Financial Performance of the Malaysian Banking
Industry: Domestic vs Foreign Banks
Mamadou Lamarana Guisse
Submitted to the
Institute of Graduate Studies and Research
in partial fulfillment of the requirements for the Degree of
Master of science
in
Banking and Finance
Eastern Mediterranean University
June 2012
Gazimağusa, North Cyprus
Approval of the Institute of Graduate Studies and Research
Prof. Dr. Elvan Yılmaz
Director
I certify that this thesis satisfies the requirements as a thesis for the degree of Master of
Science in Banking and Finance.
Assoc. Prof. Dr. Salih Katırcıoğlu
Chair, Department of Banking and Finance
We certify that we have read this thesis and that in our opinion it is fully adequate in
scope and quality as a thesis for the degree of Master of Science in Banking and
Finance.
Assoc. Prof. Dr. Nesrin Özataç
Supervisor
Examining Committee
1. Assoc. Prof. Dr. Mustafa Besim
2. Assoc. Prof. Dr. Nesrin Özataç
3. Assoc. Prof. Dr. Salih Katırcıoğlu
iii
ABSTRACT
The aim of this study is to examine the performance of the Malaysian’s local banks and
foreign banks, and compare their profitability in the financial sector. Profitability of
commercial banks can be influenced by several factors, such as liquidity, credit, capital,
operating expenses, and the size of the banks. Measuring the profitability in term of
Return on Asset (ROA) and Return on Equity (ROE) for a panel of local and foreign
banks can give a general idea about the effects of these factors to banking system. Some
previous studies have been carried out in the same field such as the work of Sufian
(2009) that investigates the factors influencing the profitability of the Malaysian banking
industry.
For this analysis, a panel regression methodology will be applied to investigate the
performance of these commercial banks within Malaysian’s banking system empirically.
Financial ratios are collected for a total of 8 (eight) local banks and 8 (eight) foreign
banks, covering a period between 2005 and 2011. In addition, a comparative study will
be carried out to show possible difference between the two categories of bank ownership
from the perspective of performance and profitability.
Keywords: Profitability, Asset-Liability management, Banking, Malaysia Bank
Ownership.
iv
ÖZ
Bu çalışma, Malezya yerel ve yabancı bankaların finansal performanslarının
karşılaştırılmasını amaçlamaktadır. Ticari bankaların karlılıkları bazı nedenlerden
etkilenebilmektedir.
Bu faktöreleri likidite, kredi, işletim harcamaları, banka
b��y��kl��kleri diye sıralayabiliriz. Aktif getiri (ROA) ve sermaye ��zerinden getiri(ROE),
Baz rasyolarını alarak bankacılık sistemine bu faktörlerin ne yönde etki ettiği
araştırlımıştır.. Daha önce yaplılmış çalışmlarda örneğin Sufian(2009) banka
karlılıkların etkileyen faktörler ��zerine çalışmalar yapmıştır.
Analizde panel regresyon metodu kullanılarak ticari bankalrın ampirik olarak
performansları incelenmiştir. Çalışmada 8 yerel 8 de yabancı banka kullanılmış bankalar
sahiplik yapısı dikkate alınarak gloabal kriz ve performansları yön��nde bulgulara
ulaşılmıştır.
Anahtar kelimeler: Karlılık, Aktif-pasif yönetimi, bankacılık, Malezya Bankacılık
sahiplik yapısı
v
DEDICATION
To
My Family and the Guinean Community in TRNC
vi
ACKNOWLEDGMENTS
First of all, I would like to thank God for assisting me in accomplishing this thesis,
without him this study could not have seen the light of day. I also would like to thank
Assoc. Prof. Dr. Nesrin Ozatac for her continuous support and guidance in the
preparation of this study. Without her priceless supervision, all my efforts could have
been limited.
Besides that I extend my heartfelt thank to Assoc. Prof. Dr. Salih Katircioglu, Assoc.
Prof. Dr. Mustafa Besim, Nigar Taspinar and to all other instructors in banking and
finance department and my friends for their great support and help during my stay in
Eastern Mediterranean University.
I owe quite a lot to my family in particular to my Dad Thierno Mamadou Cire, my mom
Aissata Diallo, my uncle Thierno Nabika Diallo and my brother EL. Mamadou Aliou
Guisse who allowed me to travel all the way from Guinea to Cyprus and supported me
all throughout my studies. I would like to dedicate this study to them as an indication of
their significance in this study as well as in my life.
.
vii
TABLE OF CONTENTS
ABSTRACT ......................................................................................................................iii
ÖZ ..................................................................................................................................... iv
DEDICATION………………………………………………………………………...…v
ACKNOWLEDGMENTS ................................................................................................ vi
LIST OF TABLES……………………………………………………………………....ix
LIST OF ABBREVIATIONS…………………………………………………………....x
1 INTRODUCTION .......................................................................................................... 1
1.1 Historical Background ............................................................................................ 1
1.2 Aim of Study ............................................................................................................ 2
1.3 Research to find out .................................................................................................. 3
1.4 Structure of the Thesis ........................................................................................... 3
2 OVERVIEW OF MALAYSIAN BANKING SECTOR ................................................ 4
2.1 The 2008 Global crises ............................................................................................. 5
3 LITERATURE REVIEW ............................................................................................. 10
4 DATA AND METHODOLOGY .................................................................................. 15
4.1 Data ........................................................................................................................ 15
4.2 The Variables ......................................................................................................... 16
4.2.1 Dependent Variables ........................................................................................ 17
4.2.2 Independent Variables ..................................................................................... 18
4.3 Methodology .......................................................................................................... 20
4.3.1 Panel Unit root Test: ........................................................................................ 20
viii
4.3.2 Proposed Model: .............................................................................................. 20
5 EMPIRICAL ANALYSIS AND RESULTS ................................................................ 22
5.1 Panel Unit Root Test Results: ................................................................................ 22
5.3.1 Regression Analysis Result of All Banks ........................................................ 26
5.3.2 Regression Analysis Result of Domestic Banks: ............................................ 28
5.2.3 Regression Analysis Result of Foreign Banks: ............................................... 28
5.4 Comparison between Domestic and Foreign Banks............................................... 29
CONCLUSION AND SUGGESTION ............................................................................ 32
REFERENCES ................................................................................................................ 34
APPENDICES ................................................................................................................. 38
ix
LIST OF TABLES
Table 2.1: List of licensed Malaysian commercial Banks…………….….….…….....7
Table 2.2: List of licensed Malaysian Islamic Banks……………………..…….……9
Table 4.1: Selected commercial banks and Ownership Structure…………………..16
Table 4.2: The variables measures and their notation…………………….…...……17
Table 5.1: Correlation matrix of variables: All Banks……...………………..……..24
Table 5.2: Correlation matrix of variables: Domestic Banks……………….………25
Table 5.3: Correlation matrix of variables: Foreign Banks………………….……...26
x
LIST OF ABBREVIATIONS
BNM……………………………………….………..………….…Bank Negara Malaysia
ROA………………………………………………….……………..……Return on Asset
ROE………………………………………………….….………………Return on Equity
CAR…………………………………………………..…………..…….Capital Adequacy
ASQ……………………………………………….…………………..….…Asset Quality
LQR……………………………………………………………....………..Liquidity Ratio
EAR……………………………………………………………………………....Earnings
LSIZE……………………………………………….…...Natural Logarithm of total asset
E-VIEWS……………………………………………………………...Econometric views
LLC………………………………………………………………..…Levin, Lin and Chu
OLS………………………………………………………………..Ordinary Least Square
VAR Model………………………………..…………….…Vector Autaregression Model
1
Chapter 1
1 INTRODUCTION
1.1 Historical Background
The financial institution’s history is relatively close to that of the money, but trading
started probably before the money has been invented. Therefore, the first form of
transaction consisted of deposits of grain, goods and precious metal like gold that had to
be kept in the Temples and other places that were considered as the ideal places for
storing good items. The role played by financial institution is so important than that we
cannot think about life without banks. The innovation and modernization of the banking
sectors nowadays have made the banking system more secure and more comfortable for
their customers, so that they can even do transactions through the internet and even their
mobile phones. Commercial Banks as financial intermediaries accept deposits from
savers and give loans to borrowers for investment and the spread between the interest
rate paid to depositors and that charged to borrower is the profit or the interest income to
the banks. They also provide some trading facilities like letter of credit, shipping
guarantee, Banker’s acceptance, and so on. Faezah (2007) mentioned in his study that
commercial banks have started being under the Central Bank of Malaysia, Bank Negara
Malaysia ( BNM) control since 1959, two years after the Malaysian independence. With
reference to the BNM (2012), Malaysian licensed financial institution has 25
commercial banks (constituted by 9 domestics banks and 16 foreign banks), 17 Islamic
2
banks (constituted by 11 domestic banks and 6 foreign owned-banks), 5 International
Islamic banks (all foreign owned), 15 investment banks (all domestic owned-banks), and
2 other financial institutions (also domestically owned-banks). According to the IMF
(2004) report, over 90 percent of share of Malaysian banking in 1957 were held by
foreign banks, but due to the some government policies against them, these percentages
declined to 16.7 by 1997.
