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MARKET STRUCTURE, STRATEGIC CHOICE AND BANK
PERFORMANCE: EVIDENCE FROM SRI LANKA
A DISSERTATION
Submitted to the
DEPARTMENT OF FINANCE
FACULTY OF COMMERCE AND MANAGEMENT STUDIES
In partial fulfillment of requirement of the
BACHELOR OF BUSINESS MANAGEMENT (SPECIAL) DEGREE IN
FINANCE
November 2014
Piyumi Chanika Amarakoon
BM/2009/012
Department of Finance
University of Kelaniya
Sri Lanka
Certificate of Declaration
I, Piyumi Chanika Amarakoon, declare that this dissertation title “Market structure,
strategic Choice and Bank Performance is entirely my own work and has not
previously been submitted for a degree in any university.
To the best of my
knowledge and belief, the dissertation contains no material previously published or
written by another person except where due reference is made in the dissertation
itself.
…………………………….
Piyumi Chanika Amarakoon
BM/2009/012
22/11/2014
Countersigned
Supervisor
Name
: Ms. J.M.R. Fernando
Signature
:
Date
: 22/11/2014
ii
Recommendation
Hereby I recommend that the dissertation on “Market Structure, Strategic Choice and
Bank Performance by Piyumi Chanika Amarakoon (BM/2009/012) prepare under my
supervision can be accepted in partial fulfillment of the requirements of the Bachelor
of Business Management (Finance) special degree programme.
……………………….
Supervisor
Name
: Ms. J.M.R. Fernando
Signature
:
Date
: 22/11/2014
iii
ACKNOWLEDGEMENT
I would like to take this opportunity to express my profound gratitude and deep regard
to Dr. D.M.Semasinghe, Dean of the Faculty of Commerce and Management Studies,
University of Kelaniya, Dr. P.N.D.Fernando, Head of the Department of Finance for
the opportunity that they have given for me as an undergraduate of the Department of
Finance to complete an important study about banking industry, which is vital
industry in the economy of Sri Lanka.
I am heartily thankful to my supervisor, lecturer Ms. J.M.R.Fernando, whose
encouragement, guidance and support from the initial point until the end.
Her
insightful advices and expertise were very valuable to complete this research.
The accomplishment of this research would not have been possible without the
support of many others who also deserve acknowledgement and I would like to
appreciate all the lecturers of the Department of Finance for their support and advices
throughout the success of this study.
I should also offer my sincere thanks to my parents, who given me their blessing in
every moment and for all my friends and other persons who helped me with all the
ways that they can to complete the research and for giving me their encouragement
and thoughtful comments at the necessary situations.
iv
Market Structure, Strategic Choice and Bank Performance:
Evidence from Sri Lanka
Piyumi Chanika Amarakoon
Department of Finance, University of Kelaniya, Sri Lanka
Abstract
The effect of market structure and performance of banking industry has been studied
extensively for American banks and for European banks. In contrast, little work has
been done to study this effect for Asian banks. Some of researchers in Sri Lanka have
identified the effect of market structure on performance of the banks. Even though
the market structure or market concentration has a direct effect to the performance,
the performance is also affected by the strategies that are followed by the banks and
those strategies such as risk taking strategy, cost efficiency and diversification create
an indirect effect of market structure to the bank performance. Hence, based on
structure conduct performance paradigm this paper has developed and tested the
performance of the banks in Sri Lanka.
As per the analysis, there is a significant positive effect of market concentration on
bank performance where as significant negative effects of risk taking strategy and the
cost efficiency strategy and insignificant negative effect from diversification strategy.
Furthermore, the paper has identified when there is a low market concentration the
performance of the banks, credit risk and cost efficiency is also low whereas with
high market concentration the performance of the banks and diversification is high,
but the credit risk and cost efficiency are low.
Keywords: Market structure, Operational Efficiency, Diversification, Credit Risk,
Bank performance
v
CONTENTS
1. INTRODUCTION .................................................................................... 1-5
1.1.
Background of the Study .............................................................................. 1-2
1.2.
The Research Problem .................................................................................. 2-3
1.3.
The objectives of the study ........................................................................... 3-4
1.4.
Significance of the Study..................................................................................4
1.5.
Scope and Limitations of the Study..................................................................5
1.6.
Chapter Organization........................................................................................5
2. LITERATURE REVIEW ........................................................................ 6-17
2.1.
Chapter Introduction.........................................................................................6
2.2.
Review of Literature ................................................................................... 6-12
2.3.
Chapter Summary ..................................................................................... 12-17
3. RESEARCH METHODOLOGY ............................................................ 18-27
3.1.
Chapter Introduction.......................................................................................18
3.2.
Research design ..............................................................................................18
3.3.
Population and Sample Selection ............................................................. 18-19
3.4.
Conceptual Framework............................................................................. 19-20
3.5.
Operationalization..................................................................................... 20-22
3.6.
Hypotheses of the Study ........................................................................... 23-26
3.7.
Data Collection Techniques............................................................................26
3.8.
Data Analysis and Model Specification ................................................... 26-27
3.9.
Chapter Summary ...........................................................................................27
vi
4. RESULTS AND DISCUSSION ............................................................. 28-48
4.1.
Chapter Introduction.......................................................................................28
4.2.
An Overview of the Analysis ................................................................... 28-29
4.3.
Data Analysis Method Used ...........................................................................29
4.4.
Descriptive Statistics ................................................................................ 29-31
4.5.
Testing the Normality .....................................................................................31
4.6.
Testing the Ordinary Least Square Assumption....................................... 31-33
4.7.
Correlations............................................................................................... 33-34
4.8.
Regression Analysis.................................................................................. 34-40
4.9.
Hypotheses Testing................................................................................... 40-47
4.10. Chapter Summary ...........................................................................................48
5. SUMMARY AND CONCLUSION ..................................................................49-54
5.1.
Chapter Introduction.......................................................................................49
5.2.
Summary of Results.................................................................................. 49-54
5.3.
Conclusion ......................................................................................................54
REFERENCES ........................................................................... 55-56
APPENDIXES............................................................................ 57-61
vii
LIST OF FIGURES
Figure 01
Conceptualization.......................................................................................20
Figure 02
Summary of Direct and Indirect Effect ......................................................40
LIST OF GRAPHS
Graph 01
Testing Homoscedasticity..........................................................................32
LIST OF TABLES
Table 01
Table of Literature ............................................................................... 13-17
Table 02
Descriptive Statistics..................................................................................30
Table 03
Correlations between the Variables ...........................................................32
Table 04
Model Summary ........................................................................................33
Table 05
ANOVA Table...........................................................................................35
Table 06
Coefficients.......................................................................................... 36-37
Table 07
Summary of causal effects................................................................... 39-40
Table 08
Categorization of banks based on HHI ......................................................41
Table 09
Correlations (Banks with low HHI)...........................................................43
Table 10
Correlations (Banks with moderate HHI)..................................................43
Table 11
Correlations (Banks with high HHI)..........................................................44
viii
Table 12
Summary of Results...................................................................................50
Table 13
Relationship between market concentration and bank performance .........51
Table 14
Relationship between market concentration and risk taking strategy........52
Table 15
Relationship between market concentration and cost efficiency...............53
Table 16
Relationship between market concentration and diversification ...............53
LIST OF ABBREVIATIONS
ROA
Return on Assets
ROE
Return on Equity
MC
Market Concentration
CR
Credit Risk
CEff
Cost Efficiency
DIV
Diversification
ix
CHAPTER I
INTRODUCTION
1.1 Background of the Study
The center of development in an economy is the financial markets and the institutions. From
all the financial institutions, the banks are playing a major role as a financial intermediary.
When considered the Sri Lankan economy, during past few years banking industry has
experienced a huge transformation due to tighten in the regulations mainly in risk
management framework, development in information and communication technology and
globalization of the banking industry.
The banking industry is the main intermediary in the financial services sector in Sri Lanka
which holds approximately 69% of the total financial assets (Central Bank of Sri Lanka,
2013).
Therefore efficiency and performance of the banking industry are the key
requirements for the development of the sector. After more than thirty years of narrow
economic policies and financial control, the economic policy changes package was
introduced in 1977 which covered the way for structural translation of the overall economy
(Dunham & Kelegama, 1996). The policies included some drastic policy changes in relation
to deregulation of the financial services sector, along with the other economic modifications.
Financial restructurings in Sri Lanka commenced in past decades aimed to improve the
performance of banks through enhancing competitiveness and efficiency of the industry.
Initial structural changes in financial services sector were mainly focusing on giving greater
freedom to the private sector. So the government encouraged new entrants to the financial
services market. Those changes were affected to expand the scope of the banking industry as
well as to increase the number of firms in the banking industry. Structural changes in the
industry aimed to enhance competition expecting productivity and efficiency enhancements
1
in banks. Ultimately the policy makers aimed to improve the performance of overall banking
industry.
1.2
The Research Problem
Widen of the scope of the operations of the banks, increase in the number of banks and
branches, enhancing the quality of the human resource of the banks and increase in the
efficiency of the operations due to use of new technology has been affecting to the
performance of the banks. Even though these are observable, it is necessary to quantify how
far the performance of the banks is affected by the above mentioned factors. This research
focuses on identifying the direct and indirect effect of market structure, strategic choices such
as risk taking strategy/ credit risk, cost efficiency and diversification strategies on bank
performance and the relationship between market structure, strategic choices and the
performance of the banks in Sri Lankan context.
There are several strategies that the banks are used in order to increase the performance of the
banks. The first one lies in limiting the number of banking units in the market through
encouraging mergers among existing banks (Byeongyong, Choi and Weiss, 2005; Williams,
Molyneux and Thornton1994; Molyneux 1999; Moore, Robert, 1998). This helps to increase
the bank size for perusing scale of economics. The second strategy is the sharing common
facilities such as ATM with other banks in the industry.
Both strategies are useful in
enhancing the competition in the market and improving the overall productivity and
efficiency of the market.
In Sri Lankan context, there is a continuous increase in the gross loans, deposits and also the
return on assets of the banks from 2009 onwards (Sri Lankan Banks, outlook 2012).
According to that, even during the world financial crisis situation these banks were
performing well when compared to the banks in world economy. The main reasons for that
2
were the several strategies followed by the Sri Lankan banks under the supervision of Central
Bank of Sri Lanka. A research conducted by Seelanatha (2010), identified the relationship
between market structure and the performance of the banks in Sri Lanka. But assessing the
strategies emphasized earlier is on the banks performance and identifies the relationship
between low, medium and high market concentration and bank performances are the current
necessities of the country.
