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Bank income structure and risk an empirical analysis of vietnam commercial banks

MINISTRY OF EDUCATION AND TRAINING
UNIVERSITY OF ECONOMICS HOCHIMINH CITY
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TRẦN ĐÌNH KHẢI

BANK INCOME STRUCTURE AND
RISK: AN EMPIRICAL ANALYSIS OF
VIETNAM COMMERCIAL BANKS

MASTER OF BUSINESS ADMINISTRATION

HO CHI MINH CITY, 2012
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MINISTRY OF EDUCATION AND TRAINING
UNIVERSITY OF ECONOMICS HOCHIMINH CITY
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E Â1


TRẦN ĐÌNH KHẢI

BANK INCOME STRUCTURE AND
RISK: AN EMPIRICAL ANALYSIS OF
VIETNAM COMMERCIAL BANKS
MAJOR: BUSINESS ADMINISTRATION
MAJOR CODE: 60.34.05

MASTER THESIS
SUPERVISOR: Dr. VÕ XUÂN VINH

HO CHI MINH CITY, 2012

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1

ACKNOWLEDGEMENT

This thesis would not have been possible without the guidance and the help of
several individuals who in one way or another contributed and extended their
valuable assistance in the preparation and completion of this study.
First and foremost, my utmost gratitude to Dr. Vo Xuan Vinh, whose sincerity
and encouragement I will never forget. Dr. Vinh has been my inspiration as I
hurdle all the obstacles in the completion this research. Dr. Vinh has spent plenty
of time in many weeks to support me with his fully enthusiasm.
I also express my warm gratitude to all professors at Faculty of Business
Administration, University of Economics in Hochiminh City for their teaching
and sharing during my MBA course.
I have many thanks to my classmates who show their sharing and
encouragements when I do this thesis.
Last but not the least, I want to thank so much to my beloved wife who always
understands and encourages me to complete my thesis especially in the hardly
time of taking care of my newborn baby.


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ABSTRACT
This paper investigates the relationship between bank risks and product
diversification of the Vietnam banking industry. Employing a sample of Vietnam
commercial banks for the period 2008–2011, the results indicate that banks
expanding into non-interest income activities do not present higher risk than
banks that mainly supply loans. However, considering size effects and splitting
non-interest activities into both trading activities and commission and fee
activities, we show that the link with risk is mostly accurate for small banks and
essentially driven by commission and fee activities. Whereas, for both of small
and large banks, a higher share of trading activities is never associated with
higher risk.

Keywords: Bank risk; Interest income; Non-interest income; Diversification.


3

CONTENTS
ACKNOWLEDGEMENT ...................................................................................................... 1
ABSTRACT........................................................................................................................... 2
LIST OF TABLES ................................................................................................................. 5
ABBREVIATIONS................................................................................................................ 6
CHAPTER 1: INTRODUCTION ........................................................................................... 7
1.1

BACKGROUND ..................................................................................................... 7

1.2

RESEARCH PROBLEM ......................................................................................... 9

1.3

RESEARCH OBJECTIVE ....................................................................................... 9

1.4

RESEARCH METHODOLOGY AND SCOPE ......................................................10

1.5

STRUCTURE OF RESEARCH ..............................................................................10

CHAPTER 2: BASIC THEORETICAL BACKGROUND AND LITERATURE REVIEW ..11
2.1

BANK RISK ...........................................................................................................11

2.2

BANK INCOME.....................................................................................................13

2.3

DIVERSIFICATION...............................................................................................13

2.4

BANK RISK AND DIVERSIFICATION................................................................15

2.5

HYPOTHESIS DEVELOPMENT...........................................................................18

CHAPTER 3: DATA AND RESEARCH METHODS...........................................................19
3.1

MODEL ..................................................................................................................19

3.2

VARIABLES ..........................................................................................................20

3.2.1 DIVERSIFICATION VARIABLES......................................................................20
3.2.2 BANK RISK MEASURES ...................................................................................20
3.2.3 CONTROL VARIABLES.....................................................................................21
3.3

DATA.....................................................................................................................22

CHAPTER 4: RESULTS AND DISCUSSION......................................................................27
4.1

UNIVARIATE MEAN TESTS ...............................................................................27

4.1.1 BANK RISK AND INCOME STRUCTURE ........................................................27


4

4.1.2 INCOME STRUCTURE AND BANK CHARACTERISTICS.........................30
4.2

MULTIVARIATE REGRESSION ANALYSIS......................................................32

CHAPTER 5: CONCLUSION ..............................................................................................44
5.1