In the last 3 decades, Malaysian banking sector has faced several financial crisis such as
that of the period 1985-1986 in which some financial institutions went to bankruptcy
because of default on loans, and 1987-1989 which are related to a high level of
nonperforming loans of financial companies and small banks, in contrast, 1997-1998,
and 2008 are the effect of the Asian crisis and Global financial crisis respectively.
The Global financial crisis 2008 did not have its origin in Asia, but started in the United
State, due to the lack of control of its financial downturn and transmitted to all financial
institutions, Khoon and Mah-Hui (2010) studied the impact of the global financial crisis
on the Malaysian economy which stated that the negative effect started in the last 3
months of 2008.
1.2 Aim of Study
A similar study was done by Sufian (2009) that examined the factors influencing bank
profitability in developing Economy in the case of Malaysia, for the period 2000-2004
including 23 commercial banks (constituted by 10 domestically owned and 13 foreign
owned banks).
3
The present study aims to investigate the factors influencing bank profitability in
Malaysia for the period 2005-2011 covering 16 major commercial banks (8 locally
owned and 8 foreign owned). In order to examine these selected commercial banks
profitability, we will use Return on Asset (ROA) and Return on Equity (ROE) which are
considered as dependent variables. In the other hand, Capital Adequacy, Asset Quality,
Management Efficiency, Liquidity and the Bank Size (Total Asset) are the independent
variables.
1.3 Research to find out
The present study examines the profitability of 16 major commercial banks in Malaysia
and the factors influencing their performance for the period 2005-2011. However, in
order to figure out that, a number of questions have to be answered. Do local banks
perform better than foreign banks in the above period or is it the inverse? During a
period of financial crisis, which of the two kinds of owner banks is able to better deal
with the crisis effect and perform more? If there is any difference between local and
foreign banks performance, what is the reason? The response to these questions will be
useful to Malaysian banking management, as well as to policies makers, in order to
improve the financial institution performance.
1.4 Structure of the Thesis
From now till the end, this thesis will have the following structure: section 2 gives an
overview of the Malaysian banking sector, section 3 focuses on the literature review
related to previous studies, section 4 presents the selected data and methodology, section
5 explains the finding results, and at the end, section 6 will be the conclusion and
suggestion for further study.
4
Chapter 2
OVERVIEW OF MALAYSIAN BANKING SECTOR
Malaysian financial system has started since before its independence in 1957, however,
in those periods, foreign banks were the only financial institution operating in the
country. In contrast, domestic banks
1
waited until 1959 to start with the implementation
of the Central Bank of Malaysia (Matthews and Ismail 2006). According to the BNM
2
,
Malaysian financial institution is constituted by 25 commercial banks (9 domestically
owned and 16 foreign owned banks), 16 Islamic banks, 5 international Islamic banks, 15
investment banks and 2 other financial institutions. Sufian (2009) pointed out in his
study that, 10 domestic and 13 foreign banks constituted the commercial banks in 2004.
Said and Tumin (2011) reported in their study that by 2008, Malaysian commercial
banks were constituted by 9 local and13 foreign banks. The decline of the number of
domestic banks is a result of banks merger in which they expect an improvement in their
performance. For instance, the last bank merger is that between EON Bank and Hong
Leong Bank on May 2011 (Ong, Teo, and Teh November 2011). Malaysian Financial
institutions have experienced several crises since 1959, such as 1985-1986 and 1987-
1989 that were not brought from outside of the Malaysian banking system, in contrast,
the Asian crisis 1997-1998, the dot.com bubble in 2001 and the Global Financial crisis
in 2008 were brought from outside the country. In overall crises, Malaysian commercial
1 Domestic banks: public and private banks that are under the BNM control.
2 List of licensed Banking institutions in Malaysia:
http://www.bnm.gov.my/microsites/financial/0201_fi_list.htm
5
banks suffered more deeply from, firstly, the Asian crisis which started in Thailand and
the worst crisis in the Malaysian banking history (Khoon and Hui 2010), and secondly,
the Global Financial crises in 2008 for which this study will focus in more detail.
2.1 The 2008 Global crises
The Global financial crises had its origin in the United State, which was a result of
inequality and uncontrolled lending. Furthermore, from many years before 2008,
financial institutions were giving mortgages to people who were relying on buying
houses as that is considered as a good opportunity of investment, because of the
expectation on their rising prices and also collateral in the case of default in the lenders
point of view. Though, banks were lending as much as they could even borrow from
other financial institutions in order to lend more, unfortunately, the default in mortgage
made the house prices to fall and the financial institutions started going bankruptcy and
it was the beginning of the crisis. The American’s economy started being hurt by the
effect of the crisis by January 2008, followed by other developed countries like China,
Japan and the European countries
3
.
As Malaysia occupies the category of the developing countries, and also was relying
heavy on trading with the US financial sectors and other developed countries within
Asia. Thus, the country was affected by the contagious and the negative impact of the
Global financial crisis to the Malaysian’s economy began in the last three months of
2008. Financial institutions suffered mostly from the stock market that fell down
approximately to 50% compare to the previous year (KHOON and MAH-HUI 2010),
the other financial activities were not much affected by the crisis. However, that was a
3 http://www.wikinvest.com/concept/2008_Financial_Crisis
6
result of some positive changes made by the Malaysian government to the banking
sectors after the Asian Financial crisis. Malaysia’s export
4
constituted the major sources
of the country’s income, and the sector was the most impacted by the crisis due to the
lack of external demand, resulting to a fall of 27.8% of export by January 2009
5
. The
consequences of this fall had an effect in most of the Malaysian sectors, for instance, the
gross domestic product(GDP) growth fell by 6.2% at the beginning of the year 2009
compare to 0.1% at the end of 2008 (UNDP)
6
. It is important to note that the
unemployment level was also very high which impacted negatively the consumer
expenditures.
The picture given by the table 2.1 is supported by previous studies like the one that have
been done by Matthews and Ismael (2006), saying that foreign commercial banks started
operating in Malaysia before its independence (1957), however, the Central Bank and
domestic banks waited two years after it to be established. It is also shown in this table
that on average foreign banks could be larger than domestic in term of Assets size; and
Malaysia has higher number of foreign commercial Banks compare to the domestics.