In order to evaluate the consequences of these strategies, it is necessary to examine the
current market structure of the banking industry, to determine the degree of competition, and
to investigate the impact the concentration is likely to have on the market structure and the
behavior of banks. A greater level of competition and efficiency in the banking system can
contribute to better financial stability, product innovation, and access by households and
firms to financial services, which in turn can expand the prospects for economic growth.
Setting the point departure, this study would like to address “Whether the bank performances
are affected by the market structure, strategic choices such as risk taking strategy, cost
efficiency and diversification strategies.
1.3
Objectives of the Study
The purpose of this paper is to examine the direct and indirect effects of strategic choice and
market structure on bank performance. This research covers the study on market structure,
strategic choice and bank performance in several important ways. Therefore the objectives of
the study are;
i.
To identify the direct and indirect effect of market concentration on bank
performance.
ii.
To identify the effect of strategic choices (Risk taking strategy, cost efficiency
strategy and diversification strategy).
3
iii.
To measure the relationship between market concentration and bank
performance.
iv.
To measure the relationship between strategic choices (Risk taking strategy,
cost efficiency strategy and diversification strategy) and bank performance.
v.
To measure the relationship between market concentration and strategic
choices (Risk taking strategy, cost efficiency strategy and diversification
strategy).
vi.
1.4
To identify the effect of market concentration on strategic choices.
Significance of the Study
This study focuses to identify how the market structure and the strategic choices of the banks
finally affect to the performance of those banks. The research will help for the improvement
of the banking industry since this provides an idea of the best strategy that should be followed
by the banks. The strategies include risk taking strategy, cost strategy and diversification
strategy. Hence, the study assists the banks to select the best strategy in order to increase the
performance of the banks and to be competitive within their industry.
Thus the banks will be able to identify the relationships of the performance of the banks with
those strategies and how to manage those strategies within the competitive environment.
When acquiring the new technology to their operations, the banks can select the best
technology which is aligning with their strategy. The policy makers of the country will be
able to make the policies while generating the more advantages over the banking industry and
to the economy of Sri Lanka. The regulatory bodies can focus on putting the regulations
which will enhance the performance of the industry while increasing the growth of the
economy.
4
1.5
Scope and Limitations of the Study
However there are some problems when determining the sample and also determining the
model for the study. When determining the model for the study, there can be multi-colinearity situations, autocorrelation and hetroscedasticity.
The sample of the study should represent the whole population. Since the banks are having
different efficiency levels and also different performance levels, if the research concerns only
one to two categories it is difficult to give a suitable conclusion for the study. Thus it is
necessary to choose the reliable data sources in order to obtain the accurate inputs to the
research.
1.6
Chapter Organization
This paper is organized as follows. The next section presents a brief review of literature
related with market structure, bank operational efficiency, credit risk and diversification
giving special reference to the banking industry and hypothesis development. The third
section detailed the empirical framework used.
The fourth section presents results and
implication of the study. The last section presents conclusions of the study.
5
CHAPTER II
LITERATURE REVIEW
2.1 Chapter Introduction
Literature review is an analysis of definition and the researches done by previous researchers.
The literature review can be explained as of the published work from secondary sources of
data in area of specific interest to the researcher. This research will focus on how the market
structure, strategic choices such as risk taking strategy or credit risk strategy, cost efficiency
strategy and diversification strategy affect to the performance of the banks. Hence, the
paragraphs below will discuss the previous literatures carry out with relate to the variables
such as market structure, cost efficiency, credit risk, diversification and measuring
performance of banks.
2.2 Review of Literature
The earlier studies as in the table 01 have used various methods such as structural and nonstructural approaches to measure the performance of banks with relate to different market
structures and different efficiency levels.
Structural approaches are grounded on the
traditional industrial organization theory which concentrates on the structure conduct
performance (SCP) paradigm and on the efficient structure paradigm. Those literatures
mainly focused on the level of competition and how this is linked to concentration, and
whether the structure of the banking system does affect profitability. But non-structural
approaches assume that factors other than market structure and concentration may affect
competitive behavior, such as entry or exit barriers and the general contestability of the
market.
As per the past study conducted using structure conduct performance (SCP) paradigm, the
efficiency hypothesis and the P-R model (Mugume, 2006) there was a positive relationship
6
between profitability and market concentration according to the structure-conductperformance paradigm, but the efficient structure hypothesis interprets that the positive
relationship is not a consequence of market power but of the greater efficiency of firms with
larger market share. In other words, higher efficiency creates both higher concentration and
greater profitability. These two theories observed that there is a positive relationship between
the market concentration and the performance of banks. But the way of interpretation of the
relationship was different in those theories as efficient structure hypothesis explains an
indirect relationship of market concentration with the performance of the banks.
The relative market power hypothesis (RMP), which is a special case of structure conduct
performance states that the firms with large market shares and well differentiated product
lines have ability to exercise market power to obtain greater profit on non-competitive price
setting behavior, not directly but indirectly by interacting with other key determinants such as
bank age, bank ownership status and regulation (Mirzaei, Moore & Liu, 2001). They argued
that there is a positive relationship between profitability and market share in advanced
economies but not in emerging economies. Further they have found that the market power is
not directly influences bank performance. It is indirectly affect to performance by interacting
with other key determinants, such as market power, bank age, bank ownership status and
regulation. This study rebutted the direct positive relationship explained by Mugume, (2006).
The study conducted to identify the most powerful variable from market power and the
market efficiency that was having a major influence on the performance of the banks (Jeon &
Miller, 2005) concluded that there was a robust positive correlation between bank
concentration and the average return on equity and most powerful variable was the market
power not the market efficiency. Even though the increasing market concentration leads to
increase the profitability of the banks decreasing market concentration does not directly affect
the decrease in the profitability of banks.
This research has confirmed the finding of
7
Mugume, 2006 which explains the positive relationship between market concentration and
the performance of banks.
According to the study carry out by Gldbreg and Rai (1995), the structure conduct
performance (SCP) hypothesis has emphasized that banks were able to extract monopolistic
charges in concentrated markets by their ability to offer lower deposit rates and charge higher
loan rates and the efficient-structure (EFS) hypothesis has stated that efficient firms increase
in size and market share because of their ability to generate higher profits which usually leads
to higher market concentration. Gldbreg and Rai (1995) has emphasized that the government
controlled banks are run less efficiently and consequently are less profitable also they have
not found a positive relationship between market concentration and profitability of banks in
European countries. The findings of the study are contrast to the research conducted by Jeon
& Miller, 2005 who have found the robust positive relationship.
Some of the researches emphasized that the market concentration was shown to be
insignificant in bank performance (Maudos, 1998). These findings suggested that bank
regulatory decisions based on concerns for their impact on changes in concentration may be
inappropriate and should focus instead on bank efficiency.
Market share is used as
representative of the market structure, and has a statistically significant positive effect on
profitability. Thus the results show that efficiency is highly significant and positive when
determining the performance of banks. However market power has the moderate relationship
with bank performance. As per the literature, market power has considered as the market
power and rebutted the robust positive relationship explained by Jeon & Miller, 2005 and
accepted the results of the research carry out by Mirzaei, Moore & Liu, 2001.
Atemnkeng and Joseph (1999) found that there was a positive relationship between market
structure and banks profitability within the institutional context of the banking system and the
8
role of market concentration in the determination of bank profitability was very much
important.
Further the overall result indicates that bank size, loan-deposit ratio and
devaluation were directly contributed to the profit rate of the banks while the loan-asset ratio
and operation expenses contrariwise affects banks profitability. The major theories applied
by this study were the structure conduct performance (SCP) hypothesis and the relative
market power (RMP) hypothesis. Corporate performance of the banks which is calculated by
using return on assets, return on capital and return on equity was the dependent variable and
the independent variables were the market concentration, management of capital of the bank,
loan portfolio of the bank, total advances to total deposit, bank size measure, expense control
and compositions of deposits of the bank. Still the research emphasized that the market
power is vital when measuring the performance of the banks rather than the relationship with
other variables.
Muharrami, Saeed, and Kent (2009) have analyzed the relationship between market structure
and bank performance. For that purpose they have employed four hypotheses to test the
relationship between efficiency, market structure and profitability the main hypotheses used
by them were the structure conduct performance (SCP) hypothesis and the relative market
power (RMP) hypothesis.
The research has found that there was positive relationship
between profits of the banks and market structure and the presence of an efficiency measure
provides support for the traditional structure conduct performance (SCP) rather than relative
market power (RMP) hypothesis. The evidence presented in the study clearly supports the
view that concentration is the principal structural determinant of profitability and not market
share. It has again proved the findings of Mirzaei, Moore & Liu, 2001.
Some literatures aimed to evaluate the role of market structure in the pricing behaviour and
profitability (More and Marton, 2003). A simple Cornet model has developed by them in
order to determine the most important variables related to the pricing behaviour of the banks
9
and profitability of the banks. The major theories applied by this study also were the
structure conduct performance (SCP) hypothesis and the relative market power (RMP)
hypothesis. One of the most important findings of this study lies in showing that the tests
could not confirm the SCP, as market concentration was found to have no positive correlation
with either the net interest margin or ROA. This research implied that banks did not earn
higher profits by means of conspiring with other banks to apply higher margins in more
concentrated markets. And the empirical results provided support for the RMP hypothesis.
Furthermore the results of the research have proved that cost and risk levels and the size of
reserve requirements have become incorporated into pricing decisions. According to the
literature, there appears to be a close negative correlation between the relative size of the
banking sector and pricing and the profitability.
This is more against the conclusions
provided by most of the researches discussed in the literature as the positive relationship
identified in between market structure and profitability of banks.
The research conducted by Belkhaoui, Lakhal, Faten and Hellara (2014) has shown that
market structure has a positive and indirect effect on bank performance and that market share
has a positive and direct effect on bank performance.
Strategic variables related to risk
taking and diversification affect directly and indirectly bank performance and the indirect
effect occurs via market share. The results suggested that the mediating role played by the
strategic choice in the relationship between market structure and performance is complete.
In order to identify the relationship between market structure, strategic choice and the
performance of the banks they have built a model using path analysis. To measure bank
performance they have used the present value of expected future profits, not the return on
equity or return on assets and market structure was calculated using the market concentration.
