The results of analysis and ranking of technical efficiency by the method of data

envelopment analysis (DEA) are presented in detail in Appendix 1, the study finds

that the performance of Vietnamese commercial banks in the sample has disadvantage

as below:

Firstly, the limitation in the performance of Vietnamese commercial banks is that the

asset quality of banks tends to decrease, which is reflected in the increase in provision

ratios over total outstanding loans in the 2007-2017 period.

Secondly, the proportion of income from service activities is too low compared to the

proportion of income from credit activities, which reduces the efficiency of banks'

operations. The average of non-credit activities is only one-tenth of the average

revenue from credit activities.

Third, the size of commercial banks in the sample has an average growth of over 15%.

However, as of the end of 2017, the average total assets of commercial banks was

only approximately 267,829,499 million VND, making Vietnamese commercial banks

not take advantage of the scale that banks have.

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hoice of many studies on
measuring effectiveness. There are also many approaches to estimating, measuring
and interpreting banking efficiency. For example, there are two measurable
approaches to access to structure approach and nonstructural approach Hughes &
Mester (2008).
1.2.2.1 The nonstructural approach
Accordingly, the nonstructural approach to measure banking efficiency is a traditional
and popular way of being used. How to measure through a series of financial
indicators such as: ROE (return on equity), ROA (return on assets), ROS (return on
sale), C/I (costs ratio) However, this approach has two disadvantages: one is that
the market value of the asset, the degree of risk of two, is only appropriate when the
bank uses a single input or produces only one output. Follow Wozniewska (2015 2015
), Hughes and Mester Hughes & Mester (2008 )measuring bank efficiency by the
index may not be 4 primary metric groups:
- One is, the metric group reflects profitability such as ROE, ROS.
- Two is, the indicator group reflects the structure of the balance sheet as the ratio of
customers to total assets (DTA), credit balance of credit (LTA).
- Three is, the indicator group reflects the quality of assets of banks such as bad debts
(NPLs), total debt risk allowance ratio.
- Four is, the metric group reflects market value and the risk of assets such as Tobin' s
q, Sharpe index, the Capital Adequacy Factor CAR
1.2. 2. 2 Approaches
According to Hughles and Mester Hughes & Mester (2008) the structural approach is
usually based on the economic cost of the cost minimization or the maximum profit
(profit maximization), which is shown through the cost of the cost or the profit
function, or may be called the production function.
From here, the research on banking efficiency is increasingly diversified and forms a
variety of banking evaluation methods and the relationship between banking
efficiency and other factors affecting the bank (such as economic growth, equity
structure, etc.). Most of the following studies use the structure approach with the main
methods to measure bank efficiency, as follows:
One is, the parameter approach (parametric) with three main methods: (i) a random
method (SFA)); (ii) thick frontier approach (TFA); (iii) and Distribution Free
Approach analysis.
Two is, the non - parametric approach (non parametric) with two main methods: (i)
method for analyzing data (DEA), (ii) and method of free - factor treatment of Hull
(FDH)
CONCLUSION OF CHAPTER 1
CHAPTER 2: ASSESSMENT OF RESEARCH WORKS ON BANKING
EFFICIENCY, FACTORS AFFECTING BANKING OPERATIONS AND
RELATIONSHIPS BETWEEN LIQUIDITY AND BANKING OPERATIONS
2. 1 FUNDAMENTAL THEORY
2. 1. 1 Theory of involved parties (Stakeholders Theory)
The theory of stakeholders determines that the company is established and operates
for the benefit of all stakeholders, so when the decision of the board of management
and the operator of the company must consider the benefits of all concerned
stakeholders, such as traditional views. It does this by ensuring that the benefits of
stakeholders are interested. Therefore, the bank needs to be careful in the state of
liquidity regulation, avoiding the profit in order to increase the efficiency of the
operation that can protect the interests of the involved parties.
H1: The liquidity position is positive to performance in the commercial banks
2.1.2. Dynamic liquidity theory
Almeida and associates. (2002) the proposed state of liquidity is based on the
assumption that the choices related to liquidity will depend on the access to capital
resources and importance of the use of resources in the operations of the banks.
Expenses incurred in the absence of a higher liquidity shortage for banks with less
efficient operations. Therefore, there will be a positive relationship between banking
performance and liquidity position.
H2: Active effect on liquidity position at commercial banks