4 Before the 2008 global crisis, Malaysia’s exports were 81% of manufacture for which 66% of electrical
and electronic merchandise.
5 http://www.adbi.org/working-paper/2009/08/26/3275.malay
sia.gfc.impact.response.rebalancing/impact.of.the.crisis.on.the.malaysian.economy/
6 A join report by the Institute of Strategic and International Study (ISIS) Malaysia commissioned by the
United Nations Development Programme.
http://www.isis.org.my/index.php?option=com_content&view=article&id=456:curr&catid=92:recent-
papers&Itemid=168
7
Table 2.1
: List of licensed Commercial Bank in Malaysia
7
:
No Banks
Ownership
Date
of
Establish
Total Asset
(USD Billion)
1 Bank Negara Malaysia
Central Bank
1959
1209.92
2 JP Morgan
Foreign
1964
2,459.13
3 HSBC
Foreign
1994
2,117.61
4 Bank of China Berhad
Foreign
1991
2,042.09
5 Bangkok Bank Berhad
Foreign
1959
970.39
6 Malayan Banking Berhad
(Maybank)
Dometic
1960
110.3
7 CIMB Bank Berhad
Domestic
1965
88.3
8 Public Bank
Domestic
1972
74.2
9 Hong Leong Bank + Eon
Bank
Domestic
2011
43.2
10 AmBank
Domestic
1975
42.4
11 RHB Bank
Domestic
1966
31.6
12 Hong Long Bank
Domestic
1968
27.8
13 Royal Bank of Scotland
Berhad
Foreign
1964
22.0 9
14 OCBC Bank Berhad
Foreign
1912
21.38
15 Mizuho Corporate Bank B Foreign
1973
20.93
16 United Overseas Bank
Berhad
Foreign
1993
18.36
17 CitiBank Berhad
Foreign
1994
16.39
18 Standard Chartered Bank Foreign
1875
15.85
19 Affin Bank
Domestic
2000
15.4
20 Eon Bank
Domestic
1960
15.2
7 http://www.bnm.gov.my/index.php?ch=13&cat=banking&type=CB&fund=0&cu=0
8
21 Allance Bank
Domestic
2004
10.4
23 Deutsche Bank (Malaysia) Foreign
1967
4.074
24 BANKOF
Tokyo-
Mitsubishi
Foreign
1959
3.12
25 Bank of Nova Scotia
Berhard
Foreign
1973
3.9
Sources: the web side of each bank and annual reports
In contrast to what we have seen in the first table, it is important to note that in the Table
2.2, domestic Islamic banks have larger size than foreign and also they are higher in
number.
9
Table 2.2: List of licensed Islamic Malaysian Banks
8
No Banks
Owner
Date
of
Establish
Asset
Size($billion)
1
CIMB Islamic Bank Berhad
Domestic 2003
70.63
2
AmIslamic Bank Berhad
Domestic 2006
37.83
3
Maybank Islamic Berhad
Domestic 1960
21.97
4
HSBC Amanah Berhad
Foreign
1994
21.25
5
Bank Islamic Malaysia Berhad
Domestic 1983
10.12
6
RHB Islamic Bank Berhad
Domestic 2005
7.54
7
Bank Muamalat Malaysia Berhad Domestic 1999
6.06
8
Hong Leong Islamic Bank
Berhad
Domestic 2005
4.06
9
Affin Islamic Bank Berhad
Domestic 1993
3.51
10 Kuwait Finance House berhad
Foreign
2005
3.38
11 Alliance Islamic Bank Berhad
Domestic 1994
2.07
12 Al Rajhi Islamic Bank Berhad
Foreign
2006
1.97
13 OCBC Al-Amin Bank Berhad
Foreign
2008
1.58
14 Standard Chartered Saadiq
Berhad
Foreign
2008
1.57
15 Public Islmic Bank Berhad
Domestic 2004
1.53
16 Asian Finance Bank Berhad
Foreign
2007
0.75
Sources: the web side of each bank and annual reports.
8 http://www.bnm.gov.my/index.php?ch=13&cat=banking&type=CB&fund=0&cu=0
10
Chapter 3
LITERATURE REVIEW
It is important to recognize that several studies have been done in order to examine the
factors influencing bank profitability, about the most popular, we have the primary
study done by Short (1979), followed by Bourke (1989) who gave more detail to the
relevant variables. The improvement of these studies has led to more specific
examination of bank profitability such as the following focusing in a particular country
or region: Molyneux and Seth (1996), Said and Tumin (2011), Sufian (2009),
Davydenko (2010), Matthewsand Ismail (2005), Flamini, McDonald and Schumacher
(2009), B Nimalathasan (2008), Gul et al (2011), Gerlach,Peng and Shu (2005), Varadi,
V. Kumar, Mavaluri, P. Kumar and Boppana, Nagarjuna (2006).
Molyneux and Seth (1996) examine foreign bank profitability and commercial credit
extension for the period 1987-1991 in the USA and they find out that the capital strength
and demand on loan have positive effect on the foreign bank profitability but
unfortunately unrelated to an improvement in commercial lending. Furthermore, in
order to generate higher profitability, a foreign bank in USA should deal with a
considerable capital, in other words with a certain higher level of capital compare to
other financial institutions.
11
Said and Tumin (2011) analyze the relationship between performance and financial
ratios of commercial banks in Malaysia and China by using some internal factors, their
results suggest that credit risk and operating expenses affect negatively the performance
of banks in both countries in the case of return on asset (ROA), however, this is
different in the case of return on equity (ROE). Therefore, in this case, credit risk and
operating expenses have respectively a negative impact on Malaysian and Chinese
banks performance. In addition, this study shows that bank performance in both
countries is not affected by bank size and liquidity.
In the case of Malaysia which is more related to this study, Sufian (2009) analyzes the
factors influencing bank profitability in Malaysia covering the period 2000-2004 and
focusing specially to foreign and domestic commercial banks. He comes up with the
results that there is a negative relationship between credit risk and loan concentrated for
Malaysian banks. Therefore, the higher the credit risks of a bank, the more its exposure
to loan payment which will result consequently in a low level of profitability. In
contrast, he finds that capital size, income from non-interest sources and operating
expenses have a positive effect on Malaysian banking profitability. Furthermore, well
capitalized bank will generate higher profitability due to lower cost of borrowing but on
the contrary is possible otherwise. The results show also, although the negative
relationship between economic growth and profitability in the Malaysian banks, high
inflation rate affect them positively.
Analyzing efficiency and productivity of Malaysian domestic and foreign commercial
banks from 1994 till 2000, Matthews and Ismail (2005) figure out that efficiency is
12
related to size instead of profitability and productivity is based on technical change.
They conclude that foreign banks are in a better position than domestic banks in the case
of efficiency.
In addition, another publication done by the same author (Sufian 2010), which analyzes
the effect of regulation and supervision in Malaysian commercial banks’ profitability for
the period 1992-2003. The results point out a negative relationship between the
regulations and supervisions and the banks’ profitability. Thus the higher the regulation
and/or supervision in the Malaysian banking system, the lower the profitability the
banks will generate from their operations. On the other hand, the economic growth has a
positive effect on Malaysian banks’ profitability and also inflation is positively related
to profitability, meaning that the level of inflation was anticipated by the banking sector.
Flamini, McDonald and Schumacher (2009) analyze the determinants of commercial
bank profitability in Sub-Saharan Africa (SSA) by testing a sample of 389 banks in 41
SSA countries. The results of this study show that private and foreign banks are doing
better than public and local banks respectively in term of profitability. It is also
mentioned that bank size, activity diversification and private ownership are positively
related to the banking profitability in terms of return on asset. In contrast, credit risk and
macroeconomic variables have a negative impact on bank profitability.