Several types of strategic choices were observed by them called risk taking strategy and
diversification strategy and cost leadership strategy. Belkhaoui, Lakhal, Faten and Hellara
10
(2014) have identified a gap which is not identified by other researchers, that is to consider
the strategies followed by different kind of banks in different nations. It leads to get an
understanding of the best strategy which should pursue by the banks in order to increase the
performance of the banks.
The study conducted by Seelanatha (2010) has studied main structural and performance
features of banking industry in Sri Lanka. The study used the hypotheses proposed by Berger
and Hannan (1997) called structure conduct performance (SCP) hypothesis, the relative
market power (RMP) hypothesis and relative market power (RMP) hypothesis and two
performance measures namely return on assets (ROA) and net interest margin (NIM).
Empirical results are not consistent with both market power hypothesis and structure conduct
performance hypothesis. It is appeared that high market concentration with small number of
large banks in the industry has intensified the competition. Confirming the major arguments
against the profit concentration relationship, this study totally rejected the traditional SCP
hypothesis. However the findings of the study rejected significant profit market power
relationship. Empirical results pointed out that efficient operation of banking firms are vital
for having higher profitability with better net interest margin. This study has established the
view of Mirzaei, Moore & Liu, 2001 that there is not having a positive relationship between
market powers or the market concentration and the performance of banks in the emerging
countries.
Consequently, some researchers argued that there is a vigorous positive relationship between
market structure and bank performance while some have found that there is a positive
relationship in the banks in advanced economies rather than the banks in the emerging
countries. Several researches emphasized that the market structure is the main determinant of
the performance of banks than the market share. But accordingly there are few factors such
as bank age, bank ownership status and regulation which are supported to be interacted with
11
the market power when agree on the positive relationship with the performance of the banks.
The little number of researches has concluded the negative relationship between market
structure, market power or market concentration and the profitability of banks.
2.3 Chapter Summary
Since in an emerging economy, the concentration on the finance institutions mainly on the
banks are very significant it is necessary to judge what would be the best strategy that should
follow in order to achieve the competitive advantage. Having considering strategic choices,
some of the researchers conducted their researches and have found a positive relationship
between market structure and the performance of banks with direct and indirect relationships.
Even though the research carry out in the Sri Lankan context concluded that there is not
having a positive relationship between market structure and performance, emphasized that
efficiency and performance of the banks in Sri Lanka is having direct relationship.
12
Table 01: Table of Literature
Title
Authors
Problem
Objectives
Methodology
Market
Adam
Structure
Mugume
and
Performance
in Uganda's
Banking
Industry
The level of competition
and how this is linked to
concentration,
and
whether the structure of
the banking system does
affect profitability
To examine the competitiveness of The P-R Model
Uganda’s banking industry.
To examine Uganda’s banking industry
market structure and its impact on banks’
profitability.
To examine bank efficiency and its
possible impact on the market structures
To empirically ascertain the relative
strength of market power and efficiency
in explaining the banks’ profitability.
Does Market
Structure
Matter
on
Banks’
Profitability
and Stability
Can the market power
hypothesis be applied to
the emerging market
banking system?
Why are banks operated
in
the
emerging
economies
more
profitable than their
counterparts in advanced
economies?
To what extent are
discrepancies
in
determinants of bank risk
and returns due to
Investigate the effect of market structure
in banks on profitability and stability, in
particular whether banks, who are
operating in concentrated markets
generate more profit or not, whilst taking
into account of the bank-specific
characteristics; whether banks are
efficiently managed.
Examine overall effect of financial
structure and macroeconomic conditions;
whether financial development and
business cycles affect bank risk and
returns.
Ali
Mirzaei,
Tomoe
Moore &
Guy Liu
13
Findings
A positive relationship
between
profitability
and
market
concentration according
to the SCP paradigm.
A higher efficiency
creates both higher
concentration
and
greater
profitability
according to efficient
structure hypothesis.
Profitability – ROA
A positive relationship
Market
structure
- between
profitability
market share and market and market share in
concentration (Lorenz advanced economies.
Curve for market share)
Market power not only
influences
bank
performance
directly,
but also indirectly by
interacting with other
key determinants.
variations in factors
under the control of bank
management
and/or
factors relating financial
structures?
Market
Samir
Whether the market
structure,
Belkhaou, structure, strategic choice
strategic
Lassaad
(risk
taking,
choices and Lakhal,
diversification and cost
bank
Faten
leadership) affect to the
performance Lakhal & performance
of
the
Slaheddie banks?
Hellara
Bank
Performance
:
Market
Power
or
Efficient
Structure?
Develop and test a conceptual model of Bank Performance bank performance.
Present
value
of
expected future profits,
Use of the path analysis method to Market
structure
estimate the direct and indirect Market Concentration,
relationships.
Bank strategic choice
(Risk-taking,
diversification
strategy
and
cost
leadership strategies)
Yongil
Why
are
more The paper considers the market-power
Jeon
& concentrated
markets versus the efficient structure theories of
Stephen
more profitable?
the positive correlation between banking
M.
concentration and performance on a
Miller
state-by-state basis.
14
Market
structure
Market Concentration &
Profit-Structure
Relationships - market
power and efficient
structure theories
The market structure has
a positive and indirect
effect
on
bank
performance, and that
market share has a
positive and direct effect
on bank performance.
Strategic
variables
related to risk taking and
diversification
affect
directly and indirectly
bank performance. The
indirect effect occurs via
market share.
Robust
positive
correlation
between
bank concentration in a
state and the average
return on equity within
that state.
The
structure
performance
relationship
for European
banking
Lawrence
G.
Gldbreg
& Anoop
Rai
The
structure Measure the performance
performance relationship European banks.
for European banking is
also positive as the
American banks?
of
the The Berger and Hannan Government controlled
(1993) model
banks are run less
efficiently
and
consequently are less
profitable.
Market
structure and
performance
in Spanish
banking
using
a
direct
measure of
efficiency
Market
Structure
and
Profitability
Performance
in
the
Banking
Industry of
CFA
Joaquin
Maudos
Does the market structure Paper analyses the relationship between Performance - ROA,
of Spanish banks affect market structure and performance within ROE, Efficiency - data
to the performance of the Spanish banking industry.
envelopment analysis
those banks?
Market share is used as
representative of the
market structure, and
has
a
statistically
significant
positive
effect on profitability
Tabi
Atemnkeg
J.
&
Nzongang
Joseph
Does the market structure
affect to the performance
of the banking industry
of CFA?
The
relationship
between
commercial
bank
profits
and
concentration or market
power is positive and
the
coefficient
is
statistically significant
at the 5 percent and 10
percent level in the
specifications
The main objective of this study is to test
empirically the Structure - Performance
(S- P) hypothesis within the context of
the Cameroonian Commercial banking
system.
15
Corporate Performance ROA, ROC, ROE
Independent variables –
market
concentration,
Management of bank’s
capital, Bank’s loan
portfolio,
Total
advances
to
total
deposit,
Bank
size
measure,
Expense
control, Compositions of
Market
Power
versus
EfficientStructure in
Arab GCC
Banking
AlMuharrai,
Saeed,
Matthews
& Kent
What is the factor from
market
power
and
efficient structure which
is affecting to the
performance of the Arab
banks?
Assess the relevance of the StructureConduct-Performance
(SCP),
the
Relative-Market-Power (RMP) and the
Efficient- Structure (ES) hypotheses in
the GCC banking industry.
Examine the evidence for the Hicks
(1935) Quiet Life Hypothesis (QL).
Relationship
Between
Market
Structure
and
Bank
Performance
Csaba
Do the changes in the
Móré & operating
environment
Márton
also exert a substantial
Nagy
impact on the structure of
banking markets and the
degree of competition?
Do the dominance of
private
(foreign)
ownership and stable
financial systems in
place,
banks'
performance and pricing
behaviour have become
increasingly
marketbased.
The study aims to assess the role of
market structure in the pricing behaviour
and profitability of Central and Eastern
European banks.
16
the bank’s deposits
Performance - ROA,
ROE
Efficiency - Berger and
Hannan (1993) model
Concentration – HHI
Price of a productaverage loan rates
Performance
ROA,ROE
Market
structure
Market Concentration
The evidence presented
here clearly supports the
view that concentration
is the principal structural
determinant
of
profitability and not
market share
The tests could not
confirm
the
SCP
hypothesis in Central
and Eastern Europe, as
market
concentration
was found to have no
positive correlation with
either the net interest
margin or ROA. This
implies that in more
concentrated markets,
banks did not earn
higher profits by means
of colluding with other
banks to apply higher
margins.
Market
Lalith
structure,
Seelanata
efficiency
and
performance
of banking
industry in
Sri Lanka
How the banks’ market
structure and banks’
efficiency
have
influenced
the
performance
of
the
banking firms?
This paper reviewed how the banks’
efficiency and market structure affect the
overall performance of the banking firms
measured in terms of profitability and net
interest margin using structure conduct
performance literature.
17
Performance - ROA,
ROE
Efficiency - Berger and
Hannan (1993) model
Concentration – HHI
The traditional structure
conduct
performance
argument is not held in
the banking industry in
Sri Lanka and the banks
performance does not
depend on either market
concentration or market
power of individual
firms but on the level of
efficiency
of
the
banking units.
CHAPTER III
RESEARCH METHODOLOGY
3.1
Chapter Introduction
This chapter discusses the methodology for the study which includes the research
design, population and sample selection, operationalization, conceptualization,
hypothesis development, data collection techniques and model specification to
facilitate the study to achieve the established objectives.
3.2
Research Design
The research focuses on identifying the effect of market structure, strategic choices
such as risk taking or credit risk, operational efficiency and diversification and the
performance of Sri Lankan Banks and the relationship between those variables. This
is a descriptive and deductive study which is to identify the effect and the relationship
between each of the variables. The research quantifies the data and generalizes the
results from the sample to the population of interest while testing the hypothesis
generated with relate to the objectives of the study.
3.3
Population and Sample Selection
The focused population consists of Licensed Commercial Banks in Sri Lanka for five
years starting from 2009 to 2013. From those banks, the research concern is all the
licensed commercial banks in Sri Lanka except Union bank of Colombo and Amana
Bank due to unavailability of sufficient information throughout the research period as
both banks have started those operations on 2010, since therefore it is unable to obtain
the financial information for year 2009. The licensed specialized banks have been
18
ignored from the sample since the financial position, financial performance,
efficiency, market concentration and also the risk management system are not same as
the licensed commercial banks and therefore it is unreasonable to include in the same
sample as to analyze the effect and relationship between market structure, strategic
choice and bank performance.