2. 2 RESEARCH STUDIES ON BANKING PERFORMANCE
2. 2. 1 Studies on banking performance in the world commercial banks
Berg et al. (1993 ) the study of the banking efficiency in Norway, Sweden and Finland
used the data method, both ways to calculate the effectiveness of each territory and
compare the three countries. The data from the study of 503 Finnish banks, 150
Norwegian banks and 126 Swedish banks. The author found that Swedish banks had
52 – 63% more effective than Finland and 40 – more effective than the Norwegian
bank. At the same time, Sweden' s largest banks were the most effective units in the
aggregates, so the group concluded that the Swedish bank was in the best position to
expand the bank of Nordic banking.
Fecher & Pestieau (1993) )use the SFA parameter method to assess technical
efficiency for 11 financial institutions in OECD (Organization for Economic
Cooperation and Development). They use total value added tax such as criteria for
evaluating the output of each country' s financial services, and the employment in the
financial sector and capital is the two inputs. Over there, they found the most effective
financial services, and Denmark was the least effective.
Most of the research on banking efficiency uses the structural approach (dimensions
and dimensions) with the main methods for measuring such as random boundary
approach (SFA) ; Thick Frontier Approach (TFA) ; Distribution Free Approach
(DFA); data analysis approach (DEA); and method of free - factor treatment of Hull
(FDH)
2. 2. 2 Research studies on banking efficiency in Vietnam .
Huong (2002), the need to improve the efficiency of the bank' s business operations
through investment activities to raise the competitiveness of commercial banks in the
context of international economic integration. Population (2004) has developed an
efficient evaluation system of commercial banks through statistical descriptions. Hung
(2008) the study conducted the performance of 32 Vietnamese commercial banks in
the period 2001 – 2005 through qualitative and quantitative methods. H. T. Vu &
Turnell (2010) measuring cost efficiency (cost) by random boundary approach (SFA)
in the Bayesian approach of the Vietnamese commercial bank.
Research towards a reasonable estimate in estimating marginal costs and using
Bayesian. Research results indicate that the effectiveness of the cost of Vietnamese
commercial banks is very high, 87%. There is a small and insignificant difference in
cost effectiveness between different banks of banks by ownership. However, during
the period of research, the banking sector has a slight decline in cost. This is explained
by the increase in the cost of managing diversified activities, extending the branch
network and upgrading the banking platform.
Dang - Thanh (2012 )the study used the analysis of DEA data analysis to analyze the
performance of the Vietnamese banking system in 1990 – 2010. H. Vu & Nam (2013)
conducting research on the factors affecting the efficiency of the bank of Vietnam in
2000 – 2006. Ngoc Nguyen & Stewart (2013) examined the level of concentration and
efficiency of the Vietnamese banking system according to the structure structure
(structural) – this is the name of the parameter and the parameter.The study used data
of a sample of 48 Vietnamese commercial banks during 1999 – 2009. Empirical
results show that the Vietnamese banking system is less concentrated, and the large
commercial bank dominates the banking system. Minh et al. (2013 )the study of 32
commercial banks in Vietnam from 2001 – 2005 to identify factors affecting the
banking efficiency. Morning (2015) )conducting the study of 48 Vietnamese
commercial banks during 1992 – 2013 on banking efficiency and relationship with
economic growth through three methods: financial index analysis; analysis of
parameters with SFA random approach; method of non - parametric analysis of data
(DEA)
Through empirical evaluation of banking works. The author found most of the
research on banking efficiency using two methods of DEA data and SFA. There are
studies like resti (1997), bauer et al ,. (1998), Pelosi (2008), Hung (2008), Vuet al ,.
(2010), Ngoc Nguyenet al. (2013) use both methods to measure efficiency in a
country. As a result of the efficiency of banking in a country, dea data method is used
increasingly common, especially in 2008, such as liang et al ,. (2008), staubet al ,.
(2010),et al ,. (2010), yuet al ,. (2013), Replová (2014), Zimková (2014) At the
same time, most of the research uses the DEA model, which allocates such as CCR,
BCC, SBM, profit efficiency.
2. 2 EVALUATION OF RESEARCH WORKS RELATED TO THE EFFECT
OF BANKING OPERATIONS
Hoang (2016) is based on the model of the model Williams (2012)research on factors
influencing the performance of the Vietnamese commercial bank system of
commercial banks - 2011 according to the efficiency measurement method (SFA), and
the regression method of regression analysis to analyze the impact factors of the
banks. Results show that the effect is affected by 02 main groups: subjective factors