B.imalathasan (2008) uses CAMELS rating in order to do a comparative study of
financial performance of Banking Sector in Bangladesh which is categorized in four
parties: Nationalized, Public, Private and Foreign commercial banks. According to the
13
result of the analysis that is done on 48 banks covering the period of 1999-2006, there
are 3 strong banks, 31 satisfactory, 7 fair, and 2 unsatisfactory banks.
Gul et at (2011) analyze the effect of bank-specific and macroeconomic factors on
profitability in the case of Pakistan. Focusing on 15 commercial banks, covering a
period of 2005-2009; and using Pooled Ordinary Least Squares, they find that there is a
positive relationship between both internal and external factors and profitability,
meaning the higher the Equity capital, economic growth and so on, the more profitable
the banks are.
Gerlach, Peng and Shu (2005) analyze the macroeconomic conditions and banking
performance in Hong Kong by using a panel data for 29 banks covering the period of
1994-2002. They use only two ratios of profitability determinant that are Net Interest
Margin (NIM) and Non-Performing Loans (NPLS) because they couldn’t get enough
data due to some confidentiality. For instance, they don’t know the Asset size of
individual banks and they also don’t have any information about banks ownership. The
finding of the study is that changes in macroeconomic conditions affect banks’
performance and financial health.
In order to examine Efficiency of Indian banks, Varadi, V. Kumar, P. Kumar and
Boppna, Nagarjuna (2006) have used four indicators which are profitability,
productivity, asset quality and financial management for public, private and foreign
banks for a period of 1999-2003. The results of the study show that public banks have a
high efficiency according to both above ratios, whereas private banks have a very high
14
inefficiency, but foreign banks are in a better situation compare to private in term of
efficiency.
15
Chapter4
DATA AND METHODOLOGY
4.1 Data
The data that are used in this study are firstly collected from the balance sheet and
income statement of each bank that are provided throughout their financial annual
reports for the concerning period, secondly put in excel spreadsheet in order to calculate
the ratios needed for the empirical study. It is important to underline that the data are
annual data. Instead of analyzing all the local commercial banks (8)
9
, this study will
focus on the seven local banks; the reason is simply the problem that was faced in the
collecting data.
9 http://www.bnm.gov.my/index.php?ch=13&cat=banking&type=CB&fund=0&cu=0
16
Table 4.1: Selected commercial banks and Ownerships
No
Name of Banks
Ownerships
1
Affin Bank Berhad
Local Bank(domestic)
2
Alliance Bank Malaysia Berhad
Local Bank
3
CIMB Bank Berhad
Local Bank
4
Hong Leong Bank Berhad
Local bank
5
Malayan Banking Berhad
Local Bank
6
Public Bank Berhad
Local Bank
7
RHB Bank Berhad
Local Bank
8
Bank of China (Malaysia) Berhad
Foreign Bank
9
Citibank Berhad
Foreign Bank
10
Deutsche Bank (Malaysia) Berhad
Foreign Bank
11
HSBC Bank Malaysia Berhad
Foreign Bank
12
OCBC Bank (Malaysia) Berhad
Foreign Bank
13
Standard Charteredt Bank Malaysia
Berhad
Foreign Bank
14
United Overseas Bank (Malaysia)
Berhad
Foreign Bank
4.2 The Variables
Referring to the previous studies, this thesis will employ two categories of variables in
order to examine the profitability of the selected commercial banks. These categories are
classified as dependent variables and independent variables. In the case of this study,
seven (7) variables have been chosen: two dependent and five independent.
17
Table 4.2: The variables measures and their notation
Bank-Specific
Variables
Measures
Notation
Dependent
Variables
Profitability
Return on Assets(ROA)=Net
Income/Total Asset
Return on Equity=Net
Income/Total Equity
ROA
ROE
Independent
Variables
Capital Adequacy
Equity/Total Asset
CAR
Asset Quality
Total Loan, Advances and
Financing/Total Asset
ASQ
Earnings
Interest
Income/Interest
Expense
EAR
Liquidity
Liquidity Asset/Total Asset
LQR
Bank Size
Natural logarithm of Total
Asset
LSIZE
4.2.1 Dependent Variables
According the importance role played by the Return on Asset (ROA) and Return on
Equity (ROE) in the banking profitability, these dependent variables are present in
almost all the bank performance analysis.
ROA:
Return on Asset (ROA) ratio is obtained from the division of the Net Income by the
Total Asset, and expressed in percentage. It is a key indicator of profit and asset
management efficiency. Therefore, it indicates how well the bank’s assets are managed
to bring profit for each one dollar of asset that has been invested to the company or the
bank (Gul et Al 2011).
ROE:
Return on Equity (ROE) is obtained by the ratio of Net Income to Total Equity and
expressed in percentage. This ratio is also an important indicator of bank profitability in
18
the case of the use of the shareholder’s Equity. Furthermore, it shows the ability of the
management to utilize the shareholder’s Equity whether to improve the return earning or
to keep the bank in good position. Thus the better the management of the shareholder’s
Equity, the more efficient or the more profit the bank will generate in term of Return on
Equity.
4.2.2 Independent Variables
Capital adequacy:
Capital adequacy ratio, also known as capital to risk weighted asset ratio, is calculated
by the division of Equity to Total Asset and estimated as a percentage of the bank
riskiness or ability to protect its depositors from bank failure. (Mlyneux, 1993),
indicates in his study a positive relationship between Equity and bank profitability in the
case of lowering the cost of capital.
Asset Quality:
It is the ratio of Total Loan, advances and financing to Total Asset, this ratio determines
the degree of use of asset in term of Loan. As Loan is the main source of bank’s income
and is also expected to have positive impact on profit, the higher this ratio, the more
profitable the bank is in a stable economy and the worst on the other hand when the
borrowers fall to pay their promises.
Earning:
Management Efficiency is calculated as the ratio of Interest Income over Interest
Expense, this ratio will show how well a financial institution is able to use its assets and
liabilities internally. Moreover, as the goal is to earn more from the investments that
19
have been made, the higher this ratio for a company the more efficient it is in generating
more profit over its operating expenses.
Liquidity:
Liquidity Ratio is expressed as a company’s ability to repay its short-terms debts
obligations. It is obtained from the division of the Liquidity Assets by the Total Assets
of the company. A larger number of this ratio implies sufficient liquidity to meet
unexpected customers need in cash, thus the more safety for going bankruptcy. Some
authors like Bourke (1989) mentions in his study a positive relationship between
liquidity and bank profitability. In contrast, Molyneux and Thorton (1992) point out a
negative impact of liquidity on the profitability. However keeping a certain amount of
liquidity will engender loses because of the time of money.
Bank Size:
Calculated as Logarithmic of Total Asset, Bank Size is expected to have a positive
impact in the company profitability especially in economy of scale. There has been a lot
of discussion concerning the relationship between Bank Size and profitability.
Anthanasoglou et, at (2006) point out that according to some factors, increasing bank
size may have negative effect on profitability.
Dummy:
Dummy is introduced in the regression as another variable indicator of profitability
especially during a period of crisis to indicate whether the financial institutions have
20
been affected by the crisis or not. In the present study, dummy is given the value zero
(0) for the stable period and the value one (1) for the financial crisis 2008.
