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Results of Regression Model Analysis with Two Independent Variables Service and Interbank


Table 4.2. Results of testing research hypotheses



Relationship

Estimated value

Standard deviation

Wald test

Sig value


Result


SIZE

0.000

0.000

0.061

0.044

Reject H1


ROA

-1.040

0.817

1,619

0.203

Reject H2

Y←

SERVICES

0.654

0.175

13,957

0.000

Accept H3


INTPAID

-0.014

0.014

1,021

0.312

Reject H4


BADLOAN

0.255

0.198

1,655

0.198

Reject H5


LABORCOST

0.000

0.001

0.619

0.431

Reject H6

Y←

INTERBANK

-0.361

0.091

15,768

0.000

Accept H7


Constant

-3.660

0.984

13,847

0.000


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Results of Regression Model Analysis with Two Independent Variables Service and Interbank

(Source: Author's synthesis and analysis from SPSS software)


Based on Table 4.2, we can see that there are only two statistically significant variables (Sig. < 0.01), namely SERVICES and INTERBANK (the Sig. coefficient is 0.000, meaning each variable is statistically significant at the 1% level). Although the SIZE variable also has Sig. < 0.05, it has a fairly low coefficient (0.000), so it can be concluded that the total assets of the bank do not have much impact on the bank's ability to receive foreign investors' capital contribution. In fact, it also shows that the size of a bank does not really evaluate its operating efficiency.

Income from services (SERVICE): The coefficient 𝛽 of the variable SERVICE is 0.654, meaning that the bank's income from services has a positive relationship with the bank's ability to have foreign shareholders and has the strongest impact among all variables. In fact, income from the service channel is gradually playing a role.


important in the development strategy of banks and has brought a significant source of revenue. Increasing the proportion of service income in the total operating income of banks is the right direction, helping to diversify business activities, reduce risks, especially credit risks. This is consistent with the orientation of most foreign strategic investors, which is to aim for sustainable, moderate and low-risk growth. This result is similar to the study of Forcarelli and Pozzolo (2001), who found that if a bank has a large service income in its total income, it is more likely to have the participation of foreign investors.

Lending position in the interbank market (INTERBANK) : The coefficient 𝛽 of the variable INTERBANK is -0.361, which means that the net interbank balance has an inverse relationship with the bank's ability to obtain foreign shareholders. Specifically, the more a bank has access to loans in the interbank market (ie borrows more in this market), the higher the possibility of obtaining foreign investors' capital contribution.

Variables not statistically significant: ROA, BADLOAN, LABORCOST, INTPAID:

Return on Assets (ROA) : This can be explained by the fact that in this study, the author only studies the factors affecting the investment in a bank, ignoring the analysis of the actions of the buying bank, so the information included in the analysis is only a part. This is similar to the research results of Houston and Ryngaert (1999). On the other hand, the ROA of the group of joint stock commercial banks in this period did not have much difference between banks with and without foreign shareholders due to the competitiveness in the operation process and the efficiency achieved by the bank. At the same time, foreign investors tend to want sustainable, moderate growth and are afraid of hot growth in banks, so they do not pay much attention to the ROA index.

Bad debt (BADLOAN) : In the period of 2011-2015, the Government directed the State Bank to resolutely implement the Project "Restructuring the system of credit institutions in the period of 2011-2015", the Project "Handling bad debt of the system of credit institutions".


and the Project "Establishment of Asset Management Company of Vietnam Credit Institutions". In addition, according to the economic restructuring process in the period of 2016-2020, the National Assembly issued Resolution No. 24/2016/QH14 dated November 8, 2016 on the economic restructuring plan in the period of 2016-2020. The task is to accelerate the process of handling bad debt effectively and apply Basel II at credit institutions with attention. After implementation, the bad debt situation has basically achieved the set target. Banks pay more attention to the bad debt issue in this period and are more cautious in the lending process. Therefore, the bad debt ratio in general does not have much difference between banks with and without foreign shareholders.

Labor costs (LABORCOST) : Competition between banks also goes hand in hand with competition in human resource quality. Only with stable and quality-assured human resources can a bank develop sustainably. If you want to have a human resource that meets this requirement, the cost must be competitive. Therefore, there is not much difference between banks with and without foreign shareholders in terms of this criterion.

Cost of capital (INTPAID) : In fact, the Vietnamese banking industry has developed to a certain extent during this period, and banks compete fiercely with each other in the process of finding sources of capital mobilization. Therefore, if banks want to mobilize loans, they must carefully consider the interest rate range. If the interest rate is not competitive, it will be very difficult to mobilize capital. On the other hand, banks are governed by the interest rate ceiling regulations from the State Bank of Vietnam, so there is not much difference in the cost of capital mobilization between banks.