(market share, liquidity, foreign investor holdings and bank size and objective factors
(gross domestic and inflation). In which the positive factors are the proportion of
foreign countries, the size and market share of the bank.
Sufian (2009) analysis of factors influencing performance of Malaysian commercial
banks in 1995 – 1999 around the crisis of East Asia in 1997. Research using the DEA
analysis method to measure performance efficiency and regression analysis to
evaluate factors affecting performance of Malaysian commercial banks. Variable the
dependence of the model is the performance of the commercial bank by the DEA
independence includes: (i) the size of the bank measured by natural logarithms of the
total deposit, (ii) ratio of credit balance on total assets, (iii) bad on total assets, (iv)
total income on total assets, (v) total expenses in addition to the interest on total
assets, (vi) ratio of equity on total assets.
Follow Williams (2012) use SFA method to analyze factors affecting the efficiency of
commercial banks, including the power market (lerner index). ' ownership' and' listed
dummy' are included as a false role: ownership receives the value' 1' when the bank
has a foreign investor' s holding rate and the value' 0' when the investor' s capital
contribution is listed as' 1' and non - listed banks receive the value' 0'. Bringing
counterfeit variables into the model to help authors in consideration of positive effects
or negative negative effects on the performance of banking systems.
Ayadi (2013) analyses factors affecting the performance of commercial banks in
Tunisia during 1996 – 2010. Study the application of non - parametric analysis to
measure the performance of commercial banks in Tunisia. The model used for the use
of the cost - effective variable by DEA is dependent on the variable and the
independent variables are the market' s concentration index (hhi), rate of each bank
compared with the system, credit balance of credit on the total assets, the ratio of
equity on total assets, the size of the measuring bank in the decimal logarithm, and
Hausman, shall be used by using the regression method to test the data in the fixed
effects, Ayadi (2013) method uses the regression method, according to the fixed
effects model and a random effect then using Hausman to test.
Alrafadi et al. (2014) measuring performance acts as factors affecting the performance
of banking systems in Libya during 2004 – through the data set of 17 Libyan
commercial banks. The study applied the DEA analysis method to measure the
efficiency of resource use commercial bank and regression Tobit to analyze factors
affecting performance of the performance Libyan commercial bank. The research
model uses the same technique as the DEA' s dependence and independence
including: customer deposits / total assets, owner' s equity on total assets, bank size of
the total of the total property, the state of primary liquidity commercial bank .
2.3 EVALUATION OF RESEARCH ON THE RELATIONSHIP BETWEEN
LIQUIDITY STATE AND BANKING EFFICIENCY.
Some study of liquidity position and performance has been performed by scholars
with various aspects. Study of Nkobe (2013 )consider the relationship of the liquidity
state, capital safety and performance of commercial banks in Kenya. Study of Sufian
et al. (2012 )to examine the relationship of the operation and the factors of the
Malaysian banking sector. Research results show that liquidity states have a positive
relationship with the bank' s performance. This is consistent with the study of Dang
(2011), who discovered the state of liquidity in the performance of the bank' s
performance. But it does not fit Ongore & Kusa (2013) when their findings indicate
that the relationship between liquidity and banking operations in Kenya is negligible.
Bordeleau, Crawford and Graham (2009) reviewed the impact of liquidity position to
the performance of 55 American banks and 10 Canadian banks during 1997 to 2009.
The study used quantitative measures to assess the impact of liquidity on bank profits.
Results from research show that the non - linear relationship, which is effective in
improving the bank' s liquidity banks, however, there is a more dominant point than
the bank performing effectively to the liquidity state of., bank
Eljelly (2004) said that organizations that have high liquidity accounts for most
investments in short - term assets, have lower profits than long - term assets. As a
result, the high liquidity is expected to work better but the low yield and vice versa.
Maintaining liquidity is indicated that money is limited in mobile assets so it is not
available for investment purposes to yield higher returns, but it is necessary to meet
the capital requirements when it is necessary to help the performance of the banks
better.
2. 4 EVALUATIONS FROM PREVIOUS RESEARCH PROJECTS
For banking performance:
Research works measure the efficiency of banking operations using 2 methods of data
(DEA) and randomness (SFA). Some studies use both methods to measure banking
performance as Pelosi (2008 ), Resti (1997 ; To (2013) )
