ROA – Return on total assets; ROA – Return on total equity;

RAR ROA – Risk-adjusted ratio of ROA; RAR ROE – Risk-adjusted ratio of ROE.

Independent variables: Lerner – Level of competition; Lerner 2 – Square of Lerner coefficient; Size – Bank size; Growth – TTS growth rate; Loans – Total loans on TTS; Deposits – Total capital mobilization on TTS;

Estimation method: GLS, GMM

Regression model: Bankstab i,t = α 0 + α 1 Bankstab i,t-1 + α 2 Lerner i,t + α 3 Lerner i,t 2 + β j , Control i,t + β j ,, Control ' i,t + ε i,t


Variable name

Z-Score

ROA

ROE

RAR ROA

RAR ROE

Z-Score t-1

-0.213***

(-5.07)

ROA t-1

0.0798***

(6.73)

ROE t-1

-0.0594***

(-8.74)

RAR ROAt-1

0.866***

(31.80)

RAR ROEt-1

0.646***

(15.10)

Lerner

-26.02***

(-0.77)

-0.0180***

(-1.25)

-0.087***

(-2.32)

-3,754***

(-1.82)

-3,425***

(-1.18)


Lerner 2

7,393*** (0.46)

0.00833*** (1.50)

0.00764*** (2.11)

0.128*** (2.67)

1,754*** (1.23)

Size

-10.32*** (-9.62)

-0.00276**** (-7.97)

-0.0106*** (-6.67)

-0.230*** (-3.83)

0.120*** (2.10)

Growth

-0.521

(1.56)

0.000501*** (3.59)

0.0673*** (5.03)

-0.106** (-2.09)

0.247*** (4.21)

Loans

17.20*** (2.64)

0.00460* (1.89)

-0.434*** (-6.99)

0.383

(1.17)

-0.758*** (1.98)

Deposits

21.22*** (5.19)

-0.000194

(-0.04)

-3,393*** (-41.98)

-0.616*** (-0.88)

-0.0310*** (-0.03)

GDP

-127.6*** (-7.18)

0.0122

(0.81)

1,296***

,10)

25.76*** (3.35)

21.21** (2.32)

INF

1,820*** (3.53)

-0.0164*** (-9.56)

-0.371*** (-9.43)

-1,247*** (-1.59)

0.00693

(0.80)

Constant

176.9*** (5.66)

0.0653*** (6.75)

2,624*** (3.29)

-1.789** (-1.17)

-2,886*** (-3.14)

N

300

300

300


300

VIF

1.36

1.33

1.30

1.35

1.28


R 2

0.6375

0.6267

0.6310

0.7469

0.4881

F (p-value)

56.67

Prob > F=0.0000

19.20

Prob > F=0.0000

378,5044,02

Prob > F=0.0000

107.37

Prob > F=0.0000

30.73

Prob > F=0.0000

F-test

F(27, 264)=6.35 Prob > F=0.0000

F(27, 264)=1.79 Prob > F=0.0000

F(27, 264)=2.21 Prob > F=0.0000

F(27, 264)=3.28 Prob > F=0.0000

F(27, 264)=2.38 Prob > F=0.0000

Hausman test

p-value = 0.0000

p-value = 0.0000

p-value = 0.0000

p-value = 0.0000

p-value = 0.0000

PSTD Audit

Chi2 (28)=85194.44

Prob>chi2=0.0000

Chi2 (28)=1687.53

Prob>chi2=0.0000

Chi2 (28)=1849.61

Prob>chi2=0.0000

Chi2 (28)=202.23

Prob>chi2=0.0000

Chi2 (28)=481.76

Prob>chi2=0.0000

Wald test

Chi2(9)=15153.01

Prob>chi2=0.0000

Chi2(9)=650.79

Prob>chi2=0.0000

Chi2(9)=1.34e+06

Prob>chi2=0.0000



Note: The symbols (***), (**), (*) represent statistical significance levels of 1%, 5%, 10% respectively.

Source: Author's synthesis from research results


4.2.3 Research results on the impact of diversification and competition on banking stability

After regressing the models on the impact of income diversification and competition on banking stability of 28 Vietnamese commercial banks, the thesis continues to examine the impact of diversification, in the context of commercial banks using it as one of their competitive strategies, on banking stability. The expansion of Vietnamese commercial banks into non-interest-bearing areas will contribute to increasing their competitiveness. However, how will this affect the stability and sustainability of banks? The thesis uses many regression models with many dependent variables to measure banking stability. The regression results for 28 Vietnamese commercial banks are all statistically significant and consistent with research expectations (results in Table 4.6). The regression results outline different levels of influence of the research factors in the model. The R-Div variable shows the level of income diversification of the bank, which has a positive impact on the Z-Score coefficient in the regression model using the GMM method with a significance level of 1%. The sign of the correlation coefficient in model (3) is opposite to the sign of the correlation coefficient in model (1). However, when considering the correlation with the variables ROA, ROE, RAR ROA and RAR ROE , the regression coefficient has a negative sign and is not statistically significant. With the GMM method, the income diversification variable shows a positive correlation with bank profits, similar to the regression result of model (1). Thus, in this model (3), it shows that the income diversification of the bank affects

positively to its stability in the case of 28 commercial banks in Vietnam.

For the Lerner index used in the regression model (3), the correlation sign of the regression coefficient is negative, which is the same as the regression result of model (2). However, the statistical significance of the impact of Lerner on the Z-Score coefficient is 1%, with the remaining dependent variables ROA, ROE, RAR ROA , RAR ROE being 1%. The estimated results are completely reliable because the tests performed afterwards to handle the phenomena of variance change and endogeneity between variables are appropriate. Thereby, it shows that competition is a factor that has a positive impact on bank stability for commercial banks in Vietnam.


Considering the impact of diversification on the relationship between competition and banking stability, the thesis regresses the interaction variable Lerner*R-Div to study whether when Vietnamese commercial banks use diversification strategy as one of the competitive methods, the results will bring more stability in their business operations. The results of 5 regression models with dependent variables of banking stability including Z-Score, ROA, ROE, RAR ROA and RAR ROE all give results with statistical significance of 1%. The regression coefficient is negative, proving that the interaction variable has a negative impact on the dependent variables. This is contrary to the initial research expectation that diversification is really a bridge, or a catalyst to help increase and make the impact of competition on banking stability more sustainable. However, from the economic perspective, from the regression results of model (3) on the interaction variable between diversification and competition, it can be analyzed that in a competitive environment between banks, the implementation of a diversification strategy can lead to financial instability for that bank. The reason for failure is that under the pressure of competition to gain market share, banks can participate in activities or increase the search for profits from areas that are potentially quite risky. At that time, the bank will face financial instability. Therefore, in this case, the financial instability of banks can be born from fierce competition between banks with the desire to create profits and distinguish each other through non-traditional activities, but these banks lack experience in detecting, managing and controlling newly arising risks.

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