RESEARCH FINDINGS:........................................................................................44

5.2

RESEARCH CONTRIBUTIONS:...........................................................................45

5.3

RECOMMENDATIONS FOR FUTURE RESEARCH: ..........................................45

REFERENCES......................................................................................................................46
APPENDIX...........................................................................................................................49


5

LIST OF TABLES
Table 1: Descriptive statistics for Vietnam commercial banks, on average over
the period 2008-2011 (%)
Table 2: Descriptive statistics for small and large Vietnam commercial banks,
on average over the period 2008-2011 (%)
Table 3: Income structure and accounting indicators of risk for Vietnam
commercial banks (2008-2011)
Table 4: Income structure and bank characteristics for Vietnam commercial
banks (2008-2011)
Table 5: OLS estimations for the sample of 35 banks with M_NNII as the
independent variable.
Table 6: OLS estimations for the first cohort of 13 small banks with M_NNII as
the independent variable.
Table 7: OLS estimations for the second cohort of 22 large banks with M_NNII
as the independent variable.
Table 8: OLS estimations for the sample of 35 banks with M_COM and
M_TRAD as the independent variables.
Table 9: OLS estimations for the first cohort of 13 small banks with M_COM
and M_TRAD as the independent variables.
Table 10: OLS estimations for the second cohort of 22 large banks with
M_COM and M_TRAD as the independent variables.


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ABBREVIATIONS
NII _ Net interest income to net operating income.
NNII _ Net non interest income to net operating income.
COM _ Net commission and fee income to net operating income.
TRAD _ Net trading income to net operating income
Q75 _ Third quartile.
Q25 _ First quartile.
LOANS _ loans to total assets;
DEP _ deposits to total assets;
EQUITY_ equity to total assets;
EXPENSES _personnel expenses to total assets;
ROA_ return on average assets;
ROE_ return on average equity;
TA _ total assets
SDROA_ standard deviation of the return on average assets;
SDROE_ standard deviation of the return on average equity;
LLP_ ratio of loan loss provisions to net loans;
ADZ_ Z-score;
ADZP_ ‘‘ZP-score”;
ADZP1_ measure of bank portfolio risk;
ADZP2_ measure of leverage risk.
OLS _ Ordinary least squares
HOSE_Hochiminh Securities Exchange
HNX_Hanoi Securities Exchange
OTC_ Over The Counter


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CHAPTER 1: INTRODUCTION
1.1 BACKGROUND
Following more definitions of bank income structure in the world, bank income
structures has two main components: interest income that stems from traditional
activities such as giving loan and non-interest income that stems from
nontraditional activities such as supplying services, trading services.
In the context of financial deregulation that took place in the seventies and in the
eighties, western banking systems faced major changes in the form of increased
competition, concentration and restructuring. Banks have reacted to the new
environment by adopting a proactive strategy widening the range of products
they offer to their clients. These changes mainly implied an increasing share of
non-interest income in profits. Non-interest income stems from traditional
service charges (checking, cash management, letters of credit. . .) but also from
new sources. With the decline in interest margins induced by higher competition
banks were incited to charge higher fees on existing or new services (cash
withdrawal, bank account management, data processing. . .). As a result,
structure of bank income experienced a dramatic change in the world. In the
eighties, non-interest income represented 19% of US commercial banks’ total
income. This share had grown to 43% of total income in 2001 (Stiroh, 2004) and
increased from 10% in 1984 to 31% in 2011. In Europe, non-interest income has
increased from 26% to 41% between 1989 and 1998 (European Central Bank,
2000). In Vietnam, non-interest income represented 20% of commercial banks’