Therefore the sample includes all the licensed commercial banks excluding Union
bank of Colombo and Amana Bank for five years begins with 2009 to 2013 which
represents almost all the banks in population. The sample is selected based on the
convenience and considering the availability of the information.
3.4
Conceptual Framework
The conceptual framework of the study is based on the Structure Conduct
Performance (SCP) paradigm developed by Joe S. Bain in Industrial Organization
Economics which offers a causal theoretical explanation for firm performance through
economic conduct on incomplete markets and it is published by Edward Chamberlin
and Joan Robinson. The market concentration can be identified as the structure, the
strategic choices as the conduct and the return on equity and return on assets as the
performance. According to that the conceptualization of the study can be developed
as follows.
19
Market Structure
Strategic Choices
Bank Performance
Credit Risk
Market
Concentration
ROA and
ROE
Cost Efficiency
Diversification
Figure 01: Conceptualization
3.5
Operationalization
As this study is about the market structure, strategic choices including risk taking or
credit risk, cost efficiency and diversifications and the performance of the banks it is
necessary to identify the operationalization of the selected variables.
Bank Performance
Here the performance of the banks is the financial performance which can be simply
expressed as the profitability of banks. It can be measured using Return on Assets
(ROA) or Return on Equity (ROE). The equations are as follows,
ROA =
Net Income
ROE =
Net Income
Total Average Equity
Total Average Assets
Net income is identified based on the net profit after tax of the bank. Total average
assets and average equity are obtained from dividing opening balances plus closing
balances by two.
20
Market Structure/ Market Concentration
The market structure can be explained as the relative market share of each bank.
This is also known as the market concentration.
Market concentration can be
measured using the Herfindahl-Hirschman index (HHI) which is widely used in the
past literatures (Seelanatha, 2010 and Belkhaoui, Lakhal, Faten & Hellara, 2014).
HHIt = ∑௡௜ୀଵ(‫ܵ ܯ‬it)2
In the HHI index, t means the end of the particular period, n means the number of
sectors that the bank is focusing on and the i means the particular bank of the sample.
Since the HHI index is used in two independent variables, market structure and
diversification there can be occurred a multicollinearity problem. So the market share
of each bank is eliminated from the index. Market share of bank i measured at the
end of each year t, by using the ratio below.
MSit =
Deposits of the bank i
Total deposits of the banking sector
Credit Risk
Credit risk is the potential for losses due to failure of a borrower to meet its
contractual obligation to repay a debt in accordance with the agreed terms. It can be
measured as follows;
CR = Non Performing Loans
Total Bank loans
21
Managing the credit risk can be identified as a risk taking strategy that can be used by
the banks in order to mitigate the risk of reducing the quality of assets of the banks.
Diversification
Another strategy that can be used by banks is the diversification strategy. This
reflects the variety of assets included in statement of financial position of the banks
such as advances and loans, other assets and the fixed assets of the banks.
Diversification of assets is measured by using Herfindahl-Hirschman index (HHI) of
assets.
HHIit =
∑n
(Assetk/Total assets of the bank)2
k=1
In the HHI index, t means the end of the particular period, n means the number of
sectors that the bank is focusing on, k means the type of the assets and the i means the
particular bank of the sample. The main assets types are loans & advances, fixed
assets, other interest earning assets and non interest earning assets. According to the
index, a high index value indicates a low diversification of the banks.
Cost Efficiency
In terms of banks the cost efficiency means, how far the revenue can be generated by
the bank while minimizing the operational cost of the bank.
CEff = Total expenses – Finance Cost
Revenue
This strategy will helps to discover the banks’ ability to move with market
competition as cost leaders while enhancing the profitability level of the banks.
22
3.6
Hypotheses of the Study
The relationship between market structure, strategic choices and bank performance is
basically based on the structure-conduct-paradigm. According to Muharrami, Saeed,
and Kent (2009), market structure is the principal determinant which is positively
affect to the performance of banks which is significant. Belkhaoui, Lakhal, Faten and
Hellara (2014) also explained that there is a positive relationship between market
structure and bank performance. As per the study conducted by Mugume (2006) there
was a positive relationship between profitability and market concentration according
to the structure-conduct-performance paradigm. These literatures lead to following
hypothesis;
H1 – Market Concentration positively affect to the bank performance
According to Hicks’s (1935) “Quiet Life Hypothesis” firms trying to secure their
operations if the firm is more concentrated. With relate to banks, it would increase
the risk of assets portfolio which would finally increase the credit risk. Then the
banks may try to focus on more supervision and monitoring process and it would
cause to go away from the risk taking strategy (Belkhaoui, Lakhal, Faten and Hellara,
2014). Therefore there is a negative relationship between market concentration and
risk taking strategy where the effect of market concentration on risk taking strategy is
significant. This can be concluded as the hypothesis below.
H2 - Market Concentration negatively affect to the risk taking strategy
The effect of market structure on the cost efficiency has discussed in few literatures
(Belkhaoui, Lakhal, Faten and Hellara, 2014). When there is a more concentration on
a particular industry, then it is caused to an increase in competition and finally to
23
increase in the operational expenses. As per above study there is a significant effect
of market concentration on the cost efficiency strategy. But due to more competition
within a particular industry, income generation is becoming low and it would grounds
to decrease in efficiency. The hypothesis developed for the concept as follows;
H3 - Market Concentration negatively affect to the cost efficiency strategy
The research conducted by Christensen and Montgomery (1981) shows that the
increase in market structure will cause to a decrease in the degree of diversification of
the banks.
In addition to that a few previous researches show that banks adopt a
strategy of strong diversification when the market is more competitive, that means
when there is a low concentration (Belkhaoui, Lakhal, Faten and Hellara, 2014).
Since the increased competition generally destroys the profitability of banks, the
banks adopt a diversification strategy to maintain profitability.
Under these
conditions it is expectable that in case of market concentration banks are likely to
specialize in a limited number of activities, in general terms low diversification of
assets of the bank. So the research will test following hypothesis;
H4 - Market Concentration negatively affect to the diversification strategy
Some authors (Hellmann et al., 2002; Beck et al., 2006) show that the relationship
between risk-taking-strategy on the other hand credit risk and profitability of the
banks are unstable.
But with regard to banking industry, the decrease in the
performance of the banks is mainly due to the increased in credit risk as failure of
borrower to meet its contractual obligations in a timely manner. So this will lead to
following hypothesis;
24
H5 – Risk taking strategy negatively affect bank performance
As explained in efficient structure theory, effective cost management will direct to
increase in the profitability level, because of reducing the cost incurred.
Cost
efficiency is one of the strategies that can be followed by the banks in order to
enhance the performance of banks while focusing on taking the best advantages from
the products and services provided. According to Belkhaoui, Lakhal, Faten and
Hellara, 2014; Mugume, 2006 there is a positive relationship between cost efficiency
and bank performance. Therefore the following hypothesis is formulated;
H6 – Cost efficiency strategy positively affect bank performance
Generally, diversification is needed when gain from such strategy offset the cost
incurred for implementation. Notwithstanding the fact that it may wipe out the value
of the firm, diversification is a vital strategic choice which is taken by managers.
Banks are permitted to enlarge the scope of their activities beyond the traditional role
of financial intermediation. They are then able to decrease the average financing cost
through a combination of several different funds. Diversification could destroy firm
value (De Long, 2001). The negative effect of diversification on firm performance
can be explained through the agency costs associated with debt (Hadlock et al., 2001).
It should be noted that regardless of the lack of a compromise on the effects of
diversification the general trend in the literature suggests that diversification destroys
firm value (Belkhaoui, Lakhal, Faten and Hellara, 2014). So the study formulates the
following hypothesis;
H7 – Diversification strategy negatively affect bank performance
25
3.7
Data Collection Techniques
The research data are collected from the secondary sources such as annual reports of
the banks. Financial information for five years begins with 2009 to 2013 is extracted
from the annually audited financial statements and other required information is
collected from the websites of banks.
3.8
Data Analysis and Model Specification
The study basically focuses on identifying the direct and indirect relationship between
market structure and bank performance, effect of the market concentration on the
strategic choices such as risk taking strategy, cost efficiency and diversification and to
identify the relationship between those strategies with the bank performances. For
that purpose following regression models has been specified.
ROAit = ß1 + ß(mc)MCt+ ß(cr)CRit + ß(eff)CEffit + ß(div)DIVit + Uit
ROEit = ß1 + ß(mc)MCt+ ß(cr)CRit + ß(eff)CEffit + ß(div)DIVit + Uit
In order to identify the effect of market concentration on the strategic choices, the
following models have been developed.
CEffit = ß3 + ß(mc)MCt+ Uit
CRit = ß2 + ß(mc)MCt+ Uit
DIVit = ß4 + ß(mc)MCt+ Uit
26
Where ROA is the ratio of bank i at the end of the year t; MC is the market
concentration at the end of year t; CR is the credit risk at the end of year t; CEff is the
cost efficiency at the end of year t; DIV is the diversification at the end of year t of
bank i. The direct effect can be identified as the effect of market concentration and
strategic choices (Credit risk, cost efficiency and diversification) on bank
performance.
The indirect effect is the effect of market concentration on bank
performance via the strategic choices, which are initially identified using the effect of
market concentration on strategic choices and then multiply those effects with the
strategic choices on bank performance.
3.9
Chapter Summary
The methodology chapter is developed to attain the research objectives in order to
address the research problems.
This chapter discussed the research design,
operationalization, population and sample selection, conceptualization, hypothesis of
the study, data collection techniques and the model specification and data analysis
techniques. Results and conclusion of the study will be discussed under the next
chapters.
27
CHAPTER IV
ANALYSIS AND DISCUSSION
4.1
Chapter Introduction
This chapter focuses on the collection of data, data analysis and also discusses the
findings from the analysis. In addition to that this chapter includes assessing the
assumptions with relate to the ordinary least square method and testing of the
hypotheses of the study while achieving the mentioned objectives as in the chapter
one.
4.2
An Overview of the Analysis
The required data for the study obtained from the annual reports of each bank and
covering five years. To measure the performance of the banks the research has used
the return on assets ratio (ROA) and return on equity (ROE) where those are
calculated using the profit after tax and average total assets or average total equity of
each bank.
Credit risk is calculated by using the non-performing loans and advances (NPL) ratio
and to obtain the non-performing loan ratio, the research has obtained non-performing
loans of each bank and the total loans and advances of the banks and then dividing the
non-performing loans from the total loans and advances.