For the study of factors affecting the performance of the banking operations,
researchers applied different regression methods, including the smallest squares
(OLS), regression, for the proposed economic model of the proposed economy. The
models are built to assess the movements of the factors in the banking operations in
which the explanatory state is the liquidity state Alrafadi et al. (2014 ; Nkobe (2013 ;
Sufian et al. (2012 ).The results of the study often show positive impact of liquidity
position to banking operations during the study.
For the study of the relationship between liquidity state and banking operations Nkobe
(2013), Bordeleau & Graham ; Eljelly (2004) towards the analysis of the relationship
between liquidity states and performance effectiveness in a multivariate regression
model. These studies often use linear analysis techniques through the D-GMM method
for the model data model, Granger analysis, Granger Karmar analysis, Tobit
censorship regression; minimum squares regression.
From theoretical research and experimentation on liquidity position and performance
of commercial banks. With the study outside the country, the factors affecting
liquidity factors, factors affecting liquidity in this country must not be repeated in
other countries. For domestic studies, it is only stopped to identify factors affecting
liquidity, operating efficiency without expanding the determination of the relationship
between liquidity and banking performance. Studies on banking efficiency in Vietnam
are quite a lot of achievement (2008); To (2013) )in both parameters and dimensions.
There are also studies that analyze factors affecting banking efficiency, analyzing
factors affecting liquidity position such as Hong (2012) ; (2013) but lack of research
on the relationship assessment between liquidity and banking efficiency. With the
author' s research knowledge evaluation and synthesis, currently no research has been
conducted in determining factors affecting the performance of the state - of - the - art
operations, as well as the assessment of the relationship between the liquidity state and
the effective performance of the state - of - the - art state, in 2007, in 2017 – 2017. In
short, when studying the " liquidity and operational position " topics Vietnamese
commercial bank will seek (i) empirical evidence for the effect of liquidity position to
the efficiency of the banking operation (ii), empirical evidence for linear relations
between liquidity states and operational efficiency commercial bank Vietnam period
2007 – 2017. This is the gap that studies solve.
CONCLUSION OF CHAPTER 2
CHAPTER 3. RESEARCH MODELS AND METHODS OF RESEARCH
RELATIONSHIP BETWEEN LIQUIDITY STATE AND BANKING
OPERATION
3.1 MODEL RESEARCH MODEL AND METHODS OF MEASURING BANKING
ACTIVITIES
3.1.1. Model background
A cost function is represented as follows Ilieva (2003 2003):
(1.1)
In which:
- TC i is the sum of total bank expenses
- And y i , p i is the vector that represents the output and input.
is error number.
Ilieva (2003) assuming that different evaluation techniques and different assumptions
for the distribution of errors are results in different models.
The optional profit function (alternative profit function) allows the bank to have large
rights in the output decision so the function is determined by the input price and
output output, as follows:
= 1n, (1.2)
3. 1. 2. Model of measuring data efficiency
If the assumption is that one DMU uses the input element x to produce the output n
elements with the method of coordinating certain inputs and outputs in two different
weights, such as v and u (u and v are the set of input variables, the DMU, which is the
following, is calculated as the following:
i = 1m; j = 1n (2.1)
Applying the formula above to compute the efficiency of each DMU and on the
theory, each DMU is different about x and y, and u, v, m, n is the same. If the price is
not determined, it is possible to assume that a variable in x i or a turn - out i will be
assigned to a v i or u i based on the importance of the head input or that output to
DMU. However, each DMU will have different evaluation of the importance of each
input and output, so each DMU is very different from both u, v, x, and y. so the DEA
will intervene and solve the problem.
However, for different analysis purposes, researchers often classify the DEA models
used in the measure of banking efficiency Kumar & Gulati (2013 ): (i) Non –
allocation DEA models; (ii) Allocation DEA models.
3.1.2.1. Non- Allocation DEA models
3.1.2.2. Allocation DEA models
3. 1. 3 Specifies the model and selection of input inputs
In this study, commercial bank was considered the financial intermediaries and
provide financial services and provide payment services to the economy should be
selected with three input variables: the cost of output variables include:
earnings from interest (y1) ; revenues from interest (y2) include net income from
service activities net income from securities trading, investment and income net from
