Descriptive Statistical Analysis Table 4.4: Sample Descriptive Statistical Results

CHAPTER 4: RESEARCH RESULTS AND DISCUSSION

4.1. Qualitative research results

4.1.1. Ownership structure

Since 1986, Vietnam has carried out institutional reform, shifted to a market economy, and recognized the private sector, especially the Ordinance No. 37-LCT/HDNN8 on the State Bank of Vietnam and France. Order No. 38/-LCT/HDNN8 dated May 23, 1990 on Banks, Credit Cooperatives and financial companies, Law on State Bank, Law on Credit Institutions effective from October 1st/ 1998 created a premise for commercial banks with private capital to develop and changed the ownership structure of Vietnamese commercial banks.

Along with that, in the environment of market economy and international integration, enterprises with 100% state capital revealed weaknesses, were not active, and operated inefficiently. In order to actively integrate into the world and overcome the weaknesses of state-owned enterprises, the Government issued Decree No. 109/2007/ND-CP dated June 26, 2007 on transferring enterprises with 100% state capital. become a joint stock company. Accordingly, Article 1 of the Decree clearly states: “The objective and requirement of converting a 100% State-owned enterprise into a joint stock company (hereinafter referred to as equitization) is to convert enterprises that the State It is not necessary to hold 100% of capital to the type of enterprise with many owners; mobilize capital from domestic and foreign investors to improve financial capacity, innovate technology, to innovate management methods to improve the efficiency and competitiveness of the economy; Ensure harmony between the interests of the State, enterprises, investors and employees in enterprises; To perform openly and transparently according to market principles; Overcoming the situation of closed equitization within the enterprise; Associated with the development of the capital market, the stock market".

Implementing the policy of equitization of the State, Bank for Foreign Trade of Vietnam (Vietcombank - VCB) is the first 100% State-owned commercial bank approved by the Prime Minister in Decision No. 1289/QD. - TTg on September 26, 2007. In December 2007, Vietcombank officially conducted a public auction of shares on the Ho Chi Minh City Stock Exchange. Ho Chi Minh. Followed by Vietnam Commercial Bank for Industry and Trade (Vietinbank – CTG), Mekong Delta Housing Development Bank (MHB) and Vietnam Investment Bank ( BIDV ). The equitization of commercial banks with 100% state capital has contributed to promoting the diversification of ownership types and the ownership structure of commercial banks has changed significantly.

Following that, the Government issued Decree No. 141/2006/ND-CP, Decree No. 10/2011/ND-CP, Circular No. 13/TT-NHNN, Decision 254/QD-TTg forcing commercial banks to rapidly increasing legal capital to 3,000 billion and meeting international safety standards in a short time, this has created a wave of consolidation and merger between commercial banks and attracted domestic and foreign investment capital. . The beginning of the merger wave between commercial banks was the merger of three commercial banks including De Nhat Commercial Joint Stock Bank - Tin Nghia Commercial Joint Stock Bank - Saigon Commercial Joint Stock Bank. After that, the number of banks mergers and acquisitions increased rapidly, notably by the end of 2017 there were four state-owned commercial banks that were equitized, namely Industrial and Commercial Bank, Foreign Trade Bank, Investment Bank and Commercial Bank. Housing development in the Mekong Delta merged into an investment bank. Now, the remaining state capital in these commercial banks is Vietinbank: 64.46%; Vietcombank: 77.11%; BIDV: 95.28%. Particularly, Agriculture Bank (Agribank) is preparing to be equitized in 2019. In 2015 also completed the merger between other joint-stock commercial banks such as: Maritime Commercial Joint Stock Bank (Maritime Bank) and Mekong Development Commercial Joint Stock Bank. Kong (MDB); Southern Commercial Joint Stock Bank (SouthernbBank) and Saigon Thuong Tin Commercial Joint Stock Bank (Sacombank). There are three commercial joint stock banks that operate poorly, do not self-restructure or merge, and fall into negative equity. In order to ensure the stable operation of the commercial banking system, avoid system breakdown, and ensure the interests of depositors, the State Bank has purchased shares In 2015 also completed the merger between other joint stock commercial banks such as Maritime Commercial Joint Stock Bank (Maritime Bank) and Mekong Development Commercial Joint Stock Bank (MDB); Southern Commercial Joint Stock Bank (SouthernbBank) and Saigon Thuong Tin Commercial Joint Stock Bank (Sacombank). There are three commercial joint stock banks that operate poorly, do not self-restructure or merge, and fall into negative equity. In order to ensure the stable operation of the commercial banking system, avoid system breakdown, and ensure the interests of depositors, the State Bank has purchased shares In 2015 also completed the merger between other joint stock commercial banks such as Maritime Commercial Joint Stock Bank (Maritime Bank) and Mekong Development Commercial Joint Stock Bank (MDB); Southern Commercial Joint Stock Bank (SouthernbBank) and Saigon Thuong Tin Commercial Joint Stock Bank (Sacombank). There are three commercial joint stock banks that operate poorly, do not self-restructure or merge, and fall into negative equity. In order to ensure the stable operation of the commercial banking system, avoid system breakdown, and ensure the interests of depositors, the State Bank has purchased shares