Market structure of banks can be identified as the market concentration of the banks.
The market concentration is calculated by using the Herfindahl Hirschman Index
(HHI), eliminating the effect of market share. To come up with the ratio, obtained the
percentages of loans and advances of each bank are divided among the various
28
industries and that is multiplied by the market share which is arrived by dividing the
total deposits of the bank by the total deposits of the banking industry.
The cost efficiency is the ratio between operating expenses and the income of the
banks. So collected the data with relate to the revenue, total expenses and interest
expenses and arrived with the cost efficiency ratio.
To calculate the diversification the research has used the Herfindahl Hirschman Index
of assets and to arrive at the figure, obtained the combination of the assets of the bank
and split among the assets relate to the loans and advances, fixed assets, other interest
earning assets and non-interest earning assets and obtained the HHI of assets.
4.3
Data Analysis Method Used
To find the relationships, study has used the correlation and to measure the direct and
indirect effect of the independent variables to the dependent variables study used
regression analysis.
4.4
Descriptive Statistics
Descriptive statistics is the discipline of quantitatively describing the main features of
a collection of information, or the quantitative description itself (Dodge, 2003).
In
descriptive statistics central tendency and dispersion measures are used to describe the
dataset.
Central tendency include mean, median and mode, while the measures for
dispersion include standard deviation, variance, and distribution measures includes
skewness and kurtosis. Table 02 represents the descriptive statistics for the sample.
29
Table 02: Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
ROA
80
0.0001
0.0213
0.0126
0.0051
ROE
80
0.0054
0.4292
0.1768
0.0735
CR
80
0.0025
0.3352
0.0516
0.0550
CEff
80
0.1487
1.1091
0.3598
0.1715
MC
80
0.0010
0.6630
0.0755
0.1492
DIV
80
0.3704
0.6164
0.4744
0.0568
As in the table above (Table 02) the number of observations included in the regression
analysis is eighty observations with two dependent variables; return on assets and
return on equity and four independent variables; market concentration, credit risk,
cost efficiency and diversification. The minimum value is the lowest value with relate
to the variables and maximum is the highest value of mentioned variables. The mean
value is the measurement of central tendency where it represents the average value of
the above variables. According to the statistics it can be observed that the minimum
return on assets is 0.01% whereas the maximum is 2.13%. But compare to the return
on assets, return on equity of the banks is having the higher ratio and the average is
also indicates a higher value of 17.68%. The credit risk, market concentration and
diversification respectively are having the ratio of 5.16%, 7.55% and 47.44%. Even
though the maximum value of the cost efficiency is 110.91%, due to the lower ratio of
one of the bank the mean has decreased to 35.98%.
The standard deviation measures the spread of the observations. The higher the value
of standard deviation, the spread of the observations is also higher. Except cost
efficiency and market concentration ratio, the return on equity, credit risk and
30
diversification are having smaller spread whereas the return on assets is having the
smallest variance of 0.0051 in the observations.
4.5
Testing the Normality
In order to identify the observations that have the unusual values in the dependent
variables, the study has tested the normality and according to the testing, identified
that the return of assets of some of the banks has the abnormal ratio when compared
to the return of assets of the other banks. After removing the unusual ratios related to
return on assets, again tested the normality of the observations in the sample. The
sample is normally distributed means the Shapiro-wilk value should be approximately
one and the Shapiro-wilk value for return on assets of this model is 0.96 which
indicates that the sample is normally distributed.
4.6
Testing the Ordinary Least Square Assumptions
There are several assumptions that should be satisfied in order to have better results in
the analysis. Such as parameters of the regression should be linear, homoscedasticity
of the error term, no perfect multicollinearity, no autocorrelation between disturbance
terms, zero covariance between error term, variability in the independent variables,
number of observations should be greater than the number of parameters etc.
When considering the regression model of the study, there are eighty variables which
are more than the number of parameters. The correlation table (Table 03) shows that
there are no significant correlations among the independent variables.
can be concluded that there is no perfect multicollinearity in this model.
31
Therefore it
Table 03: Correlation between the Variables
ROA
ROE
CR
CEff
MC
DIV
ROA
1
ROE
0.69512
1
CR
-0.16674
-0.25851
1
CEff
-0.60417
-0.56083
-0.09652
1
MC
0.07165
0.16112
-0.00733
-0.02376
1
DIV
0.29658
0.32020
-0.18733
-0.42335
-0.09392
1
To test the homoscedasticity of the error term, performed the park test and ensured
that the disturbance term is normally distributed. The graph (Graph 01) below shows
that the disturbance term is normally distributed and there is the homoscedasticity in
the regression model.
Graph 01: Testing Homoscedasticity
32
Next assumption is to ensure that there are no any correlations between the
disturbance terms of the model. To test the assumption of autocorrelation, this study
has used the Durbin Watson value. As in the model summary (Table 04) the Durbin
Watson value in the model one, ROA model is 1.695 and in the model two, ROE
model the Durbin Watson value is 2.043 which very close to the benchmark value 2.
Table 04: Model Summary
Model
4.7
Dependent
Variable
R
R Square
Adjusted R
Square
Std. Error of
the Estimate
DurbinWatson
1
ROA
0.64735
0.41906
0.38808
0.00400
2.04334
2
ROE
0.65956
0.43502
0.40489
0.05668
1.69532
Correlations
Correlation measures the relationship between two variables. Generally the results of
correlation explain using correlation coefficient. Correlation coefficient is a measure
of the linear correlation between two variables, giving a value between +1 and −1
inclusive, where 1 is total positive correlation, 0 is no correlation and −1 is total
negative correlation. As explained earlier in this study, correlation analysis has used
to find out the interrelationships between the variables such as return on assets,
market concentration, credit risk, cost efficiency and diversification. The results
obtained from statistical analysis are presented in the correlation table (Table 03).
As in the table 03, there is a negative relationship between return on assets and credit
risk and cost efficiency.
The relationships show that there are weak negative
relationships between return on assets and credit risk whereas medium negative
33
relationship between cost efficiency. The relationship between return on equity and
credit risk also shows a weak negative relationship whereas with cost efficiency there
is a medium negative relationship.
Cost efficiency and credit risk show that there is a weak negative relationship of the
banks. And also there are weak negative relationships between market concentration
& credit risk, market concentration & cost efficiency and market concentration &
diversification. According to the correlation table, it shows that there is a weak
negative relationship between diversification & credit risk, a medium negative
relationship between diversification & cost efficiency and a weak positive relationship
between diversification and bank performance in both ROA and ROE models.
4.8
Regression Analysis
This paper has performed a multiple regression analysis as discussed in the previous
chapters for the data collected for five years from 2009 to 2013 to analyze the direct
and indirect effect of market structure and strategic choices; credit risk, cost
efficiency and diversification to the bank performance. The results obtained from the
analysis are given below.
As per the model summary table 04, in the model one R square is 0.419 which
indicates the explanatory power of the independent variables to the dependent
variable. It indicates that 42% variation of the performance of the banks as measured
using return on assets, is explained by the selected independent variables; market
structure, credit risk, cost efficiency and diversification. The model two is having the
R square of 0.435 and it indicates that the 44% variation of the performance of the
banks as measured using return on equity is explained by the independent variables
mentioned earlier.
34
The adjusted R square from model one and two respectively are 0.388 and 0.405
which indicate how far the independent variables will explain the dependent variable
when another variable is added to the model. Standard error of the estimate is simply
the standard deviation.
This explains how far the mean of the selected sample
deviates from the actual mean of the population. According to table 04, the standard
errors of the estimate respectively from two models are 0.004 and 0.056 which
represent a minimum value. That means the actual mean only have variance of 0.4%
from the sample mean in the model one, return on assets model and when it comes to
the model two 5.6% variance of sample mean from the actual mean.
Table 05: ANOVA Table
Model
ROE
F Value
14.43690
Significant Level
0.00000
ROA
13.52533
0.00000
The regression sum of square or explained sum of square explains how much
variability is accounted for by the regression model which is the fitting of the least
squares line. According to the results obtained from the regression models developed
in this paper it is found that that the regression-sum of square is 0.186 in the ROE
model and 0.0009 in the ROA model. Hence, it can be identified that the ROE model
is more reliable that ROA model since it has explained more variability. The residual
sum of square tells how much variability is unexplained for by the regression model
used. The residual sum of square of these models respectively in ROE and ROA
models are 0.241 and 0.0012.
Total sum of square is the summation of both
regression sum of square and residual sum of square. According to the results, it can
be identified that the percentage that can be explain by using the independent
variables is somewhat low in two models.
35
Degree of freedom of regression is four which is equal to the number of predictors in
the model, degree of freedom of residual is one hundred five which is the amount
obtained from deducting number of predictors and intercept from the number of total
observations. When it comes to the mean squares, those are arrived by dividing sum
of squares from the degree of freedom.
F value is the measure of the overall significance of the model that is obtained by
dividing the regression mean sum of square from the residual mean sum square. It is
found that the F value of ROE regression model is 14.437 and the significant level is
1% and ROA regression model is 13.525 and the significant level is 1%. So it can be
mentioned as the overall models are significant at 1% level.
The coefficient of each of the variable in the model with beta value and the standard
error value is mentioned in the coefficient table (Table 06). Regression model
coefficients matrix contain essential information for interpreting the regression
analysis. Because of the matrix includes the significant levels of the dependent and
independent variables of the model. The interpretation has indicated as below.
Table 06: Coefficients
Model
ROA – Constant
ROA
Beta
Std. error
t - Value
Significant
Level
0.02056
0.00510
4.03371
0.000
CR
-0.02123
0.00852
-2.49187
0.015
CEff
-0.01872
0.00297
-6.30916
0.000
MC
0.00189
0.00304
0.62171
0.536
DIV
-0.00052
0.00912
-0.05666
0.955
36
ROE – Constant
ROE
0.25941
0.07215
3.59525
0.001
CR
-0.40946
0.12061
-3.39482
0.001
CEff
-0.24521
0.04201
-5.83742
0.000
MC
0.07312
0.04308
1.69724
0.094
DIV
0.04466
0.12913
0.34585
0.730
CR - Constant
0.05183
0.00694
7.46929
0.000
-0.00270
0.04171
-0.06478
0.949
0.08291
0.03920
2.11478
0.038
-0.02067
0.09848
-0.20989
0.834
0.47714
0.00714
66.85931
0.000
-0.03575
0.04290
-0.83319
0.407
CR
MC
CEff - Constant
CEff
MC
DIV - Constant
DIV
MC
According to the above table (Table 06), in the ROA model the constant is 0.0206
which shows that the least square line touches the ordinate axis at a value of 0.0206
and in ROE model it is 0.259. Further it says that the given the value of independent
variables zero, the value of expected return on assets is 0.0206 and with relate to the
return on equity it is 0.259.