4.3 Methodology
4.3.1 Panel Unit root Test:
As the aim of this study is to analyze factors affecting Malaysian banking industry by
analyzing bank specific, a regression analysis is employed to the panel data that have
been collected from the balance sheet and income statement through their financial
annual report. Panel data is defined as the combination of cross-section and time series
data. Before running the regression analysis, a test has been done in order to see whether
the data are stationary or not, by doing so, a unit root test has confirmed a rejection of
the null hypothesis under the Levin Lin and Chu (LLC), Pesaran and Shin W-stat (PS);
and Fisher Chi-square (M-W), which means the data are stationary. The Unit Root of
the panel is provided in the Empirical Analysis and Results.
4.3.2 Proposed Model:
After verifying and finding that the data are stationary, it comes to the estimation of the
banking performance, and to do so, the Ordinary Least Square (OLS) is employed. The
regression analysis is done by applying Eviews software program to the OLS method,
unfortunately this OLS method will not be efficient if there is autocorrelation in the
regression model as it is in this case, because the value of Durbin Watson obtain from
the regression analysis (OLS) is below tow (2). Therefore, the best way of elimination
of the autocorrelation is to use Var model (Vector Auto regression model) that will lead
to a fitted model at lag1, lag2 and lag3 as the case in this study.
21
Referring to the dependent variables (ROA, ROE) involved in this thesis, the
econometric of the Panel Regression will be as the following:
Yi = β0 + βXi + Di + εt
Where:
Yi represents the dependent variable of the function
βο the intercept of the model
Xi represents the independent variables
Di represents the dummy variables
εt represents the error term
In respect to the model above, the regression analysis of this study are the following:
LROA=βο+β1LCAR+β2LLQR+β3LEAR+D+εt
LROE=βο+β1LCAR+β2LLQR+β3LEAR+D+εt
Asset Quality (ASQ) does not figure in the regression because of the higher
multicollinearity it has with Liquidity Ratio (LQR) and also by using it instead of LQR
the regression will not give efficient significance, the same problem is also faced with
bank size (LSIZE). In addition, the natural Logarithm is used here in order to eliminate
the trend in the model because the variables are too much volatile.
22
Chapter 5
EMPIRICAL ANALYSIS AND RESULTS
5.1 Panel Unit Root Test Results:
The results of the Unit Root Analysis indicate the rejection of the null hypothesis and
accepting the alternative meaning that the data involve in this study are stationary.
Furthermore, single star (*) stands for probability less than α=1%, double stars (**) for
α=5% and finally three stars (***) for α=10%
Unit Root Analysis (All Banks)
Variables
Levels
LLC
IPS
M-W
ROA
τT
-8.87*
0.50
41.03***
τμ
-7.13*
-0.13
37.29
τ
-3.18*
-
41.78**
ROE
τT
-7.82*
0.10
50.04*
τμ
-1.93**
1.10
21.45
τ
-4.89*
-
76.33*
CAR
τT
-4.59*
-0.68
38.27***
τμ
-1.58***
0.26
34.61
τ
-0.47
-
33.97
τT
-13.45*
-0.53
73.81
23
LQR
τμ
-5.76*
1.26
62.82*
τ
-3.81***
-
33.97
EAR
τT
-31.54*
-1.60***
52.68*
τμ
-2.3
0.33
21.71
τ
34.66
-
13.90
5.2 Correlation Analysis:
Correlation analysis is employed to identify the relationship between a dependent
variable and one or more independent variables. In the case of this study, the correlation
is analyzed in three separate categories or groups: firstly, the correlation of the variables
for all banks in general, secondly, for domestic banks, and finally, for foreign banks.
Correlation analysis plays double role in the regression analysis model by indicating
how the dependent variable is affected by the independent variables and by testing for
the existence of multicollinearity between the independent variables. It is important to
note that in all the three tables of correlation below, the dependent variables (ROA and
ROE) are positively correlated.
24
Table 5.1: correlation Matrix for All banks
ROA
ROE
CAR
LQR ASQ LSIZE EFF D
ROA
1.00
ROE
0.60
1.00
CAR
-0.01
-0.62
1.00
LQR
-0.23
-0.28
0.31
1*.00
ASQ
0.27
0.28
-0.24
-0.92 1.00
LSIZE 0.23
.41
-0.60
0.61
0.51 1.00
EAR
0.29
0.06
0.01
-0.03 0.08 0.06 1.00
D
0.12
0.10
-0.10
-0.10 0.00 -0.00 -0.16 1.00
According to the result of the correlation analysis in table 5.1, Capital Adequacy (CAR)
and Liquidity (LQR) have negative effect on both Return on Asset (ROA) and Return
on Equity (ROE), in contrast, Asset Quality (ASQ) and Erning (EAR) affect ROA and
ROE positively. The same table shows a higher negative (-0.92) correlation between
two independent variables which are ASQ and LQR, also a low correlation between
these variables and the other remaining, thus the presence of multicollinearity problem
in the model. However, in order to eliminate this higher multicollinearity, ASQ and
bank size have been dropped and in the case of the lower value of Durbin Watson
(below 2), a Var model at lag3 is used.
25
Table 5.2: Correlation Matrix for Domestic Banks
ROA
ROE
CAR
LQR
ASQ
EFF
D
ROA
1.00
ROE
0.41
1.00
2
CAR
0.39
-0.51
1.00
LQR
-0.18
-0.12
0.02
1.00
ASQ
0.18
0.04
-0.02
-0.70
1.0
EAR
0.24
-0.10
0.08
-0.37
0.47
1.00
D
0.02
0.19
-0.09
-0.13
-0.08
-0.21
1.00
This table 5.2 indicates that a positive relationship between ROA and CAR, ASQ, EAR
and a negative with LQR. Looking to the ROE, only ASQ has positive impact on it,
while the other variables (CAR, LQR, and EAR) have inverse relationship. Here also,
there is higher negative (-0.70) correlation between ASQ and LQR as the case in the
table 5.1.
26
Table 5.3: Correlation Matrix for Foreign Banks
ROA
ROE
CAR
LQR
ASQ
EFF
D
ROA
1.00
ROE
0.70
1.00
CAR
-0.22
-0.68
1.00
LQR
-0.33
-0.45
0.40
1.00
ASQ
0.36
0.41
-0.28
-0.96
1.00
EAR
0.32
0.08
-0.01
0.03
0.07
1.00
D
0.21
0.01
0.01
-0.10
0.03
-0.15
1.00
As in the first table this for the foreign banks shows that ASQ and EAR are positively
related to both on ROA and ROE, however, CAR and LQR affect them negatively. The
higher negative correlation between ASQ and LQR also appeared in these results.
5.3 Regression Analysis Results
After finding the correlation between the variables, the present task is to see whether the
explanatory (independent) variables affect or not the explained (dependent) variables, in
other word, to see how the selected ratios (CAR, LQR, ASQ, EAR, LSIZE) impact
profitability of financial institutions which are represented by ROA and ROE in this
case. Furthermore, the regression analysis result is categorized in three parts as the
following:
5.3.1 Regression Analysis Result of All Banks
The regression analysis shows a negative relationship between Capital Adequacy
(Equity/Total Asset) and Return on Asset (ROA) at lag3 and also this independent
27
variable is statistically significant. This finding suggests that when the Capital
Adequacy increases, profitability will decrease. In another words, when the banks
increase the use of Equity, they will register more losses. The explanation of this
phenomenon can be firstly the amount they are paying to their shareholders as a
dividend is greater than what they are generating from it as a profit. Secondly, it could
be the case that they are using retain earning without investing it in new plan that will
give more profit to the company. Regarding the second profitability indicator which is
the Return on Equity (ROE), Capital Adequacy (CAR) is not significant, that means
ROE is not affected by CAR. Liquidity (Liquidity Asset/Total Asset) is also statistically
significant and has two different effects on the ROA; the first one is negative impact at
lag2 and second is positive at lag3. In the first case of the negative impact is supported
by the previous studies as Molyneux and Thorton (1992) point out a negative impact of
liquidity (LQR) on the banking sector profitability. Therefore, in this situation
increasing liquidity will decrease profitability. In the second one, the positive impact on
ROA is a good sign of profitability because it shows that banks have the ability to meet
unexpected demand in cash by their customers. Bourke (1989) mentions in his study a
positive relationship between Liquidity and bank’s profitability. Similarly to it relation
with ROA, LQR has one negative effect at lag1 and one positive effect at lag3 to the
ROE and it is statistically significant. That means at lag1 in order to get benefit or
increase the profit, Malaysian banks should reduce the amount of liquidity they are
taking from their shareholders. In contrast, at lag3 they should increase liquidity as it
will bring more profit. Coming to Earning (Interest Income/Interest Expense), as the
precedent LQR, Earning (EAR) affects ROA and ROE in two sense invers and it is also
statistically significant. At lag2 it impacts both ROA and ROE negatively meaning that
28
the management of assets and liabilities of banks could not work efficiently in order to
generate sufficient interest income. However, at lag3 EAR has a positive relationship
with also both ROA and ROE, according to this relationship here, the higher the
Earning, the more profit the banks will have. Dummy is significant only in the case of
ROE and affects it negatively at lag1. This shows that Malaysian commercial banks also
suffered from the Global Financial crisis 2008 which started in the U.S.