required at a zero price to carry out a thorough and thorough restructuring. This commercial bank is Ocean Commercial Joint Stock Bank (Oceanbank), Global Petroleum Commercial Joint Stock Bank (GPB), and Construction Commercial Joint Stock Bank (CB). Thus, through the wave of mergers and acquisitions, the number of joint stock commercial banks has decreased from 37 units at the end of 2010 to 31 units at the end of 2017.

The mergers and acquisitions of commercial banks with the participation of foreign investors have increased the foreign ownership ratio in Vietnamese commercial banks. Some typical mergers and acquisitions are listed in Table 4.1.

Table 4.1: Mergers and acquisitions of commercial banks from 2010 to 2017

STT	Time	Business
first	April 2010	International Commercial Joint Stock Bank (VIB) transfers 15% shares to Commonwealth Bank of Australia (CBA)
2	March 2011	Vietinbank sells 10% of shares to finance company International Main (IFC)
3	December 2011	Consolidation of Tin Nghia Commercial Joint Stock Bank, Bank First Commercial Joint Stock Bank and Saigon Commercial Bank
4	2011	Mizuho buys 15% shares of VCB
5	December 2012	Vietinbank sells 20% shares to MUFGbank, Ltd
6	two thousand and thirteen	Ho Chi Minh City Housing Development Commercial Joint Stock Bank (HDB) merged with Commercial Joint Stock Bank Dai A
7	two thousand and thirteen	HDB acquires 100% capital of financial company Viet Societe Generale (France)
8	September 2013	Vietnam Oil and Gas Joint Stock Finance Company and Western banks merged into

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STT	Time	Business
		PVcombank
9	January 2014	Navibank transformed into a national bank people (NCB)
ten	June 2014	VPcombank acquires coal finance company Vietnamese minerals
11	March 2015	HDB transfers 49% shares of HDFinance for Credit Saigon Financial Group
twelfth	May 2015	Merger of MHB into BIDV
13	May 2015	Merger of Petrolimex Petroleum Commercial Joint Stock Bank (PGBank) to Vietinbank
14	August 2015	Mekong Development Joint Stock Commercial Bank merged to Maritime Bank
15	October 2015	Phuong Nam Commercial Joint Stock Bank merged into Saigon Thuong Tin Commercial Joint Stock Bank

Source: the author collects, summarizes on online newspapers Thus, from 2007 to now, experiencing changes in the business environment such as international integration, legal framework, requirements on safety standards Due to the economic crisis, Vietnamese commercial banks have grown in size, diversified in ownership forms, and improved their management level to adapt to the business environment and operate more safely. Especially, the implementation of the State's policies on equitization and restructuring of the commercial banking system has greatly changed the ownership structure of Vietnamese commercial banks. Private ownership and foreign ownership are possible

increased significantly, besides, the state ownership rate in commercial banks decreased.

In this thesis, the author collects data of 30 Vietnamese commercial banks in the period 2002 - 2017 to conduct quantitative research. Table 4.2 and chart 4.1 below describe the change in ownership structure of 30 Vietnamese commercial banks within the scope of the study during the period from 2002 to 2007.