Beta in the un-standardized coefficient of each of the variable is the slope of those
variables. Further, it can be explained as in model one, for one unit of increase in the
independent variables; credit risk, cost efficiency and diversification the return on
assets that mean the performance of the banks has reduced by respectively by 0.0212,
0.0187 and 0.0005 whereas for one unit increase in the market concentration will
37
cause to increase the performance of the banks by 0.0018. According to the model
two, one unit of increase in credit risk and cost efficiency have caused to reduce the
performance of the bank which is calculated by using return on equity respectively by
0.409 and 0.245 whereas increase in the market concentration and diversification have
resulted in the increase in the return on equity correspondingly by 0.073 and 0.045.
According to the model three; one unit increase in the market concentration has
caused to decrease the credit risk by -0.0027 and model four; cost efficiency model
shows that one unit increase in the market concentration will decrease the cost
efficiency by 0.02067 and as per model five; diversification model, it is clear that one
unit increase in the market concentration will decrease the diversification by 0.03575.
Standard errors provide a measure of how much should expect the given the sample
coefficient to vary under the assumption of the null hypothesis. According to the
standard errors mentioned in the table (Table 06), correspondingly in model one and
model two, the credit risk was vary in the repeated sampling only 0.85 percent & 12
percent, cost efficiency was 0.29 percent & 4.2 percent, market concentration was
0.30 percent & 4.31 percent and diversification 0.91 percent & 12.91 percent.
The
results show that the standard errors are very smaller as it indicates smaller variance
in the repeated samples.
‘t–value’ indicates the individual significant to the regression model from the
independent variables. Credit risk is having absolute t-value of 2.492 in ROA model
and in ROE 3.395 in ROE model, which is significant at 1% level to the regression
model. The cost efficiency is having the absolute t-value of 6.309 in the ROA model
and 5.837 in the ROE model, where it is more than two which is the benchmark value
and it is significant at 1% level. When it comes to the market concentration, it is
having the absolute t-value respectively of 0.622 and 1.697 in ROA model and ROE
38
model. There in ROE model the t-value is closer 2 of benchmark value and it is
significant to the regression model at 10% level. The diversification variable is
having correspondingly in ROA model and in ROE model 0.057 and 0.346 of
absolute t-value that indicates lower value than the benchmark value and it is not
significant to the regression model.
In order to identify the direct and indirect effect of market concentration on each
strategy, the study has run a regression and identified the effect of market
concentration on risk taking strategy, cost efficiency strategy and diversification
strategy (Table 06) and again the study has run a regression to identify the direct
effect of market concentration on strategic choices (Credit risk, cost efficiency and
diversification) and then identify the indirect effects of market concentration on the
bank performance (Table 07). Even though the market structure is not significant to
the strategic choices model, there are negative effects of 0.0027, 0.0207 and 0.0358
respectively to the risk taking strategy, cost efficiency strategy and diversification
strategy from market concentration.
The summary of results from regression analysis and the conceptual framework with
the direct and indirect effects are given below.
Table 07: Summary of Causal Effects
Model
Direct Effect
Indirect Effect
Total Effect
MC – ROA
0.00187
-0.00001
0.00186
MC – ROE
0.07316
-0.00002
0.07314
MC – CR
-0.00270
0.00000
-0.00270
MC – CEff
-0.02067
0.00000
-0.02067
MC – DIV
-0.03575
0.00000
-0.03575
39
CR – ROA
-0.02123
0.00000
-0.02123
CR – ROE
-0.40946
0.00000
-0.40946
CEff – ROA
-0.01872
0.00000
-0.01872
CEff – ROE
-0.24521
0.00000
-0.24521
DIV – ROA
-0.00052
0.00000
-0.00052
DIV – ROE
0.04466
0.00000
0.04466
Market Structure
Strategic Choices
Bank Performance
Figure 02: Conceptual Framework with direct and indirect effect
4.9
Hypotheses Testing
H1 – Market Concentration positively affect to the bank performance
As per the analysis (Table 07), there is a positive effect of market concentration on
bank performance in both models; return on assets and return on equity respectively
0.00186 and 0.07314. Market concentration is not a significant variable in ROA
model, but it is a significant variable in the ROE model. Thus the results of the
40
analysis have caused to accept the alternative hypothesis based on the results obtained
from return on equity model.
The correlation table (Table 03) of the overall model shows that there is a positive
relationship (0.0717 and 0.1661) between market concentration and the performance
of the banks, which is arrived from assessing the relationship between HerfindahlHirschman Index and the return on assets and return on equity. To achieve the
objectives stated in the previous chapters it is important to identify the relationship
between the bank performance and the banks with low concentration, moderate
concentration and high concentration separately. The value below 0.1 represents the
low concentration, 0.1 to 0.18 indicates the moderate concentration and more than
0.18 shows the high concentration according to the index.
The following table (Table 08) shows the categorization of the banks in the selected
sample based on the market concentration.
Table 08: Categorization of banks based on HHI
Low
Concentration
Sampath Bank
Moderate
Concentration
Commercial Bank
High
Concentration
People's Bank
DFCC Wardhana Bank
Deutsche Bank
Hatton National Bank
Axis Bank
Seylan Bank
Nations Trust Bank
Habib Bank Limited
Pan Asia Bank
Bank of Ceylon
Standard Chartered Bank
Indian Bank
State Bank of India
Public Bank
41
From the analysis it was found (Table 09, 10 and 11) that there is a medium positive
relationship (-0.5677) between market concentration with low market concentration
and a weak positive relationship (0.3051) between market concentration with high
concentration and the bank performance whereas negative relationships between bank
performance and market concentration with moderate market concentration (-0.5427),
when the performance is measured using return on assets. The relationships with
return on equity show a medium positive relationship (0.6228) with low
concentration, a weak negative relationship (-0.4133) with medium concentration and
a weak positive relationship (0.1103) with high concentration.
H2 - Market Concentration negatively affect to the risk taking strategy
As per the regression analysis (Table 07), there is a negative effect (-0.0027) of the
market concentration on the risk taking strategy which is not significant and since
there is a negative effect, it has caused to reject the null hypothesis and accept the
alternative hypothesis developed using the previous literatures.
Further, this paper has identified the relationship of market concentration with low
HHI, Moderate HHI and high HHI with the risk taking strategy that means with the
credit risk. When it comes to the banks with low concentration (Table 09, 10 and 11),
there is a weak positive relationship of 0.1199 with credit risk. And also there was a
strong positive relationship which is 0.7719, between market concentration with
moderate HHI and the risk taking strategy of the banks. But with the high market
concentration, there is a negative relationship of 0.3691 (Table 11) between risk
taking strategy and market concentration.
In Sri Lankan context, with low and moderate market HHI, there is a positive
relationship between market concentration and the risk taking strategy because the
42
banks are not focusing mainly on few industries instead they are focusing on
developing industries such as tourism and agricultural industries. Therefore the credit
risk is somewhat high as if those industries are in a recession. But when there is a
high concentration, the credit risk is low because the banks provide the loans and
advances to the well-known customers.
Table 09: Correlations (Banks with low HHI)
ROA
ROE
ROA
1
ROE
0.993376
CR
CR
CEff
MC
1
-0.638338 -0.548652
1
CEff
0.592599
0.629520
0.029459
1
MC
0.567683
0.622828
0.119852
0.898853
DIV
DIV
1
-0.110637 -0.219580 -0.693234 -0.599590 -0.669748
1
Table 10: Correlations (Banks with moderate HHI)
ROA
ROE
CR
CEff
MC
DIV
ROA
1
ROE
0.637115
1
CR
-0.571563
-0.583318
1
CEff
-0.299130
-0.507041
0.469279
1
MC
-0.542698
-0.413270
0.771916
0.391291
1
DIV
0.322248
0.270456
-0.371209
-0.592071
-0.190561
43
1
Table 11: Correlations (Banks with high HHI)
ROA
ROE
CR
CEff
MS
DIV
ROA
1
ROE
0.745024
1
CR
0.011463
0.112076
1
CEff
-0.671017
-0.664229
-0.324505
1
MS
0.305085
0.110268
-0.369146
-0.354224
1
DIV
0.218385
0.352055
-0.086904
-0.355831
0.341865
1
H3 - Market Concentration negatively affect to the cost efficiency strategy
The table 07 emphasis there is a negative effect of market concentration on the cost
efficiency strategy which is significant (-0.02067) to the model and therefore the
alternative hypothesis also can be accepted since it is said that the market
concentration has a negative effect to the cost efficiency strategy.
According the correlations of the overall model (Table 03), there is a weak negative
relationship (-0.0237) between market concentration and the cost efficiency strategy
of the banks in Sri Lanka. Since it is not much accurate to consider all the banks in
the sample as one when there are different concentrations levels, this paper basically
identified three relationships between market concentration and cost efficiency
strategy. As per the study, the research has identified there is a significant positive
relationship (0.8989 – Table 09) between the banks with low concentration and the
cost efficiency strategy of those banks. The banks with moderate concentration also
show a weak positive relationship (0.3913) between the market concentration and cost
efficiency strategy (Table 10). The main reason for that is, when the bank is not
44
focusing more on a particular industry to provide the loans and advances then the
operating expenses have reduced where they should not follow up the customers to
pay the installments.
But for the banks with high concentration the relationship (Table 11) with the cost
efficiency is weak negative (-0.3542) because when the banks were focusing more on
a specific industry, the bank should pay more attention collect the loan installments
and the interest income since the banks are depending only on that particular industry.
Therefore the high level of market concentration negatively affect to the cost
efficiency strategy with relate to the Sri Lankan scenario whereas the banks with low
and medium concentration positively affect the cost efficiency strategy of the banks.
This has proven the established hypothesis in the past literatures.
H4 - Market Concentration negatively affect to the diversification strategy
As per the direct and indirect effects (Table 07), there is a negative effect of market
concentration to the diversification strategy (-0.03575) whereas it is not significant to
the model. Even though the effect is not significant, since there is a negative effect
the hypothesis can be accepted under this scenario.