other activities. The cost of the cost is (w1) staff costs, expenditures fees for use of
fixed assets (w2) and average interest expense (w3).
With the upper approach of theses, input and output variables are selected:
- Staff cost (I1)
- Fixed assets net (I2)
- Customer deposit (I3)
- Earnings from interest (O1)
- Non - profit income (O2)
3.2/METHOD AND ANALYSIS OF FACTORS TO AFFECT THE
PERFORMANCE OF BANKS TRADE.
To determine the model and method for analyzing factors to the efficiency of
commercial banks, research conducted by the study work - related research works.
3.2.1. Specify the model and analysis of factors affecting banking efficiency
Table 3. 1 Detailed description of variables in the tobit regression model
Variables Data
Mark
expectation
Research
DEA_TE
Banking efficiency
(results from the dea) /
Sufian(2009); Alrafadi
and partners (2014)
DETA
Deposit size
(customer deposit/ total assets) +
Alrafadi and partners
(2014); Kwan (2006)
EQTA
Capital structure
(equity / total assets) +
Berger và Mester (1997)
;Sufian(2009);Alrafadi
and partners (2014)
LATA
Liquidity state
(property assets / total assets) +
Vodová (2011); Aspachs
and parters (2005);
Alrafadi and partners
(2014)
LODE
Credit density
(loan balance / deposit) +
Lee and Kim (2013)
SIZE
The logarithm of the total assets
represents the size of the bank +
Kwan (2006)
Lee and Kim (2013)
According to Tobin' s research (1958) and Coelli co - workers (1998), model
with the sample, including i bank in a year proposed:
In the meanwhile, xi and β are vectors of explanatory variables and parameters needed
finding. yi * is dependent variable blocked or cut variable and yi is effective variable
of banking activities of bank i by randomly research sample receiving value from 0 to
1; εi is the noise part.
Model (2.1) is tobit model standardnizing for cross-sectional however,So as to be
suitable to unbalanced data panel in researching and dependent variables on efficient
technique, model (2.1) is deployed to be:
= + + + + +
Hypothesis research
With research model and variables as above, hypothesis research is supposed to be:
H1: Existing relationship covariencedly between deposit scale and banking efficiency.
H2: Existing relationship covariencedly between capital structure and banking
efficiency.
H3: Existing relationship covariencedly between liquidity position and banking
efficiency.
H4: Existing relationship covariencedly between credit proportion and banking
efficiency.
H5: Existing relationship covariencedly between bank scale and banking efficiency
3.3. RESEARCHING MODEL AND RESEARCHING METHOD IN ORDER
TO ANALISING THE RELATIONSHIP BETWEEN LIQUIDITY POSITION
AND BANKING EFFICIENTCY.
Chosen variables are : liquidity position (LATA) and activity efficiency (DEA_TE).
Thematic offers researching model as below:
( )
(3.1)
( )
(3.2)
There in: n is latency number, is specific bank effect which records systematic
difference between banks, is random error which has similiar distribution and
independent, DEA_TE is work efficient, LATA is liquidity position
In order to do the above statitic, this thesis uses estimating method S – GMM two
steps for dynamic panel data models.
3.4 RESEARCHING DATA
Researching data of this thesis is taken from Thomson Reuter and Audited financial
statements (Separate financial statements) of Việt Nam commercial banks from 2007
to 2017.
The period of researching this thesis lasted from 2007 to 2017. This thesis chose the
research milestone was 10 years since Việt Nam has joined WTO and the first
intergrating branch is banking and finance thus this statement develops very fast until
2017 when banks pilot performing as Basel II standards having went to the route
bringing liquidity admistration gradually into standards and stability (Orientation of
state bank in performing Basel II route by realizing Archive 1601/NHNN-TTGSNH
on 17/3/2014 about performing capital treaty Basel II)
The total number of banks in sample research was 32 banks (however, the maximum
number of banks for several years was less, because there was merger), including
State commercial banks , joint-stock commercial bank.
CONCLUSION CHAPTER 3
CHAPTER 4: RESEARCHING RESULT
4.1 OVERVIEW OF BANK SYSTEM.
4.2 RESEARCHING RESULTOF BANK EFFICIENCY
Technical effectness as DEA of the lowest commercial bank in 2008 accounted for
80% and the highest in 2007 for 92%. Technical effect according to DEA from the
period 2007 to 2017 was 86% on average. Technical inefficiency reflected the
deviation of animistration compared to the most effective bank. The result of analising
technique according to DEA in appendix 1 showed that AGR,VCB, MBB, TPB, NAB
are banks having average highest technique effective (100%) and NAV was the bank
having the lowest highest technique effective (56%). The average technique
efficiency was maintain at quite high rate show that Việt Nam commercial banks đã
focus on increasing administration ability and using effectively their power in order to
reach the optimal technique efficiency Commercial banks in sample researc

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