Table 4.2: Ownership structure of 30 commercial banks selected for research (Appendix

1) from 2002 to 2017

Five	Equity
	Total (billion VND)	State ownership		Foreign ownership		Possession of a Natural Person
	Total (billion VND)	Total (billion copper)	Ratio (%)	Total (billion copper)	Ratio (%)	Total (billion copper)	Ratio (%)
2002	20.806	15,983	76.82	1.322	6.36	1.392	6.69
2003	28,718	22.774	79.30	1.453	5.06	1,913	6.66
2004	26.707	18,755	70.23	1.610	6.03	3,261	12.21
2005	32.868	20,728	63.06	2.020	6.15	5.593	17.02
2006	58,374	34.696	59.44	3,379	5.79	12,364	21.18
2007	103.922	51.517	49.57	7,151	6.88	26.742	25.73
2008	131,896	56,364	42.73	11,548	8.76	36,905	27.98
2009	167,055	64,160	38.41	20,465	12.25	44.471	26.62
2010	221,800	88,407	39.86	25,405	11.45	55.715	25.12
2011	274.653	105.644	38.46	32,760	11.93	74.253	27.04
2012	315,091	124.206	39.42	40,947	13.00	83.836	26.61
two thousand and thirteen	356.695	139,087	38.99	54.131	15.18	93,126	26.11
2014	374,970	144,436	38.52	61,458	16.39	94,011	25.07
2015	411,989	153.422	37.24	68,789	16.70	98,979	24.02
2016	448,651	167,395	37.31	76,087	16.96	110,849	24.71
2017	500,154	176,041	35.20	92,910	18.58	137,630	27.52

Source: the author collects, synthesizes and analyzes data from Orbis, Bankscope, annual reports and prospectus of 30 selected commercial banks (Appendix 1)

Figure 4.1: Changes in ownership types of 30 commercial banks selected for research (Appendix 1) from 2002 to 2017

% of state capital

% natural capital

% foreign capital

Source: the author collects, synthesizes and analyzes data from Orbis, Bankscope, annual reports and prospectus of 30 selected commercial banks (Appendix 1)

From the chart, we can see that the state ownership rate has decreased sharply from 2003 to 2009. Besides, the rate of foreign ownership and natural person has also increased sharply during the above period.

How does the above change in ownership structure affect the business performance of commercial banks, if so, how does each type of ownership affect? This will be further clarified in the quantitative research results.

4.1.2. Business performance

As discussed in Chapter 2, business performance is affected by external factors such as the legal environment, domestic and foreign economic environment, and internal factors such as the ability to apply technology. , quality level of employees, financial capacity, management capacity, structure

owned.

In the period from 1988 to now, external and internal factors have changed a lot. This has a significant impact on the business performance of Vietnamese commercial banks. Table 4.3, chart 4.2, and chart 4.3 will clearly show the fluctuations in business performance of 30 sampled commercial banks from 2002 to 2017.

Table 4.3: Statistical table of business performance of 30 commercial banks selected for research (Appendix 1) from 2002 to 2017

Five	Profit after tax (billion VND)	ROA (%)
2002	(1,782)	(0.49)
2003	870	0.19
2004	3.165	0.56
2005	4.692	0.67
2006	10,778	1.15
2007	18,074	1.31
2008	18,173	1.10
2009	26,429	1.18
2010	37,740	1.23
2011	41.066	1.10
2012	36.266	0.93
two thousand and thirteen	32,178	0.73
2014	31,390	0.62
2015	33,836	0.57
2016	43.512	0.62
2017	62,179	0.74

Source: the author collects, synthesizes and analyzes data from Orbis, Bankscope, annual reports and prospectus of 30 selected commercial banks (Appendix 1)

Figure 4.2: Changes in after-tax profits of 30 commercial banks (Appendix 1) selected for research from 2002 to 2017

total profit

Source: the author collects, synthesizes and analyzes data from Orbis, Bankscope, annual reports and prospectus of 30 selected commercial banks (Appendix 1)

Figure 4.3: Variation of return on assets (ROA) of 30 selected commercial banks (Appendix 1) from 2002 to 2017

ROA

Source: the author collects, synthesizes and analyzes data from Orbis, Bankscope, annual reports and prospectus of 30 selected commercial banks (Appendix 1)

Through charts 4.2 and 4.3, we can see that total profit has increased sharply since 2002

until 2010, then there was a partial decrease and then a sharp increase again from 2013 to 2017. For the business performance indicator measured by the ratio of profit after tax to total assets (ROA), there is very strong increase from 2002 to 2007, then there was an increase and decrease until the end of 2017.

4.1.3. Assessment of ownership structure and business performance

As shown in Section 4.1.1 and Section 4.1.2, it is found that the ownership structure and the ratio of profit after tax to total assets (ROA) of the 30 selected commercial banks fluctuated greatly over the period of time. period from 2002 to 2017.

Figure 4.4, shows that state ownership is negatively correlated with ROA. In contrast, the foreign ownership ratio is positively correlated. For natural person ownership, there is a positive correlation with ROA but it is not clear.