The correlations (Table 03) show that there is a weak negative relationship (-0.0939)
between the market concentration and diversification strategy of the banks in Sri
Lanka. As it is not concern about the level of market concentration of the banks, this
paper has again identified the relationship between low, medium and high market
concentration with the diversification strategy of the banks in Sri Lanka using the
selected sample (Table 09, 10 and 11).
45
According to that analysis, there is a negative relationship between the banks with low
and medium market concentration and diversification strategy respectively -0.66975
of medium negative relationship and -0.1906 of weak negative relationship where it
proves that the market concentration has the negative effect on the diversification
strategy of the banks. But when it comes to the banks with high level of market
concentration, it is somewhat different because there is a medium positive relationship
of 0.3419 with the diversification strategy of the banks in Sri Lanka. But when
considering the overall relationship, that indicates a negative relationship between the
market concentration and the diversification strategy.
H5 – Risk taking strategy negatively affect bank performance
The results of the study (Table 07) show that there is a significant negative effect of
risk taking strategy on bank performance in both models; return on assets (-0.02123)
and return on equity (-0.40946). Thus the results of the analysis have caused to reject
the null hypothesis where it proves the hypothesis developed using the past literatures.
When it comes to the relationship between credit risk and bank performance, it shows
(Table 03) that there is a weak negative relationship between the risk taking strategy
of the banks in Sri Lanka and the performance of the banks. According to the model
one which is developed using the return on assets, it is -0.1667 and while with return
on equity, the relationship is -0.2585 where it rejects the null hypothesis and accepts
the alternative hypothesis.
H6 – Cost efficiency strategy positively affect bank performance
Here also there is a negative effect of cost efficiency on bank performance in both
return on assets and return on equity models respectively -0.01872 and -0.24521
46
(Table 07) which is significant and where the results have affected to reject the
alternative hypothesis developed using past literatures.
According to the results of the study it is found that there is a medium negative
relationship of -0.6042 and -0.5608 (Table 03) between the cost efficiency strategy of
the Sri Lankan banks and the performances of those banks as it is measured
correspondingly using return on assets and return on equity. Since most of the banks
in Sri Lanka are having low to moderate market concentration, that means they are
focusing on the new customers to offer the loans and advances and even though the
profitability has been increased the operating cost is also increased. Therefore the
cost efficiency is having a negative relationship with the bank performance.
Thereby, the hypothesis was rejected from the study.
H7 – Diversification strategy negatively affect bank performance
Diversification strategy is also having a negative effect on the bank performance in
return on assets (-0.00052) and a positive effect on performance in return on equity
(0.04466) model (Table 07). But the effects for both models are not significant.
Thus the effect of diversification for return on equity is higher than the effect on
return on assets; it is suitable to reject the alternative hypothesis.
The correlations (Table 03) of the overall model shows that there is a weak positive
relationship of 0.2966 and 0.3202 between the diversification strategy of the banks in
Sri Lanka and the performance of the banks when the performance is measured
respectively by using return on assets and return on equity. Therefore the hypothesis
is rejected according to the results of the analysis.
47
4.10 Chapter Summary
This chapter explained how the data was collected and analyzed using regression and
correlation. Then the results of the testing the ordinary least square assumptions
including the normality assumption and discussed the results of the descriptive
statistics, results of the correlations, regression analysis and finally tested the
hypothesis developed. The summary of the results obtained are given in the table
(Table 12) below.
Table 12: Summary of Results
Hypotheses
Accepted or
rejected
H1 – Market Concentration positively affect to the bank performance
Accept
H2 - Market Concentration negatively affect to the credit risk strategy
Accept
H3 - Market Concentration negatively affect to the cost efficiency
Accept
H4 - Market Concentration negatively affect to the diversification
Accept
H5 – Risk taking strategy negatively affect bank performance
Accept
H6 – Cost efficiency strategy positively affect bank performance
Reject
H7 – Diversification strategy negatively affect bank performance
Reject
48
CHAPTER V
SUMMARY AND CONCLUSION
5.1
Chapter Introduction
The purpose of this study was to develop and analysis a conceptual model of bank
performance based on two different approaches. The first one is based on the market
power theory that suggests the market structure or market concentration affects
performance of the banks and the second one refers to theory of strategic management
which considers the strategic choices such as risk taking strategy, cost efficiency and
diversification as the determinants of the performance of the banks.
5.2
Summary of Results
In order to fulfill the established objectives this paper has performed a regression
analysis and a correlation using several models. The conclusions relating to the
objectives will be discussed in this chapter.
Objective 01 – To measure the direct and indirect effect of market concentration on
the bank performance
The results of the study demonstrate that there is a positive effect of the market
concentration on the bank performance where it indicates an insignificant effect to the
return on assets while a significant positive impact to the return on equity. As in the
past studies (Mirzaei, Moore & Liu, 2001 and Belkhaoui, Lakhal, Faten and Hellara,
2014), there was a significant positive effect of the market concentration on the bank
performance. Also in contrast to the Sri Lankan banks, there is a positive effect
which is significant because increase in the market concentration will focus on the
specific customers who are well known and wealthy. Then the banks have the ability
49
to lend more money and earn more interest income from them rather than focusing on
poor people.
Objective 02 – To identify the effect of strategic choices (Credit risk, cost efficiency
and diversification) on bank performance
As per the findings there is a negative effect of the credit risk on the bank
performance in Sri Lanka, because when there are defaults of the lending by the bank
it is finally affect to the profitability of the banks. The past studies (Belkhaoui,
Lakhal, Faten and Hellara, 2014) were also proved that there is a negative effect of
the risk taking strategy on the bank performance. So the banks must continuously
comply with the rules and regulations given by the Central Bank of Sri Lanka and
maintain the required rates to manage the credit risk.
The results indicate that there is a negative impact of the cost efficiency strategy on
the bank performance where it is statistically insignificant and it has proven the past
studies. Therefore the management of the banks should improve the cost efficiency
by having the competitive advantage by decreasing the interest rates and improve the
financial stability of the banks within the industry.
As per the analysis the effect of diversification strategy on the bank performance is a
negative effect which is insignificant where in the past literatures also have proven.
Normally the assets base of the banks should have well diversified among the various
types of assets such as loans & advances, fixed assets and other non-interest bearing
assets etc. It is necessary to have the required amount of fixed assets to run the
operations of the banks and the loans and advances should also well diversify among
the various industries.
50
Objective 03 – To measure the relationship between market concentration and the
bank performance
To identify a clear relationship between market concentration and the performance of
the banks, the study has focused on three types of concentration which includes low,
medium and high concentration. According to the findings it is obvious that there is a
positive relationship with low concentration and high concentration where as a
negative relationship with the banks with medium concentration. When there is a low
concentration that means the banks are focusing on most of the industries in a similar
manner. Therefore the profitability of the banks decreases due to a larger customer
base with low interest loans advances and due to the high operating cost. When there
is a high concentration, which means the banks are focused more on specific
industries. So the operating expenses attached with given loans are low and the banks
have the ability to charge the higher interest rate on those loans.
Table 13: Relationship between market concentration and bank performance
Market Concentration
Relationship
Supporting Literature
Low Concentration
Positive
Mugume. A. ,2006
Medium Concentration
Negative
More and Marton, 2003
High Concentration
Positive
Jeon & Miller, 2005
Objective 04 –To measure the relationship between strategic choices and bank
performance
There is a negative relationship between credit risk and bank performance and also
with cost efficiency also there is a negative relationship. But when it comes to the
diversification the relationship shows a positive with the bank performances.
51
Objective 05 –To measure the relationship between market concentration and
strategic choices (Credit risk, cost efficiency and diversification)
When considers the Sri Lankan banking industry as a whole, there is a negative
relationship between the market concentration and the risk taking strategy of the
banks. Further this paper has identified the relationship between market concentration
and risk taking strategy by isolating the banks as low concentration, medium
concentration and high concentration. According to the findings it is clear that there
is a positive relationship between the banks with low and moderate concentration
whereas a negative relationship with the banks with high concentration. When the
market concentration of the banks is increasing then the credit risk for them is
decreasing. With high concentration, the banks can provide the loans and advances to
the known customers rather than giving to the unknown customers with low
concentration. Hence the credit risk is low with high concentration.
Table 14: Relationship between market concentration and risk taking strategy
Market Concentration
Relationship
Supporting Literature
Low Concentration
Positive
No
Medium Concentration
Positive
No
High Concentration
Negative
Belkhaoui, Lakhal, Faten and Hellara,
2014
As per the findings of the study there is a negative relationship between the bank
performance and the cost efficiency strategy as a whole. But when consider the banks
separately as low, medium and high market concentration the results are significantly
different from the overall conclusion. It is with low concentration, there is a positive
relationship between market concentration while there is a negative relationship
between moderate and high market concentration and performance of the banks.
52
When the market concentration is increasing the cost efficiency decreases whereas
when the market concentration is decreasing the cost efficiency also decrease. The
main reason for that is the higher operating expense involve with the loans and
advances given to the customers of the banks.
When there is a low market
concentration the number of loans is high and the operating cost is also high.
Table 15: Relationship between market concentration and cost efficiency
Market Concentration
Relationship
Supporting Literature
Low Concentration
Positive
No
Medium Concentration
Negative
No
High Concentration
Negative
Belkhaoui, Lakhal, Faten and Hellara,
2014
The results of the study show that there is a negative relationship between market
concentration and the diversification strategy as a whole.
When the sample is
dividing as the low, medium and high market concentration, it can be identified that
there is a negative relationship between the diversification strategy with low and
medium concentration whereas a positive relationship between diversification and
high market concentration.
Where the market concentration is increasing the
diversification is increasing and when the market concentration is decreasing the
diversification is increasing.
Table 16: Relationship between market concentration and diversification
Market Concentration
Low Concentration
Relationship
Negative
Supporting Literature
Belkhaoui, Lakhal, Faten and Hellara,
2014
Medium Concentration
Negative
Belkhaoui, Lakhal, Faten and Hellara,
2014
High Concentration
Positive
No
53
Objective 06 – To measure the effect of market concentration on strategic choices
(Credit risk, cost efficiency and diversification)
There is a direct effect of market concentration on strategic choices which are
negative but not significant.
That means, when the market concentration is
increasing, it is not significantly affect in decrease of the credit risk, cost efficiency
and diversification strategies. Because of the market concentration is not the only
factor that affects to the strategies followed by the banks in Sri Lanka.