8

total income and its share had increased 9% for period of 2008-2011 (State Bank
of Vietnam, 2012).
With the adoption of the new universal banking principle, commercial banks can
compete on a wider range of market segments (investment banking, market
trading...). Numerous studies questioned the implications of this new
environment on bank risk. The issue is of importance for the safety and
soundness of the banking system and a major challenge for supervisory
authorities.
The existing literature, mostly based on US banks, either focused on portfolio
diversification effects risk return profile (Boyd et al., 1980; DeYoung & Roland,
2001; Kwan, 1998) or on incentives approaches (Boyd et al., 1998; John et al.,
1994; Puri, 1996; Rajan, 1991). Few studies were able to show that the
combination of lending and non-interest income activities allows for
diversification benefits and therefore risk reduction. Conversely, some papers
find a significant positive impact of diversification on earnings volatility
(DeYoung & Roland, 2001; Stiroh, 2004; Stiroh & Rumble, 2006). As noted by
DeYoung & Roland (2001), three main reasons may explain this increase in risk.
Firstly, income from lending activities is likely to be relatively stable over time
because switching and information costs make it costly for either borrowers or
lenders to walk away from a lending relationship. In contrast, income from noninterest income activities may suffer from larger fluctuations as it might be easier
to switch banks for this type of activities than for lending. Secondly, expanding
non-interest income activities may imply a rise in fixed costs (for example,
additional staff may be required), which increases the operational leverage of
banks. Conversely, once a lending relationship is established, the marginal cost


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induced by the supply of additional loans is limited to interest expenses. Thirdly,
because bank regulators do not require banks to hold capital against non-interest
income activities, earnings volatility may increase because of a higher degree of
financial leverage. Moreover, as mentioned by Stiroh (2004), cross-selling of
different products to a core customer does not imply diversification benefits
(more products are sold to the same customer) which may explain why interest
income growth and non-interest income growth are highly correlated in his study
1.2

RESEARCH PROBLEM

An increasing number of papers based on the US context have focus on the
effect of earning diversifications of banks on earning volatility (DeYoung &
Roland, 2001; Stiroh, 2004; Stiroh & Rumble, 2006). DeYoung and Roland
(2001) concludes that fee-based activities increase the volatility of banks revenue
in USA. Lepetit et al. (2008) find that European banks expanding into noninterest income activities present higher risk and higher insolvency risk than
banks mainly supply loans. However, no paper has tried to study the effect of the
diversification of Vietnam commercial banks’ earning on risks. This paper aims
to fill the gap of lacking the empirical analysis of commercial banks in Vietnam.
1.3

RESEARCH OBJECTIVE

The aim of this paper is to assess the risk implications of the changing structure
of the Vietnam banking industry which has shifted away from traditional
activities (deposit funded loans) towards activities generating non-interest
income. Using individual bank data from 2008 to 2011 for 35 Vietnam
commercial banks, we begin by analyzing the link between bank risk and the
degree of output diversification measured by three indicators, the income share


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of: (i) non-interest income, (ii) trading income and (iii) commission and fee
income. We hence start by comparing the risk level of banks which have
expanded into nontraditional activities with the risk level of banks which have
invested less in those activities. Our results show that higher reliance on noninterest activities is not associated with higher risk, however, higher risk is
correlated with commission and fee income for small banks with total assets
smaller than 25.500 billion VND (equivalent to 1 billion €)1. Conversely, for
banks with a larger share in trading income are not associated with both of risk
exposure and insolvency (default) risk.
1.4

RESEARCH METHODOLOGY AND SCOPE

The subject of this research is all listed and non-listed banks in Vietnam for the
period from 2008 to 2011. The sample size is 35. This paper uses quantitative
research based on Lepetit et al. (2008) model to investigate the link between
bank risk and the degree of output diversification. We use various data analysis
methods in conducting the research such as descriptive statistics, T-test,
correlation test, and OLS regression with Eviews 7 for Windows.
1.5 STRUCTURE OF RESEARCH
Section 2 reviews the basic theoretical background and prior work of previous
researches. Chapter 3 describes model for this paper, data collection and analysis
methodology. Chapter 4 contains the result and discussion of empirical tests
while Chapter 5 concludes.
1

Our criterion for distinguishing large and small banks is similar to Bank scope’s and is frequently used in the
literature to categorize banks (Carter & McNulty, 2005)


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CHAPTER 2: BASIC THEORETICAL BACKGROUND
AND LITERATURE REVIEW
Chapter 2 is to review the basic theoretical background and literature on bank
risk, bank income, diversification and shows the relationship between bank risk
and diversification.
2.1 BANK RISK
There are multiple definitions of risk. Banks face several types of risk. All the
following are examples of the various risks banks encounter:
 Borrowers may submit payments late or fail altogether to make payments.
 Depositors may demand the return of their money at a faster rate than the
bank has reserved.
 Market interest rates may change and hurt the value of a bank’s loans.
 Investments made by the bank in securities or private companies may lose
value.
 Human input errors or fraud in computer systems can lead to losses.
To monitor, manage, and measure these risks, banks are actively engaged in risk
management. In a bank, the risk management function contributes to the
management of the risks that a bank faces by continuously measuring the risk of
its current portfolio of assets and other exposures.
From a regulatory perspective, the size and risk of a bank’s assets are the most
important determinants of how much regulatory reserve capital the bank is
required to hold. A bank with high-risk assets faces the possibility that those