Figure 4.4: Change in ownership structure and return on total assets (ROA) of 30 selected commercial banks (Appendix 1) from 2002 to 2017

% State capital

% Natural capital

% Foreign capital

ROA

Source: the author collects, synthesizes and analyzes data from Orbis, Bankscope, annual reports and prospectus of 30 selected commercial banks (Appendix 1)

Variable	Number of mandarins close	Medium	Differrence standard	Small value best	Value biggest
ROA	443	1.078758	1.168033	-9.378	7.5
GOE	443	13.56787	33.02558	0	100
FOE	443	14.32707	21,97428	0	100
IOE	443	39.51737	31.10862	0	97.45
LOD	443	0.9236995	0.3083398	0.0008071	2.432482
LOE	443	6.639658	15.58025	0.0025763	252.0612
INF	443	7.642957	5.437313	0.6	19.9
GDP	443	6.651129	1.05083	5.03	8.48

4.1.4. Descriptive Statistical Analysis Table 4.4: Sample Descriptive Statistical Results

Source: Author calculated and analyzed from the research sample

The descriptive statistics table (Table 4.4) shows the number of observations, the mean of the variables, the standard deviation and the maximum - minimum values of the variables. Because the sample has a large space and a long time, commercial banks are selected with different sizes and characteristics, so the standard deviation of the sample is relatively large. The selected sample is that most commercial joint stock commercial banks and joint venture commercial banks operating continuously in Vietnam have multiple ownership forms, in which the average value of state ownership has the largest value with 33%. This shows the characteristics of state control over the activities of commercial banks in Vietnam.

4.2. Quantitative research results

4.2.1. Multicollinearity test

Table 4.5: Variable Correlation Matrix

Variable	ROA	GOE	FOE	IOE	LOD	LOE	INF	GDP
ROA	first
GOE	-0.1531	first
FOE	-0.0281	-0.1944	first
IOE	0.0905	-0.5059	-0.401	first
LOD	-0.0066	-0.0158	-0.0057	-0.0345	first
LOE	-0.1113	0.2888	-0.0828	-0.1056	0.1306	first
INF	0.2014	0.0141	-0.0453	0.0069	0.1424	-0.0187	first
GDP	0.1603	0.0439	-0.1126	0.0475	0.1611	0.0926	0.0186	first

Source: Author calculated and analyzed from the research sample

Table 4.6: Variance Iflation Factor (VIF)

Variable	VIF	1/VIF
IOE	2.08	0.481093
GOE	1.93	0.519309
FOE	1.61	0.622197
LOD	1.07	0.930802
LOE	1.12	0.890522
INF	1.03	0.975567
GDP	1.05	0.956541
Average VIF	1.41

Source: Author calculated and analyzed from the research sample

Analysis of the correlation matrix of variables (Table 4.5), found that the independent variables, the control variables have the absolute value of the largest correlation coefficient is 0.509<0.8. It is therefore concluded that there is no perfect multicollinearity and insignificant degree of multicollinearity among the single variables.

Analysis of the magnifying factorization table (Table 4.6), found that the value of

The maximum magnification factor of the variable is 2.08 and the value of the maximum exaggeration factor is

1.41 are all less than 10. It is concluded that there is no multicollinearity between one variable and the other group of variables.

4.2.2. Preliminary regression results and test results

Table 4.7: Regression results according to Pooled, REM, FEM models and results of model selection test, variance test, autocorrelation test

	POOLED	REM	FEM
GOE	-0.00614***	-0.0268*	-0.00772**
GOE	[-2.75]	[-1.87]	[-2.11]
FOE	-0.00291	-0.0140*	-0.00384
FOE	[-0.95]	[-1.82]	[-0.86]
IOE	-0.00146	-0.00781	-0.00326
IOE	[-0.59]	[-1.31]	[-0.88]
LOD	-0.223	0.709***	0.334*
LOD	[-1.25]	[3.15]	[1.65]
LOE	-0.00559	-0.00488	-0.00494
LOE	[-1.55]	[-1.40]	[-1.42]
INF	0.0441***	0.0381***	0.0407***
INF	[4.47]	[4.19]	[4.45]
GDP	0.196***	0.167***	0.180***
GDP	[3.79]	[3.35]	[3.71]
_cons	-0.135	-0.0745	-0.412
_cons	[-0.34]	[-0.14]	[-0.97]
WOMEN	443	443	443
R-sq	0.103	0.129
F-test	0.0000
Hausman test		0.0002

	POOLED	REM	FEM
Breusch pagan test			0.0000
Wooldridge test			0.0000
t statistics in brackets
* p<0.1, p<0.05, *p<0.01

Source: Author calculated and analyzed from the research sample

Perform regression according to Pooled model and FEM model, then perform F-test to select the appropriate model between the two Pooled and FEM models. The results show that F=0.0000<5%, so the decision to choose the FEM model will be more appropriate.