5.3
Conclusion
Finally, the results of the study are very much important to the banks in Sri Lanka, the
managers of those banks and the regulatory bodies also. The banks are very much
encouraged to pay more attention on their strategic choices to increase their
performances. In addition to that the banks must comply with the rules, regulations
and standards to reduce the credit risk and increase the cost efficiency. However the
findings show that the increasing market concentration is beneficial to the banks in Sri
Lanka because it allows banks to reduce the operating cost and reduce the default risk
while increasing their performances.
54
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Axis Bank. (2009-2013). Annual Report. Axis Bank.
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Belkhaoui, Samir; Lassaad, Lakhal; Lakhal, Faten; Hellara, Slaheddin e;. (2014).
Market Structure, Strategic Choices and bank Perfrmance.
Central Bank. (2013). Annual Report. Sri Lanka: Central Bank Sri Lanka.
City Bank. (2009-2013). Annual Report. City Bank.
Commercial Bank. (2009-2013). Annual Report. Commercial bank.
Deutsche Bank. (2009-2013). Annual Report. Deutsche Bank.
DFCC Vardhana Bank. (2009-2013). Annual Bank. DFCC Vardhana Bank.
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Habib Bank Limited. (2009-2013). Annual Report. Habib Bank Limited.
Hatton National Bank . (2009-2013). Annual Report. Hatton National Bank .
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ICICI Bank Limited. (2009-2013). Annual Report. ICICI Bank Limited.
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Indian Oveseas Bank. (2009-2013). Annual Report. Indian Oveseas Bank.
Jeon, Y., & Miller, S. M. (2005). Bank Performance: Market Power or Efficient
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Maudos, Joaquin;. (1998). Market structure and performance in Spanish banking
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MCB Bank Limited. (2009-2013). Annual Report. MCB Bank Limited.
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Móré, C., & Nagy, M. (2003). Relationship Between Market Structure and Bank
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Mugume, Adam;. (2006). Market Structure and Performance in Uganda's Banking
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Muharram, A., Matthews, S., & Kent. (2009). Market Power versus EfficientStructure in Arab GCC Banking.
National Development Bank. (2009-2013). Annual Report. National Development
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Nations Trust Bank. (2009-2013). Annual Report. Nations Trust Bank.
Pan Asia Bank. (2009-2013). Annual Report. Pan Asia Bank.
People's Bank. (2009-2013). Annual Report. People's Bank.
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State Bank of India. (2009-2013). Annual Report. Standard Chartered Bank.
56
APPENDIXES
Data Set of the Analysis
Year
Bank
ROA
ROE
CR
CEff
MC
DIV
2009
Commercial Bank 0.0143
0.1583
0.0536
0.2980
0.0245
0.4134
2009
DFCC Wardhana 0.0106
0.0975
0.0808
0.4023
0.0045
0.4320
2009
HNB
0.0162
0.1957
0.0403
0.3408
0.0056
0.4153
2009
People's Bank
0.0076
0.1973
0.0670
0.2856
0.0094
0.4269
2009
Sampath Bank
0.0142
0.1941
0.0802
0.3202
0.0134
0.4384
2009
Deutsche Bank
0.0027
0.1419
0.0276
0.7465
0.2430
0.3709
2009
HBL
0.0160
0.1856
0.0979
0.3011
0.0541
0.4302
2009
BOC
0.0060
0.1285
0.0586
0.2467
0.0106
0.4005
2009
Indian Bank
0.0161
0.2026
0.0380
0.3049
0.0090
0.4828
2009
Seylan Bank
0.0038
0.0617
0.3352
0.3742
0.0389
0.4163
2009
NTB
0.0074
0.1236
0.1073
0.3149
0.0683
0.4024
2009
PAB
0.0191
0.2172
0.1004
0.2874
0.1487
0.3746
2009
Public Bank
0.0127
0.2200
0.0425
0.4025
0.0058
0.5438
2009
Standard Chatered 0.0080
0.1374
0.0084
0.6152
0.0068
0.4083
2009
State Bank of
India
0.0108
0.1705
0.0168
0.3196
0.0038
0.4407
2009
Axis Bank
0.0141
0.1913
0.0035
0.3472
0.0151
0.4724
2010
Commercial Bank 0.0160
0.1787
0.0308
0.3342
0.6280
0.4263
2010
DFCC Wardhana 0.0095
0.0924
0.0776
0.3673
0.0476
0.4491
57
2010
HNB
0.0150
0.1745
0.0293
0.3976
0.0020
0.4376
2010
People's Bank
0.0102
0.2696
0.0528
0.3407
0.0248
0.4828
2010
Sampath Bank
0.0194
0.2459
0.0390
0.4060
0.0032
0.4918
2010
Deutsche Bank
0.0014
0.0528
0.0192
0.8102
0.0032
0.3861
2010
HBL
0.0183
0.2040
0.1073
0.2990
0.2195
0.4332
2010
BOC
0.0102
0.2401
0.0339
0.2537
0.0058
0.4183
2010
Indian Bank
0.0168
0.2018
0.0189
0.3236
0.0328
0.4882
2010
Seylan Bank
0.0087
0.1084
0.2436
0.4710
0.0411
0.3978
2010
NTB
0.0131
0.1942
0.0692
0.3835
0.0081
0.4229
2010
PAB
0.0137
0.1519
0.0360
0.3885
0.0437
0.4604
2010
Public Bank
0.0162
0.2578
0.0507
0.1903
0.3240
0.5398
2010
Standard
Chartered Bank
0.0093
0.1322
0.0148
0.6684
0.0055
0.4061
2010
State Bank of
India
0.0091
0.1480
0.0172
0.3429
0.0047
0.4855
2010
Axis Bank
0.0153
0.1915
0.0036
0.4130
0.0010
0.4845
2011
Commercial Bank 0.0198
0.2076
0.0236
0.4319
0.0066
0.4265
2011
DFCC Wardhana
0.0141
Bank
0.1367
0.0467
0.3615
0.0115
0.5110
2011
HNB
0.0161
0.1731
0.0306
0.3535
0.0278
0.4515
2011
People's Bank
0.0168
0.4292
0.0357
0.2957
0.6539
0.5102
2011
Sampath Bank
0.0178
0.2260
0.0380
0.3386
0.0660
0.5194
2011
Deutsche Bank
0.0021
0.0824
0.0164
0.6687
0.0153
0.4006
58
2011
HBL
0.0213
0.2367
0.1123
0.2865
0.0456
0.4432
2011
BOC
0.0149
0.3374
0.0210
0.2368
0.0389
0.4848
2011
Indian Bank
0.0154
0.1927
0.0212
0.3323
0.0521
0.4922
2011
Seylan Bank
0.0064
0.0677
0.2504
0.4847
0.1507
0.4461
2011
NTB
0.0150
0.1972
0.0381
0.3687
0.0077
0.4515
2011
PAB
0.0211
0.2578
0.0257
0.3323
0.0859
0.4843
2011
Public Bank
0.0167
0.2494
0.0483
0.1731
0.0040
0.5519
2011
Standard
Chartered Bank
0.0088
0.1230
0.0112
0.5980
0.0114
0.3704
2011
State Bank of
India
0.0073
0.1262
0.0163
0.4123
0.0075
0.4757
2011
Axis Bank
0.0160
0.1934
0.0026
0.3945
0.0137
0.4861
2012
Commercial Bank 0.0212
0.2086
0.0165
0.2135
0.0062
0.5661
2012
DFCC Wardhana
0.0116
Bank
0.1248
0.0459
0.2359
0.0094
0.5340
2012
HNB
0.0187
0.1844
0.0370
0.2654
0.6064
0.5060
2012
People's Bank
0.0142
0.3912
0.0280
0.2292
0.0048
0.5813
2012
Sampath Bank
0.0186
0.2341
0.0233
0.2422
0.0072
0.5470
2012
Deutsche Bank
0.0001
0.0054
0.0226
0.9876
0.0010
0.4541
2012
HBL
0.0167
0.2104
0.1101
0.2588
0.0941
0.4968
2012
BOC
0.0153
0.3164
0.0168
0.1895
0.0439
0.4998
2012
Indian Bank
0.0133
0.1719
0.0529
0.2899
0.1986
0.5014
2012
Seylan Bank
0.0117
0.1123
0.1492
0.3208
0.0440
0.5087
59
2012
NTB
0.0161
0.2112
0.0250
0.3157
0.0376
0.4546
2012
PAB
0.0167
0.2194
0.0329
0.2559
0.0352
0.6164
2012
Public Bank
0.0173
0.2440
0.0348
0.1487
0.0198
0.5655
2012
Standard
Chartered Bank
0.0081
0.1140
0.0146
0.5968
0.0216
0.3978
2012
State Bank of
India
0.0091
0.1572
0.0210
0.3800
0.3357
0.5008
2012
Axis Bank
0.0161
0.2029
0.0025
0.3354
0.0049
0.4890
2013
Commercial Bank 0.0187
0.1840
0.0388
0.1988
0.0034
0.5285
2013
DFCC Wardhana
0.0090
Bank
0.0956
0.0472
0.2258
0.0343
0.5324
2013
HNB
0.0147
0.1432
0.0428
0.2272
0.0065
0.5327
2013
People's Bank
0.0083
0.2278
0.0530
0.1727
0.0044
0.5969
2013
Sampath Bank
0.0099
0.1282
0.0560
0.2286
0.0067
0.5523
2013
Deutsche Bank
0.0004
0.0125
0.0228
1.1091
0.0132
0.5556
2013
HBL
0.0138
0.1845
0.0859
0.2860
0.0369
0.4762
2013
BOC
0.0108
0.2225
0.0320
0.1858
0.3264
0.4529
2013
Indian Bank
0.0104
0.1389
0.0898
0.2787
0.0442
0.5076
2013
Seylan Bank
0.0116
0.1137
0.1202
0.2601
0.0758
0.4735
2013
NTB
0.0162
0.2127
0.0357
0.3245
0.0420
0.4520
2013
PAB
0.0019
0.0277
0.0650
0.2421
0.0056
0.5181
2013
Public Bank
0.0154
0.2079
0.0334
0.1640
0.0033
0.5697
60
2013
Standard
Chartered
0.0064
0.0904
0.0122
0.5794
0.6630
0.3992
2013
State Bank of
India
0.0097
0.1543
0.0182
0.3409
0.0038
0.5185
2013
Axis Bank
0.0165
0.1853
0.0032
0.3272
0.0431
0.4851
61