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assets could quickly lose value. If the market -depositors- perceives that the bank
is unstable and deposits are in peril, then nervous depositors may withdraw their
funds from the bank. If too many depositors want to withdraw their funds at the
same time, then fear that the bank will run out of money could break out. In
addition, when there is a widespread withdrawal of money from a bank, the bank
may be forced to sell its assets under pressure. To avoid this, regulators would
want a bank with high-risk assets to have more reserves available (Apostolik et
al., 2011)
There are many methods to measure bank risk; in this paper, some main
measurements are presented.
According to Lepetit et al. (2008), there are three standard measures of risk,
based on annual accounting data and determined for each bank throughout the
period: (i) the standard deviation of the return on average assets (SDROA); (ii)
the standard deviation of the return on average equity (SDROE); (iii) the ratio of
loan loss provisions to net loans (LLP). And he also computes insolvency risk
measures: (i) the‘‘Z-score” (ADZ) (Boyd & Graham, 1986) which indicates the
probability of failure of a given bank; (ii) the ‘‘ZP-score” (ADZP) as in (Goyeau
& Tarazi, 1992) and its two additive components which we call ADZP1 and
ADZP2. ADZP1 is a measure of bank portfolio risk whereas ADZP2 is a
measure of leverage risk. Whereas, ADZ = (100 + average ROE)/SDROE and
ADZP = ADZP1 + ADZP2 = average ROA/SDROA +
equities/Total assets)/ SDROA.

average (Total


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Following his study, a large number of reseaches have focused on it. Among of
them, Barry et al. (2009), Grassa (2009), Dhouibi & Mamoghli (2009) are few
well-known studies.
2.2

BANK INCOME

There are many papers researched on structure of bank income such as Davis &
Tuori (1998), European Central Bank ( 2000), Stiroh (2004),

Lepetit et

al.(2008), Orlik & Blancas (2012). With Davis and Tuori (1998), bank income
has two sources which are interest income from traditional activities and noninterest income from new activities. Interest income is the difference between the
interest which the bank has to pay for customers’ deposits and interest which the
bank earns from lending money to customers. While non-interest income is
calculated as the sum of net fees and commissions (fees and commissions
receivable less fees and commissions payable), income from securities and the
net profit (loss) on financial operations and other operating income (European
Central Bank, 2000).
In the paper of Lepetit et al. (2008), the author considers bank income with ratio
of net interest income or net non-interest income to total operating income. In
addition, non-interest income is distinguished two components: commission and
fee income and trading income. Whereas, trading income that the author
considers is total of income from securities, the net profit (loss) on financial
operations and other operating income.
2.3

DIVERSIFICATION

In the paper of Stiroh (2004), the U.S. banking industry is steadily shifting away
from traditional sources of revenue like loan making toward nontraditional


14

activities that generate fee income, service charges, trading revenue, and other
types of non-interest income. Non-interest income has always played an
important role in banking revenue. This shift toward non-interest income has
contributed to higher levels of bank revenue in recent years, but there is also a
sense that it can lower the volatility of bank profit and revenue, and reduce risk.
One potential channel is that non-interest income may be less dependent on
overall business conditions than traditional interest income, so that an increased
reliance on non-interest income reduces the cyclical variation in bank profits and
revenue. Alternatively, expanded product lines and cross-selling opportunities
associated with growing non-interest income may offer diversification benefits
for a bank’s revenue portfolio.
Kwast (1989) finds limited diversification benefits from expanded bank
securities powers from 1976 to 1985. Similarly, Kwan (1998) reports that bank
Section 20 subsidiaries typically posted more volatile accounting returns,
although not necessarily higher returns. DeYoung and Roland (2001) examine
the link between bank profitability, volatility, and different revenue shares for
472 large commercial banks from 1988 to 1995. They conclude that increased
fee-based activities (revenue from all sources except loans, investment, deposit,
and trading activities) increases the volatility of bank revenue and bank earnings.
Taken together, there is little evidence of large diversification benefits from
these papers.
One way to capture the degree of diversification of bank activities in the
literature (Stiroh, 2004) is to consider the structure of income statements that is
the shares of net interest income generated by traditional activities and noninterest income produced by nontraditional activities.