In summary, the factors that attracted much attention from foreign investors when wanting to invest in Vietnamese joint stock commercial banks in the period of 2012-2018 were the ratio of net service income to total operating income of the bank and the ratio of net interbank balance to total assets of the bank. In this study, ROA was not significant, but this coincidentally coincided with the results of Houston and Ryngaert (1999), their study showed that ROA is not a reliable variable in predicting the ability of banks to be acquired in the US.


but ownership and management are the most effective explanatory variables. Similarly, the indicators of scale, bad debt, labor costs, and interest costs. Thereby, it can be seen that in Vietnam, banks with the participation of foreign investors are often more efficient than other banks. Because the main motivation for these banks to seek foreign shareholders is the desire to improve management capacity; transfer technology; develop banking products and services; and at the same time help their capital increase process go more smoothly. As for banks and foreign financial institutions that want to become strategic shareholders in Vietnam, most of them aim for sustainable, moderate growth; emphasize the certainty of fundamental factors, and are afraid of hot growth because it contains many potential risks.

From the above analysis, the author re-ran the regression model with two independent variables SERVICE and INTERBANK, the results obtained are as follows:

Table 4.3. Results of regression model analysis with two independent variables SERVICE and INTERBANK


Variable

Beta coefficient

Standard deviation

Wald test

Sig value

SERVICE

0.776

0.143

29,521

0.000

INTERBANK

-0.340

0.087

15,226

0.000

Constant

-2.946

0.576

26,198

0.043

From the results of table 4.3, the research model is re-established in the form of a diagram.

awake:


𝑷(𝒀 = 𝟏)

𝐥𝐧 [ ] = −𝟐. 𝟗𝟒𝟔 + 𝟎. 𝟕𝟕𝟔 ∗ 𝑺𝑬𝑹𝑽𝑰𝑪𝑬 − 𝟎. 𝟑𝟒𝟎 ∗ 𝑰𝑵𝑻𝑬𝑹𝑩𝑨𝑵𝑲

𝑷(𝒀 = 𝟎)


We can also represent the equation in another form:

𝐏(𝐘 = 𝟏) = 𝐞 (−𝟐.𝟗𝟒𝟔+𝟎.𝟕𝟕𝟔∗𝑺𝑬𝑹𝑽𝑰 𝑪𝑬−𝟎.𝟑𝟒𝟎∗𝑰𝑵𝑻𝑬𝑹𝑩𝑨𝑵𝑲)

𝐏(𝐘 = 𝟎)


This equation will be the basis for the author to calculate and make forecasts in 2019.


4.3.3. Testing the research model


4.3.3.1. Model fit test (Omnibus test)


Table 4.4. Omnibus Testing



R squared

Df

Sig. coefficient

Model

115,994

2

0.000

(Source: Results from SPSS software)


Based on the results of the model suitability test in Table 4.4, we see that the Sig. coefficient < 0.01. Therefore, it can be concluded that the model shows that the correlation between the dependent variable and the independent variables in the model is statistically significant with a 99% confidence interval.

4.3.3.2. Testing the explanatory power of the model


Table 4.5. Results of testing the model's explanatory power



-2 Log likelihood

Cox & Snell R Square

Nagelkerke R Square

Model

78.153 a

0.553

0.747

(Source: Results from IBM SPSS Statistics software)


Based on table 4.5 we can see:


The explanatory level coefficient of the Nagelkerke R Square model = 0.747. This means that 74.7% of the change in the dependent variable is explained by the independent variables in the model, the rest are other factors. This coefficient is quite high, proving that the model is quite suitable for the data in Vietnam.

Besides, the value of -2 Log likelihood= 78.153 a is not too high (the smaller this value, the more suitable the model is), showing that the model is relatively suitable for application.

4.3.3.3. Testing the predictive accuracy of the model


Table 4.6. Results of testing the predictive level of the model


Observe


Correct prediction rate



Y

0

55

3

94.8

1

6

80

93.0

Model Predictability (%)

93.8

Y

0 1


(Source: Analysis results from SPSS software)

Based on the results table 4.6, we see:


Of the 58 cases where banks do not have foreign shareholders, the model predicted correctly in 55 cases and incorrectly in 3 cases. The correct rate is 94.8%.

Of the 86 cases of banks with foreign shareholders, the model predicted correctly in 80 cases and incorrectly in 6 cases. The correct rate is 93.0%.

The model's prediction accuracy rate is 93.8%.