After regression according to the REM model, Hausman test is performed to select the appropriate model between the two FEM and REM models. The result is P-value

= 0.0002<5%, so it is decided that FEM will be better for the study sample.

When the FEM model is closed, the variance test and autocorrelation test (Breusch pagan test, Wooldridge test) are conducted. Both of these tests result in P-Value = 0.0000<5%, so it is concluded that the model is autocorrelated and has variable variance. To overcome these two disadvantages, the author uses the GLS estimation method to perform the regression and to fix the error.

4.2.3. Regression results and overcoming statistical hypothesis violation

Table 4.8: Regression results and variance correction, autocorrelation

Estimated covariances	=	30	Number of obs	=	443
Estimated autocorrelations	=	first	Number of groups	=	30
Estimated coefficients	=	8	Obs per group: min	=	7
Estimated covariances	=	30	avg	=	14.76667
			max	=	16
			Wald chi2(7)	=	46.32

Prob > chi2	=	0
Number of obs	=	443

ROA	Coef.	Std. Err.	z	P>z	[95% Conf.	Interval]
GOE	-0.0040306	0.0014428	-2.79	0.005	-0.0068585	-0.0012028
FOE	0.0064173	0.002898	2.21	0.027	0.0007374	0.0120973
IOE	-0.0011928	0.0019061	-0.63	0.531	-0.0049288	0.0025431
LOD	0.2750988	0.1293166	2.13	0.033	0.021643	0.5285546
LOE	-0.0044765	0.0029638	-1.51	0.131	-0.0102853	0.0013324
INF	0.0083881	0.0044532	1.88	0.06	-0.00034	0.0171163
GDP	0.0721791	0.0274803	2.63	0.009	0.0183188	0.1260395
_cons	0.3227337	0.244498	1.32	0.187	-0.1564737	0.801941

Source: Author calculated and analyzed from the research sample

Regression by GLS method while simultaneously correcting the variable variance error and autocorrelation error gives the following results:

- The variable GOE has a negative correlation with ROA, the correlation coefficient is α 1 = – 0.40306%, the significance level is 99%.

- The variable FOE has a positive correlation with ROA, the correlation coefficient is α 2 = 0.64173%, the significance level is 95%.

- Variable IOE has no statistical significance with ROA.

4.2.4. Summary of regression results

Table 4.9: Total results of regression and testing

	POOLED	REM	FEM	GLS
GOE	-0.00614***	-0.0268*	-0.00772**	-0.00403***
GOE	[-2.75]	[-1.87]	[-2.11]	[-2.79]
FOE	-0.00291	-0.0140*	-0.00384	0.00642**

	POOLED	REM	FEM	GLS
	[-0.95]	[-1.82]	[-0.86]	[2.21]
IOE	-0.00146	-0.00781	-0.00326	-0.00119
IOE	[-0.59]	[-1.31]	[-0.88]	[-0.63]
LOD	-0.223	0.709***	0.334*	0.275**
LOD	[-1.25]	[3.15]	[1.65]	[2.13]
LOE	-0.00559	-0.00488	-0.00494	-0.00448
LOE	[-1.55]	[-1.40]	[-1.42]	[-1.51]
INF	0.0441***	0.0381***	0.0407***	0.00839*
INF	[4.47]	[4.19]	[4.45]	[1.88]
GDP	0.196***	0.167***	0.180***	0.0722***
GDP	[3.79]	[3.35]	[3.71]	[2.63]
_cons	-0.135	-0.0745	-0.412	0.323
_cons	[-0.34]	[-0.14]	[-0.97]	[1.32]
WOMEN	443	443	443	443
R-sq	0.103	0.129
F-test	0.0000
Hausman test		0.0002
Breusch pagan test			0.0000
Wooldridge test			0.0000
t statistics in brackets
* p<0.1, p<0.05, *p<0.01

Source: Author calculated and analyzed from the research sample

With the goal of making the estimate with the most reliable regression results, the author takes the approach from the model and the simple estimation method to the complex model. At the same time, test the statistical hypothesis of linear regression and overcome the disadvantages.

Date published: 09/04/2022