15

With Lepetit et al. (2008), he considers bank diversification as the changing
structure of the banking industry that has shifted away from traditional activities
(deposit funded loans) towards activities generating non-interest income. He
starts by analyzing the link between bank risk and the degree of output
diversification measured by three indicators, the income share of: (i) non-interest
income, (ii) trading income and (iii) commission and fee income. They split their
samples into different panels of banks based on the value of the ratio of net noninterest income to net operating income (NNII). In addition, they consider as
diversified, banks for which the value of the NNII ratio is higher than the third
quartile (Q75) and as non-diversified, banks with a NNII ratio lower than the
first quartile (Q25). For deeper insights, they compare the level of risk of banks
which are characterized by high levels of fee-based activities that is banks with a
ratio of net commission income to net operating income (COM) higher than the
third quartile Q75, with banks with the same ratio not exceeding the value of the
first quartile (COM lower than Q25). In the next step, they undertake the same
comparison based on the degree of reliance on trading activities (ratio of net
trading income to net operating income (TRAD) higher than Q75 versus TRAD
lower than Q25.
2.4

BANK RISK AND DIVERSIFICATION

There is a variety of studies that analyze diversification of income sources, more
specifically interest and non-interest income, has attracted increasing attention in
academic research. Generally, it is believed that diversification of income
sources should reduce total risk, as diversification should stabilize operating
income. For instance, Boyd et al. (1980), who simulated portfolios of banking
and non-bank subsidiaries during the seventies, find a potential for risk reduction


16

at relatively low levels of non-bank activities. The results obtained by Kwast
(1989) to determine an optimal risk-minimizing combination of banking and
nonbanking activities for the period 1976–1985 show only a slight potential for
risk reduction. Saunders & Walter (1994) perform a simulation exercise and
conclude that there are potential gains in the reduction of risk from bank
expansion into new activities. They find that property and casualty insurance is a
particularly attractive area for money center bank expansion. Gallo et al. (1996)
find over the 1987–1994 period, that combining traditional banking activities
and securities and/or insurance activities allows for some diversification benefits
increasing profitability for moderated risk levels.
Another strand of the literature reports an increase in risk when combining
traditional and non-interest income activities. According to Boyd & Graham
(1986), expansion by bank holding companies (BHCs) into nonbank activities
during the seventies tended to increase the risk of failure of banks during the less
stringent policy period. Demsetz & Strahan (1997) who study the stock returns
of BHCs between 1980 and 1993 find that although banks extended their product
mixes, no risk reduction could be observed as banks tended to move to riskier
activities and to lower their capital ratio. Kwan (1998), who investigated bank
section 20 subsidiaries during the 1990–1997 periods, underlines the increased
volatility of accounting returns despite a non-increase in bank profitability.
DeYoung & Roland (2001) examine the link between bank profitability,
volatility, and different revenue shares for 472 large commercial banks from
1988 to 1995. They conclude that increased fee-based activities (revenue from
all sources except loans, investment, deposit, and trading activities) increases the
volatility of bank revenue and bank earnings.

DeYoung & Roland (2001)


17

provide three reasons why non-interest income may increase volatility. First,
revenues from fee-based activities might be more volatile than interest income
because the customer-bank relationship is stronger in the traditional lending
business, i.e. for many of the new fee-based activities it is easier for customers to
switch to another bank. Second, expanding into fee-based services can
considerably increase fixed costs (e.g. by investments in technology and human
resources) whereas, if a lending relationship is already established, the only cost
of an additional loan are the bank’s interest expenses. Third, in contrast to the
lending business, fee-based activities require less regulatory capital, which
suggests a higher degree of financial leverage and therefore leads to a higher
earnings volatility.
A similar result is obtained by Stiroh (2004) who assesses the potential benefit of
diversification for US banks engaging in non-interest activities for the period
1984–2001. He finds that empirical evidence that reliance on non-interest
activities increases the volatility of large U.S. banks. Lepetit et al. (2008) find
that European banks expanding into non-interest income activities present higher
risk and higher insolvency risk than banks mainly supply loans.
However, no paper has tried to study the effect of the diversification of Vietnam
commercial banks’ earning on risks. Hence, to our knowledge, this is the first
study to explore the impact of the diversification of banks’ earning on risk in the
case of Vietnam. Firstly, this study considers a large set of risk and insolvency
risk measures based on accounting data at the bank individual level. Secondly, to
assess the risk implications of non-interest generating activities are split into two
components: trading activities and commission and fee activities. Third, we