5.3.2 Regression Analysis Result of Domestic Banks:
The regression analysis result of domestic banks shows that CAR is not statistically
significant in both ROA and ROE. Thus it does not have any effect in these profitability
indicators. LQR has a positive impact in both ROA and ROE and also significant at lag3
in the two dependent variables. Therefore, an increase in liquidity indicates an increase
in domestic banks profitability, thus the more safety for them of going bankruptcy. EAR
has positive relationship with ROA and statistically significant at lag3, that means assets
and liabilities are well utilized by the management team and generate more profit.
Dummy does not have any significance effect on Malaysian domestic bank’s
profitability indicators. Therefore, they did not suffer from any losses due to the Global
Financial Crisis 2008.
5.2.3 Regression Analysis Result of Foreign Banks:
The result of this regression analysis indicates that CAR has a positive impact on ROA
as well as on ROE and is also significant in both at lag1. Therefore, as CAR is defined
as Equity/Total Asset, the higher the increase in Equity the more profit of foreign banks;
this is the result of the reduction of the cost of funding. LQR is not statistically
significant, thus does not affect any of the dependent variables, and consequently does
not impact the profitability of foreign banks. The behavior of EAR here (foreign banks)
29
is similar to that one with All Banks, this means that EAR is significant in both cases
(ROA and ROE) and has two different manners of affecting these ROA and ROE
profitability indicators. In the ROA side, EFF has a positive relationship at lag1 and
negative one at lag2. When coming to the ROE, it has positive impact at lag1 and lag3;
and a negative one at lag2. The meaning of these changes is that banks can not keep
gaining or losing profit continuously in their period of operation. Dummy variable is
statistically significant at lag1 and has a negative effect on both ROA and ROE, the
meaning of that is that Malaysian foreign banks were affected by the Global Financial
Crisis 2008; as a consequence, they registered losses from their annual operating
income.
5.4 Comparison between Domestic and Foreign Banks
Comparison between the two categories of ownerships in term of profitability is done by
taking the average of ROA and ROE of the banks respectively; and then finding their
graph in the same figure. By doing so, figure 5.1 and figure 5.2 show that foreign banks
are more profitable than domestics banks, they highlight also that the former were more
affected by the 2008 crisis than the latter. As a result of the consequence of the crisis,
foreign banks register a lot of losses in the preceding years. Note that ROA1 and ROE1
stand for domestic; and ROA2 and ROE2 for foreign.
30
Figure 5.1: ROA measure for All the Malaysian Banks
ROA1: Domestic Banks
ROA2: Foreign Banks
0.00000
0.50000
1.00000
1.50000
2.00000
2.50000
3.00000
3.50000
4.00000
2005
2006
2007
2008
2009
2010
2011
ROA1
ROA2
31
Figure 5.2: ROE measure for All the Malaysian Banks
ROE1: DOMESTIC Banks
ROE2: Foreign Banks
0.00000
10.00000
20.00000
30.00000
40.00000
50.00000
60.00000
2005
2006
2007
2008
2009
2010
2011
ROE1
ROE2
32
Chapter 6
CONCLUSION AND SUGGESTION
The aim of this study is to examine the performance of the Malaysian’s local and
foreign banks, and compare their profitability in the financial sector. Profitability of
commercial banks can be influenced by several factors, such as liquidity, Asset Quality,
capital, operating expenses, and the size of the banks. Measuring the profitability in
term of Return on Asset (ROA) and Return on Equity (ROE) is done by using bank
specific variables and Dummy is introduced in the regression as another factor that
influence profitability especially during the period of 2008 to indicate whether the
financial institutions have been affected by the crisis or not. For this analysis, a panel
regression methodology has been applied to empirically investigate the performance of
seven (7) local and seven (7) foreign commercial banks, covering a period between
2005 and 2011. Some previous studies have been carried out in the same field such as
the work of Sufian (2009) investigating the factors influencing the profitability of the
Malaysian banking industry covering the period 2000-2004 and focusing specially to
foreign and domestic commercial banks. He comes up with the results that there is a
negative relationship between credit risk and loan concentrated for Malaysian banks. In
contrast, he finds that capital size, income from non-interest sources and operating
expenses have a positive effect on Malaysian banking profitability.
33
The empirical finding shows that all commercial banks are positively affected by LQR,
EFF, in contrast, they are negatively impacted by CAR, LQR, EAR and Dummy at
some lags (see tables of Var Mdel). In the case of domestic banks LQR and EAR have
positive effect on profitability; the remaining variables are not significant. Profitability
of foreign banks is affected positively by CAR, EAR; and negatively by EAR and
dummy at some different lags.
The comparison between the two categories of ownership indicates that foreign banks
are more profitable than domestic; this is supported by the study of Matthews and Ismail
(2005) saying that foreign Malaysian banks are in better position than domestic in the
case of profitability.
The suggestion of this Thesis for future studies is to introduce additional bank specific
and macroeconomic variables in order extend these results. Regarding the policy maker,
it would be better to encourage domestic banks by providing some support such as
providing subsidy or making a reduction on their taxes comparably to foreign banks.