Thus, from the above test results, we can conclude that the model is quite suitable for the data set in Vietnam. The results collected from the model are reliable.

4.3.4. Applying the model for forecasting purposes in 2019


Based on the results of the model implemented with sufficient reliability drawn from the above tests, the author performed calculations based on audited financial statements of banks in 2018 to predict the possibility of foreign investors' participation in capital contribution to some Vietnamese joint stock commercial banks in 2019, the results obtained are as follows:

According to the predicted results from Table 4.7, except for eight joint stock commercial banks that are unlikely to receive capital contributions from foreign investors, namely BAB, KLB, LPB, NamABank, NCB, PGBank, SGB, VietCapitalBank, the remaining banks tend to have foreign shareholders in 2019.

It can be seen that 2019 will be an exciting year in the field of attracting foreign investment in banking.


On the other hand, many banks still have a ratio for strategic investors. Typically BIDV and Vietcombank. According to information from these banks, Vietcombank has started to contact foreign investors, hired valuation consultants and carried out a plan to offer 10% of its capital and it is possible that Singapore's GIC Investment Fund and Japan's Mizuho Bank will become strategic shareholders of this bank in the future. And Korea's KEB Hana may be the bank that buys BIDV's shares to expand its business in the Vietnamese market.

Table 4.7. Model forecast results in 2019



Bank

Criteria 2018 (%)

Forecast results for 2019

SERVICE

INTERBANK

Probability (Y=1)

Conclude

ABBank

16.70

0.74

0.9999

Have CĐNN

ACB

10.39

(0.06)

0.9941

Have CĐNN

BAB

3.15

(1.34)

0.4885

No CĐNN

BaoVietBank

3.09

(16.65)

0.9940

Have CĐNN

BID

7.60

(1.95)

0.9738

Have CĐNN

CTG

5.69

(3.75)

0.9395

Have CĐNN

EIB

8.65

(2.38)

0.9898

Have CĐNN

HDB

2.62

(12.02)

0.9598

Have CĐNN

KLB

3.27

(0.14)

0.4104

No CĐNN

LPB

1.27

(0.38)

0.1381

No CĐNN

MBB

8.15

1.61

0.9446

Have CĐNN

MSB

4.20

(13.89)

0.9936

Have CĐNN

NamABank

1.61

(1.34)

0.2240

No CĐNN

NCB

1.48

(5.74)

0.4882

No CĐNN

OCB

7.18

(5.63)

0.9895

Have CĐNN

PGBank

2.16

(0.11)

0.2258

No CĐNN

PvcomBank

4.09

(8.05)

0.9511

Have CĐNN

SCB

19.81

(8.96)

1.0000

Have CĐNN

SeABank

2.98

(9.46)

0.9299

Have CĐNN

SGB

5.02

0.08

0.3484

No CĐNN

SHB

22.58

(4.91)

1.0000

Have CĐNN

STB

30.35

(1.38)

1.0000

Have CĐNN

TCB

23.32

(4.13)

1.0000

Have CĐNN


TPB

4.57

(8.14)

0.9667

Have CĐNN

VCB

8.63

6.07

0.8442

Have CĐNN

VIB

9.95

(12.62)

0.9999

Have CĐNN

VietABank

(0.71)

(12.59)

0.6871

Have CĐNN

VietCapitalBank

1.27

(3.03)

0.2824

No CĐNN

VPBank

5.84

(8.30)

0.9880

Have CĐNN

(Source: Author's own calculation based on model and data from financial statements of commercial banks in 2018)

Note that the predicted probability given by the author above is entirely based on the data reported by Vietnamese joint stock commercial banks. The author has not considered the aspect originating from foreign investors when participating in this activity. Therefore, a certain bank may have a fairly high probability of having foreign shareholders but it does not happen in 2019, possibly because the bank has not found a suitable partner with the set development orientation. Therefore, the predicted result only gives a general view of the possibility of having foreign shareholders in Vietnamese joint stock commercial banks with a correct prediction probability of about 93.8%. In addition, readers will see that the probability of having foreign shareholders of some banks will be higher than other banks.

Chapter 4 Summary


Based on the research hypotheses set out in Chapter 2, the author builds measurement indicators, calculates data and runs the Binary Logistic regression model. According to the results obtained, the model has two statistically significant variables, SERVICE and INTERBANK. The author also conducted the necessary tests to test the suitability, explanatory level and predictive accuracy of the model to see if the model can explain the data set in Vietnam or not, the results show that the model is quite suitable. After completing the testing process, the author also applied the model to make necessary predictions about the possibility of which domestic joint stock commercial banks having foreign shareholders in 2019.

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