18

conduct a regression analysis which enables to capture the major changes in our
period of study and we focus on risk implications both for large and small banks.
2.5 HYPOTHESIS DEVELOPMENT
The literature cited above highlights, with regards to US, EU banks, that activity
diversification does not necessarily imply lower risk, and may on the contrary
increase bank risk. As a first step, we check if similar results can also be
obtained for Vietnam banks by simply conducting univariate mean tests. We
therefore go to test some hypothesis such as:
H1: “Risk/Insolvency risk is not different for high and low degree of
diversification”.
H2: ‘‘Bank characteristics are not different for high and low degree of
diversification”.
As the last step, we do multivariate regression analysis to investigate the issue on
risk and diversification. It whether supports the hypothesis as below:
H3: “Diversification has positive effect on bank risk”.
H4: “Fee and commission income has positive effect on bank risk”
H5: “Trading income has not effect on bank risk”
H6: “Effectiveness of diversification on bank risk is not different for large and
small banks”


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CHAPTER 3: DATA AND RESEARCH METHODS
Based on the results in the literature review, this Chapter presents model and the
variables for the model. Furthermore, it also describes the data for this research.
3.1 MODEL

From the model of Lepetit et al. (2008), we employ the following model for our
analysis as following:
H

M_RISKi = α + β M_DIVi + ∑ γh M_Xhi + εi
h=1

where
- M_RISKi is the mean value, for bank i, taken for the period 2008–2011, of
each accounting based risk measure computed over period (SDROA,
SDROE, ADZ, ADZP, ADZP1, ADZP2).
- M_DIVi is the mean value, for bank i, for the period 2008-2011, of each
product diversification variable (NNII, COM and TRAD).
- M_Xhi is the mean value, for bank i, for the period 2008-2011, for a set of
control variables Xh (ROA, EQUITY, LOANS and DTA).


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3.2 VARIABLES
3.2.1 Diversification variables
Following the literature reviews, in our paper, we consider the structure of
income statements that is the shares of net interest income and non-interest
income produced. We therefore define several variables. Firstly, we consider the
ratio of net non-interest income to net operating income NNII. Net non-interest
income is defined as the difference between non-interest income and non-interest
expenses; net operating income is the sum of net interest income and net noninterest income. Secondly, for more precisely, we distinguish two components of
non-interest income: commission and fee income and trading income. We hence
define a ratio of net commission and fee income to net operating income (COM)
and a ratio of net trading income to net operating income (TRAD). Net
commission and fee income is equal to commission income minus commission
and fee expense and net trading income is equal to trading income minus trading
expense.
3.2.2 Bank risk measures
In this study, we used three standard measures of risk, based on annual
accounting data and determined for each bank throughout the period, are used in
our study: (i) the standard deviation of the return on average assets (SDROA);
(ii) the standard deviation of the return on average equity (SDROE); (iii) the
ratio of loan loss provisions to net loans (LLP).


21

We also compute insolvency risk measures: (i) the ‘‘Z-score” (ADZ)2 which
indicates the probability of failure of a given bank; (ii) the ‘‘ZP-score” (ADZP)3
as in Goyeau and Tarazi (1992) and its two additive components which we call
ADZP1 and ADZP2. ADZP1 is a measure of bank portfolio risk whereas
ADZP2 is a measure of leverage risk.
3.2.3 Control variables
We chose large set of control variables which was initially considered to account
for size differences (total assets (TA)), the annual growth rate of total assets
(DTA) , profitability differences (ROA and ROE), business differences (deposits
to total assets (DEP)), loans to total assets (LOANS), personnel expenses to total
assets (EXPENSES) and leverage differences (EQUITY).
Because of frequent collinearity among the variables both in the large sample
and the smaller sample of banks (see Appendix A.2), control variables are
restricted to ROA, EQUITY, LOANS and DTA. In Appendix A.2, we used
Spearman correlation test to consider degree of correlation of dependent and
independent variables with the sample of all banks, the first cohort of small
banks and the second cohort of large banks. With high correlation coefficent
(over from 0.7) of independent variables, we left these one out of the model. In
Appendix A.2, we saw that TA has high correlation with ROE, DTA, EQUITY;
ROE has high correlation with TA, DTA; EXPENSES has high correlation with

2

ADZ = (100+ average ROE)/ SDROE where ROE and SDROE are expressed in percentage. Higher values of
Z-score imply lower probability of failure (see Boyd and Graham, 1986 for more details).
3
ADZP = ADZP1 + ADZP = (average ROA/ SDROA)+ (average (total equities/total assets)/SDROA).


