The objective of this research project is to explore the effect of mergers and acquisitions on the

financial performance of commercial banks in Vietnam. The study is limited to a sample of banks

listed on the Vietnam stock market that merged/acquired between the years 2011-2015.

Comparisons are made between three years before and three years after acquisition, while the

year of merging/acquisition is excluded. Using financial ratio analysis and paired t’test, the study

reveals that merge and acquisition transaction does have effect on the overall financial

performance of commercial banks in Vietnam. Using regression model, the direction of effect is

estimated. The model suggests that M&A between commercial banks in Vietnam make the

profitability of surveyed banks deteriorated. Thus, M&A has negative impact on the profitability of

banks. It is suggested that the reason for this decrease because the combination of strong bank

with weak bank can lead to the decrease of profitability. This research helps to contribute to

evaluate the impact of Restructuring Banking System Project in period 2011-2015 of Vietnamese

Government. It should be undertaken for longer time span, to check whether in the longer time,

the profitability of banks after merge and acquisition increase or not.

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impact on financial performance of banks surveyed.
For control variables, total_asset also has negative influence on ROE of banks. The
results for total_asset is that estimated coefficients on the total_asset is negative (β2= - -
1.208E-09***) and statistically significant at the 1% level. Thus, according to this result, the
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increase of banks’s size doesn’t really increase the ability to create profit of bank, but make
it weaker. However, the decrease of ROE ratios derived from too large scale of total_asset
is really small, but still meaningful.
In the context of participating on M&A, lvr shows the changes in the same way with
ROE. The estimated coefficients of lvr is positive (0.019304) and statistically significant at
the 5% level. Thus, as ROE increase, banks have to face with problem of debt to equity ratio
increases, which means that the solvency ability of banks decreases.
For GROWTH, the estimated coefficients on the GROWTH is positive (β3= -0.006723)
and not statistically significant. This means that with the sample of banks being surveyed,
GROWTH has positive impact on ROE of banks. As GROWTH increase, along with the
improvement in net sale (because GROWTH is calculated by (SALEn – SALEn-1)/SALEn-1),
profitability of bank also increases. However, this conclusion does not have statistical meaning, so
if the sample has larger amount of observation, this result could be changed.
The estimated intercepts are positive, indicating that there is 0.008441 in value of
ROE is unexplained by the dependent variables. However, the probability (p-value) of
intercept has no statistical meaning (larger than 10%). Therefore, this value could be changed
if the sample is in larger scale.
With regard to the coefficient of determination
R squared of the model is pretty large 56.9%, which means that the dependent
variables ROE can be explained 56.9% by this model. Thus, this model has high meaning in
explaining the value of ROE.
Thus, by using OLS regression, we have the estimated model as following:
ROE = 0.008441 + -0.033895* MGR + 0.019304*LVR +-1.208E-09*total_asset +-
0.006723*GROWTH + Ɛ (4.1)
Diagnostic test to evaluate the fitness of the regression model
In order to examine the fitness of the model (4.1) F-test would be used in this part of
the research.
We use Wald test to undertake F-test, the result of the model 4.1 is presented in
appendix 3, with the probability <1%, so the null hypothesis is rejectes, which means that at
least a coefficient is different to zero. So, the model (4.1) can explain ROE well.
The similar result outcome in case of multivariate regression model. (Appendix 6)
Thus, both model explain well for the population.
A VIF of 1 means that there is no correlation among the independent variables and
the remaining independent variables, and then the variance of coefficients is not inflated at
all. The general rule of thumb is that VIFs exceeding 4 implies further investigation, while
VIFs exceeding 10 means that there exists serious multicollinearity in the estimation, and
the model needs to be corrected.
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The result of VIF test for the model 4.1 as following
Table 4.7: Results of VIF test
Coefficient Uncentered Centered
Variable Variance VIF VIF
C 0.000729 23.02029 NA
MGR 0.000244 3.854226 1.927113
TOTAL_ASSET 9.27E-20 44.81087 6.937204
GROWTH 6.32E-05 1.958034 1.097571
LVR 2.17E-05 86.81447 6.349570
Looking at Centered VIF, we can see that all the value of Centered VIF < 10. Thus,
the multicollinearity in the model is not serious, and acceptable. Thus, we don’t have to
justify the model for resolving the problem of multicolinearity.
Checking the autocorrelation of residuals
To check the autocorrelation, the LM test is used, with the amount of lag is 2.
The resulst as following:
Table 4.8. The result of LM test
Breusch-Godfrey Serial Correlation LM Test:
F-statistic 1.078608 Prob. F(2,17) 0.3622
Obs*R-squared 2.702543 Prob. Chi-Square(2) 0.2589
As stated in the Chapter 3, The value of Prob-Chi-square (2) equal is the p-value of
Obs*R-squared is the result of this test, which equals to 0.2589 > 5%. Therefore, we accept
the null-hypothesis, that there is no auto-correlation of residuals in the model.
6. Recommendations and suggestions.
This study attempts to look into and make a comparative analysis of the effects of
M&As in the Vietnamese banking system. It focuses on commercial banks taking part in
M&A from 2010-2015. Though the period is short, but the result can be noticeable. The
univariate analysis exposed profitability after M&A for commercial banks with the t-test
showing significant difference in profitability before and after merger. The indication from
panel methodology shows that that M&A has negative impact on the profitability of banks.
This research helps to evaluate the impact of M&A on banks through the first period of
restructuring reform of Vietnamese banking system. Overall, it can be inferred from this
research, that M&A does not always enhance the profitability of banks. However, it would
be mistaken to propose that M&A activities always has negative impacts on banks.
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Recommendation for further research
This research has some limitations of small data scale. Therefore, there are some
suggestion for further research as following. This research can be undertaken with the larger
amount of cases in the future, and at the longer time span. With the larger scale of time and
expense, data should be collected more fully. Besides, the analysed of financial performance
should be more comprehensive in terms of profitability, liquidity, solvency, quick ratio,
current ratios and some other specialised ratios of banking industry. The similar research is
also done with firms in other industry such as Retail Industry, which has been starting to be
well-developed in Vietnam.
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