34
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38
APPENDICES
39
Unit Root Analysis (All Banks)
Variables
Levels
LLC
IPS
M-W
ROA
τT
-8.87*
0.50
41.03***
τμ
-7.13*
-0.13
37.29
τ
-3.18*
-
41.78**
ROE
τT
-7.82*
0.10
50.04*
τμ
-1.93**
1.10
21.45
τ
-4.89*
-
76.33*
CAR
τT
-4.59*
-0.68
38.27***
τμ
-1.58***
0.26
34.61
τ
-0.47
-
33.97
LQR
τT
-13.45*
-0.53
73.81
τμ
-5.76*
1.26
62.82*
τ
-3.81***
-
33.97
EAR
τT
-31.54*
-1.60***
52.68*
τμ
-2.3
0.33
21.71
τ
34.66
-
13.90
40
Unit Root Analysis (Domestic Banks)
Variables
Levels
LLC
IPS
M-W
ROA
τT
-11.78*
-0.69
39.38*
τμ
-11.61*
-2.83*
38.61*
τ
-2.62*
24.29**
ROE
τT
-9.68*
-0.78
46.93*
τμ
-5.13*
-1.25
25.85**
τ
-3.46*
39.93*
CAR
τT
-3.72*
0.33
23.27***
τμ
-2.03**
0.04
13.58
τ
0.81
8.95
LQR
τT
-11.80*
-0.91
49.50*
τμ
-3.72*
-0.86
28.27**
τ
-4.03*
24.00***
τ
0.96
6.75
EAR
τT
-19.91*
-1.36***
32.47*
τμ
-1.30***
0.66
7.85
τ
21.18
6.16
41
Unit Root Analysis (Foreign Banks)
Variables
Levels
LLC
IPS
M-W
ROA
τT
-1.19
0.18
4.29
τμ
2.50
1.30
5.35
τ
-2.12*
18.69
ROE
τT
-4.05*
0.13
19.93
τμ
-1.04
1.27
11.87
τ
-4.10*
31.92*
CAR
τT
-3.07*
0.49
11.43
τμ
-1.28*
0.38
13.82
τ
-1.25
14.81
LQR
τT
-4.81*
0.23
21.74***
τμ
-4.43*
-0.90
31.73*
τ
-1.02
11.86
ASQ
τT
-5.38*
-6.00
30.04*
τμ
-5.89*
-1.52***
45.04*
τ
-0.90
19.32
EAR
τT
-4.80*
0.17
19.65
τμ
-2.94*
-0.31
15.42
τ
-0.03
6.54
42
Regression Analysis for all the Banks
Dependent Variable: LROE
Method: Panel Least Squares
Date: 05/03/12 Time: 16:29
Sample: 2005 2011
Periods included: 7
Cross-sections included: 14
Total panel (balanced) observations: 98
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
6.006070
0.381598
15.73925
0.0000
LCAR
-1.083099
0.083478
-12.97460
0.0000
LLQR
-0.129011
0.095041
-1.357418
0.1779
LEAR
0.473448
0.204616
2.313831
0.0229
D
0.134217
0.098119
1.367892
0.1746
R-squared
0.684339 Mean dependent var
3.617860
Adjusted R-squared
0.670763 S.D. dependent var
0.576450
S.E. of regression
0.330763 Akaike info criterion
0.674842
Sum squared resid
10.17457 Schwarz criterion
0.806728
Log likelihood
-28.06724 Hannan-Quinn criter.
0.728187
F-statistic
50.40508 Durbin-Watson stat
1.111897
Prob(F-statistic)
0.000000
Dependent Variable: LROA
Method: Panel Least Squares
Date: 05/03/12 Time: 16:28
Sample: 2005 2011
Periods included: 7
Cross-sections included: 14
Total panel (balanced) observations: 98
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
1.400740
0.381562
3.671064
0.0004
LCAR
-0.083057
0.083471
-0.995040
0.3223
LLQR
-0.128976
0.095033
-1.357182
0.1780
LEAR
0.473387
0.204597
2.313750
0.0229
D
0.134226
0.098110
1.368120
0.1746
R-squared
0.107042 Mean dependent var
1.119032
Adjusted R-squared
0.068635 S.D. dependent var
0.342701
S.E. of regression
0.330732 Akaike info criterion
0.674653
Sum squared resid
10.17265 Schwarz criterion
0.806540
Log likelihood
-28.05802 Hannan-Quinn criter.
0.727999
F-statistic
2.787054 Durbin-Watson stat
1.112036
Prob(F-statistic)
0.030915
43
Regression Analysis for Domestic Banks
Dependent Variable: LROA
Method: Panel Least Squares
Date: 05/08/12 Time: 18:11
Sample: 2005 2011
Periods included: 7
Cross-sections included: 7
Total panel (balanced) observations: 49
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
0.664885
0.615788
1.079729
0.2861
LCAR
0.231273
0.143565
1.610925
0.1143
LLQR
-0.060108
0.125768
-0.477933
0.6351
LEAR
0.245851
0.394021
0.623953
0.5359
D
0.074776
0.123887
0.603581
0.5492
R-squared
0.090358 Mean dependent var
1.123976
Adjusted R-squared
0.007663 S.D. dependent var
0.282908
S.E. of regression
0.281822 Akaike info criterion
0.401368
Sum squared resid
3.494637 Schwarz criterion
0.594411
Log likelihood
-4.833514 Hannan-Quinn criter.
0.474608
F-statistic
1.092672 Durbin-Watson stat
1.290100
Prob(F-statistic)
0.371974
Dependent Variable: LROE
Method: Panel Least Squares
Date: 05/08/12 Time: 18:12
Sample: 2005 2011
Periods included: 7
Cross-sections included: 7
Total panel (balanced) observations: 49
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
5.270065
0.615794
8.558161
0.0000
LCAR
-0.768711
0.143567
-5.354384
0.0000
LLQR
-0.060116
0.125769
-0.477986
0.6350
LEAR
0.245851
0.394025
0.623948
0.5359
D
0.074744
0.123888
0.603316
0.5494
R-squared
0.420798 Mean dependent var
3.638860
Adjusted R-squared
0.368143 S.D. dependent var
0.354543
S.E. of regression
0.281825 Akaike info criterion
0.401387
Sum squared resid
3.494702 Schwarz criterion
0.594430
Log likelihood
-4.833972 Hannan-Quinn criter.
0.474627
F-statistic
7.991635 Durbin-Watson stat
1.289917
Prob(F-statistic)
0.000062
44
Regression Analysis for Foreign Banks
Dependent Variable: LROA
Method: Panel Least Squares
Date: 05/10/12 Time: 01:18
Sample: 2005 2011
Periods included: 7
Cross-sections included: 7
Total panel (balanced) observations: 49
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
1.903969
0.666420
2.857010
0.0065
LCAR
-0.156396
0.115753
-1.351116
0.1836
LLQR
-0.227016
0.185074
-1.226622
0.2265
LEAR
0.500027
0.259328
1.928168
0.0603
D
0.227432
0.153099
1.485525
0.1445
R-squared
0.212127 Mean dependent var
1.114088
Adjusted R-squared
0.140503 S.D. dependent var
0.396545
S.E. of regression
0.367634 Akaike info criterion
0.932991
Sum squared resid
5.946796 Schwarz criterion
1.126034
Log likelihood
-17.85828 Hannan-Quinn criter.
1.006231
F-statistic
2.961647 Durbin-Watson stat
0.979700
Prob(F-statistic)
0.029879
Dependent Variable: LROE
Method: Panel Least Squares
Date: 05/10/12 Time: 01:18
Sample: 2005 2011
Periods included: 7
Cross-sections included: 7
Total panel (balanced) observations: 49
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
6.509157
0.666511
9.766022
0.0000
LCAR
-1.156466
0.115769
-9.989457
0.0000
LLQR
-0.227011
0.185099
-1.226429
0.2266
LEAR
0.500126
0.259363
1.928286
0.0603
D
0.227461
0.153119
1.485516
0.1445
R-squared
0.772577 Mean dependent var
3.596859
Adjusted R-squared
0.751903 S.D. dependent var
0.738181
S.E. of regression
0.367683 Akaike info criterion
0.933262
Sum squared resid
5.948409 Schwarz criterion
1.126305
Log likelihood
-17.86493 Hannan-Quinn criter.