22

LOANS; DEP has high correlation with EQUITY; NII has high correlation with
NNII.
3.3

DATA

We use a sample consisting of an unbalanced panel of annual report data from
2008 to 2011 for a set of 35 commercial banks in Vietnam (see Appendix A.1).
We collect data for our research from the annual reports of commercial banks in
Vietnam. Since the number of banks has been increasing every year, we select
banks existing for at least three years (since 2009). Our sample is constituted by
of 35 banks observed during the period 2008-2011, whereas, 9 banks listed in
Vietnam stock market (HOSE, HNX), 26 banks unlisted but in OTC market.
Source of annual reports of commercial bank is on website: www.sanotc.com,
www.cafef.vn. Most of financial statements of banks in our research are audited
by famous auditing companies in the world such as: PricewaterhouseCoopers,
KPMG, Ernst &Young. Therefore, our data in this paper is reliable at a certain
level.


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Table 1
Descriptive statistics for Vietnam commercial banks, on average over the period 2008-2011 (%)
LOANS DEP
EQUITY LLP EXPENSES ROA ROE
NII
NNII COM

TRAD

TA

Sample : non-listed and listed banks (35 banks)
Mean
Std
Min
Max

48.82%
11.67%
22.05%
72.54%

51.17%
8.50%
30.69%
66.34%

13.23%
6.89%
4.76%
31.74%

0.55%
0.35%
0.15%
1.74%

0.72%
0.19%
0.37%
1.08%

1.23%
0.63%
0.14%
3.19%

11.17%
6.16%
3.23%
26.36%

78.56%
12.55%
47.04%
101.17%

21.44%
12.55%
-1.17%
52.96%

8.48%
6.80%
-0.01%
28.25%

12.95%
12.42%
-11.86%
52.12%

66,742,048
86,033,076
7,975,497
328,743,747

0.83%
0.55%
0.15%
1.74%

0.73%
0.21%
0.45%
1.08%

1.20%
0.46%
0.37%
1.88%

14.71%
7.76%
3.78%
26.36%

73.85%
5.52%
65.41%
83.91%

26.15%
5.52%
16.09%
34.59%

10.97%
4.95%
5.37%
20.98%

15.18%
5.60%
6.61%
24.76%

159,249,443
125,951,925
12,593,914
328,743,747

0.46%
0.20%
0.17%
0.85%

0.,72%
0.18%
0.37%
1.02%

1.24%
0.68%
0.14%
3.19%

9.94%
5.12%
3.23%
23.33%

80.19%
13.91%
47.04%
101.17%

19.81%
13.91%
-1.17%
52.96%

7.63%
7.21%
-0.01%
28.25%

First cohort: listed banks (9 banks)
Mean
Std
Min
Max

51.82%
10.09%
37.33%
69.19%

54.77%
7.88%
43.20%
66.34%

9.88%
4.33%
5.67%
16.61%

Second Cohort: non-listed banks (26 banks)
Mean
Std
Min
Max

47.78%
12.18%
22.05%
72.54%

49.93%
8.50%
30.69%
63.27%

14.39%
7.29%
4.76%
31.74%

12.18%
14.05%
-11.86%
52.12%

34,720,257
29,029,316
7,975,497
120,625,711

Notes:
1) all variables are expressed in percentage except TA.
2) Variable definitions: LOANS = loans/total assets; DEP = deposits/total assets; EQUITY = equity/total assets; LLP = loan loss provisions/net loans;
EXPENSES = personnel expenses/total assets; ROA = return on average assets; ROE = return on average equity; NII = net interest income/net operating
income; COM = net commission income/net operating income; TRAD = net trading income/net operating income; NNII = net non-interest income/net
operating income; TA = total assets (million VND).


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