1.006502
F-statistic
37.36812 Durbin-Watson stat
0.979532
Prob(F-statistic)
0.000000
45
Var model of ROA of All Banks
LROA
LROA(-1)
0.787165
(0.31173)
[ 2.52515]
LROA(-2)
-0.307000
(0.37107)
[-0.82733]
LROA(-3)
-0.251620
(0.23296)
[-1.08009]
LCAR(-1)
-0.074521
(0.11034)
[-0.67539]
LCAR(-2)
0.139953
(0.19086)
[ 0.73326]
LCAR(-3)
-0.356222
(0.15794)
[-2.25549]
LLQR(-1)
-0.240578
(0.13408)
[-1.79427]
LLQR(-2)
-0.374747
(0.16861)
[-2.22252]
LLQR(-3)
0.717548
(0.09766)
[ 7.34755]
LEAR(-1)
0.113119
(0.20316)
[ 0.55681]
LEAR(-2)
-2.040824
(0.33153)
[-6.15573]
LEAR(-3)
3.342458
(0.47382)
[ 7.05432]
D
-0.105122
46
C
0.154760
(0.45324)
[ 0.34145]
R-squared
0.864572
Adj. R-squared
0.813787
Sum sq. resids
1.274080
S.E. equation
0.178471
F-statistic
17.02404
Log likelihood
26.46700
Akaike AIC
-0.373821
Schwarz SC
0.204851
Mean dependent
1.049461
S.D. dependent
0.413584
Var Model of ROE of All Banks
LROE
LROE(-1)
0.348040
(0.40790)
[ 0.85324]
LROE(-2)
0.295222
(0.48562)
[ 0.60793]
LROE(-3)
0.103330
(0.30475)
[ 0.33906]
LCAR(-1)
0.306520
(0.36876)
[ 0.83121]
LCAR(-2)
-0.229539
(0.38419)
[-0.59746]
LCAR(-3)
-0.248970
(0.32968)
[-0.75520]
47
8LLQR(-1)
-0.523877
(0.17540)
[-2.98674]
LLQR(-2)
-0.155779
(0.22056)
[-0.70629]
LLQR(-3)
0.642726
(0.12773)
[ 5.03184]
LEAR(-1)
0.074867
(0.26575)
[ 0.28172]
LEAR(-2)
-1.955905
(0.43365)
[-4.51032]
LEAR(-3)
2.479366
(0.61976)
[ 4.00055]
D
-0.205456
(0.09503)
[-2.16210]
C
0.974648
(1.78582)
[ 0.54577]
R-squared
0.882569
Adj. R-squared
0.838533
Sum sq. resids
2.179903
S.E. equation
0.233447
F-statistic
20.04175
Log likelihood
11.42944
Akaike AIC
0.163234
Schwarz SC
0.741906
Mean dependent
3.526446
S.D. dependent
0.580960
Var Model of ROA of Domestic Banks
LROA
48
LROA(-1)
0.273531
(0.62680)
[ 0.43639]
LROA(-2)
-0.169872
(0.73726)
[-0.23041]
LROA(-3)
-0.486860
(0.42071)
[-1.15722]
LCAR(-1)
0.092140
(0.16811)
[ 0.54809]
LCAR(-2)
0.026446
(0.26753)
[ 0.09885]
LCAR(-3)
0.021701
(0.27020)
[ 0.08032]
LLQR(-1)
-0.319289
(0.20151)
[-1.58446]
LLQR(-2)
-0.111991
(0.26126)
[-0.42866]
LLQR(-3)
0.644583
(0.13520)
[ 4.76762]
LEAR(-1)
-0.036219
(0.66963)
[-0.05409]
LEAR(-2)
-0.105671
(0.83733)
[-0.12620]
49
LEAR(-3)
2.227668
(0.91099)
[ 2.44533]
D
-0.046663
(0.12313)
[-0.37898]
C
-0.822065
(1.86177)
[-0.44155]
R-squared
0.863950
Adj. R-squared
0.693887
Sum sq. resids
0.389614
S.E. equation
0.180188
F-statistic
5.080185
Log likelihood
20.11695
Akaike AIC
-0.294068
Schwarz SC
0.467192
Mean dependent
1.066579
S.D. dependent
0.325676
Var Model of ROE of Domestic Banks
LROE
LROE(-1)
-0.358590
(0.96971)
[-0.36979]
LROE(-2)
0.468711
(1.14067)
[ 0.41091]
LROE(-3)
-0.105640
(0.65078)
[-0.16233]
LCAR(-1)
-0.101412
(0.84911)
[-0.11943]
LCAR(-2)
-0.037122
50
(0.98066)
[-0.03785]
LCAR(-3)
-0.021221
(0.64711)
[-0.03279]
LLQR(-1)
-0.501346
(0.31166)
[-1.60862]
LLQR(-2)
0.105748
(0.40397)
[ 0.26177]
LLQR(-3)
0.562261
(0.20903)
[ 2.68981]
LEAR(-1)
-0.229994
(1.03529)
[-0.22215]
LEAR(-2)
-0.005127
(1.29485)
[-0.00396]
LEAR(-3)
0.411004
(1.40866)
[ 0.29177]
D
-0.193773
(0.19040)
[-1.01773]
C
3.360233
(5.64396)
[ 0.59537]
R-squared
0.745204
Adj. R-squared
0.426708
Sum sq. resids
0.931437
S.E. equation
0.278603
F-statistic
2.339763
Log likelihood
7.914951
Akaike AIC
0.577503
Schwarz SC
1.338763
Mean dependent
3.578717
S.D. dependent
0.367958
51
Var Model of ROE of Foreign Banks
LROA
LROA(-1)
1.122359
(0.42838)
[ 2.61998]
LROA(-2)
0.057979
(0.63873)
[ 0.09077]
LROA(-3)
0.263494
(0.36319)
[ 0.72549]
LCAR(-1)
0.866079
(0.35907)
[ 2.41201]
LCAR(-2)
-0.538179
(0.46867)
[-1.14830]
LCAR(-3)
-0.282704
(0.28149)
[-1.00430]
LLQR(-1)
0.246019
(0.29392)
[ 0.83704]
LLQR(-2)
-0.617033
(0.39450)
[-1.56409]
LLQR(-3)
0.228128
(0.44521)
[ 0.51240]
LEAR(-1)
0.510237
(0.23036)
[ 2.21497]
LEAR(-2)
-2.912200
(0.41893)
[-6.95154]
LEAR(-3)
1.786901
(1.15130)
[ 1.55207]
D
-0.367593
52
(0.09892)
[-3.71589]
C
0.404548
(0.55046)
[ 0.73493]
R-squared
0.965199
Adj. R-squared
0.921699
Sum sq. resids
0.227166
S.E. equation
0.137588
F-statistic
22.18813
Log likelihood
27.66960
Akaike AIC
-0.833543
Schwarz SC
-0.072283
Mean dependent
1.032343
S.D. dependent
0.491696
Var Model of ROE of Foreign Banks
LROE
LROE(-1)
1.111212
(0.40349)
[ 2.75403]
LROE(-2)
0.054312
(0.60217)
[ 0.09019]
LROE(-3)
0.079927
(0.34201)
[ 0.23370]
LCAR(-1)
1.061531
(0.41161)
[ 2.57899]
LCAR(-2)
-0.842658
(0.69849)
[-1.20640]
LCAR(-3)
0.172190
(0.35051)
[ 0.49125]
LLQR(-1)
-0.022663
(0.27685)
[-0.08186]
LLQR(-2)
-0.696338
53
(0.37165)
[-1.87365]
LLQR(-3)
0.554980
(0.41956)
[ 1.32277]
LEAR(-1)
0.412174
(0.21705)
[ 1.89897]
LEAR(-2)
-2.751378
(0.39475)
[-6.96989]
LEAR(-3)
2.369656
(1.08480)
[ 2.18441]
D
-0.343610
(0.09318)
[-3.68771]
C
-1.153389
(2.79999)
[-0.41193]
R-squared
0.986342
Adj. R-squared
0.969269
Sum sq. resids
0.201522
S.E. equation
0.129590
F-statistic
57.77304
Log likelihood
29.34659
Akaike AIC
-0.953328
Schwarz SC
-0.192068
Mean dependent
3.474176
S.D. dependent
0.739236