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This article was downloaded by: [University of Malaya]On: 31 August 2012, At: 10:35Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
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Sources of TFP growth in the Malaysian
Islamic banking sectorFadzlan Sufian
a
aKhazanah Research and Investment Strategy, Khazanah Nasional
Berhad, Level 35, Tower 2, Petronas Twin Towers Kuala LumpurCity Centre, 50088, Kuala Lumpur, Malaysia
Version of record first published: 04 Feb 2010
To cite this article:Fadzlan Sufian (2009): Sources of TFP growth in the Malaysian Islamic banking
sector, The Service Industries Journal, 29:9, 1273-1291
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Sources of TFP growth in the Malaysian Islamic banking sector
Fadzlan Sufian
Khazanah Research and Investment Strategy, Khazanah Nasional Berhad, Level 35, Tower 2,Petronas Twin Towers Kuala Lumpur City Centre, 50088 Kuala Lumpur, Malaysia
(Received 8 January 2008; final version received 11 January 2008)
This paper attempts to empirically analyse productivity changes of the MalaysianIslamic banking sector during the period of 2001 2004 by applying the non-parametric Malmquist productivity index method. During the period of study, theempirical findings suggest that the Malaysian Islamic banking sector has exhibitedproductivity progress during the earlier years before declining during the latter
years. The results suggest that foreign banks have exhibited higher productivitylevels compared with their domestic counterparts during the earlier years, while thedomestic banks productivity levels were relatively higher compared with theforeign banks during the latter years.
Keywords: Islamic bank productivity; Malmquist total factor productivity index(MPI); Malaysia
Introduction
In recent years, financial institutions have experienced a dynamic, fast-paced, and
competitive environment at a cross-border scale. One of the most productive areas isthe new paradigm of Islamic banking, which has remarkably captured the interest of
both Islamic and contemporary economists. A recent survey states that there are more
than 160 Islamic financial institutions around the world (Dar, 2003). Even though most
of the Islamic banks are within developing or Middle-East countries, many conventional
banks in developed countries have begun to valve the massive demand for Islamic finan-
cial products.
The main difference between the Islamic banks and the contemporary banks is that
while the latter is based on the conventional interest-based principle, the former follows
a principle of interest-free and profit and loss sharing (PLS) in performing their business
as intermediaries (Ariff, 1988). Many Islamic economic studies have discussed in depth
about the rationale behind the prohibition of interest (Chapra, 2000) and the importance
of PLS in Islamic banking (Dar & Presley, 2000). Furthermore, under the term of
Islamic PLS, the relationship between borrower, lender, and intermediary is rooted on
financial trust and partnership. The importance of the interest-free principle in Islamic
banking has created an innovative environment among practitioners in which the
alternative of interest is explored extensively. Dar (2003) classifies four types of finan-
cing that act as alternatives to interest: investment-based, sale-based, rent-based, and
service-based.
The existing research in Islamic banking and finance has focused primarily on the
conceptual issues underlying interest-free financing (Ahmed, 1981; Karsen, 1982).
ISSN 0264-2069 print/ISSN 1743-9507 online
# 2009 Taylor & Francis
DOI: 10.1080/02642060801911128
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Email: [email protected]
The Service Industries Journal
Vol. 29, No. 9, September 2009, 12731291
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These issues include the viability of Islamic banks and their ability to mobilise saving,
pool risks, and facilitate transactions. On the other hand, few studies have focused on
the policy implications of a financial system without interest payments (Khan & Mirakhor,
1987). What is noteworthy is that empirical work on the performance evaluation of Islamic
banks is sparse. The lack of complete data impeded any comprehensive analysis of the
experience of the last three decades. To date, empirical works done in this area of research
have yielded inconclusive results (Bashir, 1999; Bashir, Darrat, & Suliman, 1993).
The Malaysian banking system has a unique setting, where conventional banks are
allowed to offer Islamic banking and finance products along with the conventional
products. This dual banking system provides an interesting ground to investigate the effi-
ciency of domestic and foreign banks. As Malaysia is among the first countries in the
world that implement a dual banking system, this study would be among the first empirical
investigation to examine the productivity of domestic versus foreign banks that provide
Islamic banking services alongside the traditional conventional banking services.
By applying the non-parametric Malmquist productivity index (MPI) methodology, we
attempt to investigate the sources of productivity change of Malaysian Islamic banksduring the period of 20012004. The preferred methodology has allowed us to isolate
efforts to catch up to the frontier (efficiency change) from shifts in the frontier (techno-
logical change (TECHCH)). Also, the Malmquist index enables us to explore the main
sources of efficiency change: either improvements in management practices (pure
technical efficiency change) or improvements towards optimal size (scale efficiency
change). Finally, we performed a series of parametric and non-parametric tests to
examine whether the domestic and foreign banks were drawn from the same population.
The remainder of the paper is organised as follows. The second section provides some
background on the Islamic banking system in Malaysia, while the third section reviews the
related studies with respect to the Islamic banking industry. The fourth section describesthe data, sources, and model specification, which are employed in the study, and the
empirical results are presented in the following section. The conclusion is given in the
final section.
Background
In Malaysia, Islamic financing traces its root back to 1963, with the establishment of the
Pilgrims Fund Board or Lembaga Tabung Haji (LTH). The LTH introduced a savings
mechanism that enables Malaysian Muslims to save money to cover their costs of perform-
ing the annual pilgrimage. Money from the savings are invested in productive sectors of
the economy, which yield returns uncontaminated by riba.1
Malaysia, as a country dominated by Muslims, was affected by the resurgence that had
taken place in the Middle East. Many parties were calling for the establishment of an
Islamic bank in Malaysia. For example, in 1980, the Bumiputera Economic Congress
had proposed to the Malaysian Government to allow the setting up of an Islamic bank
in the country. Another effort was the setting up of the National Steering Committee in
1981 to undertake a study and make recommendations to the Government on all
aspects of the setting up of an Islamic bank in Malaysia, such as the legal, religious,
and operational aspects. The study concluded that the establishment of an Islamic bank
in Malaysia would be a viable project from the operations and profits point of views.
The conclusion was the establishment of the first Islamic bank in Malaysia known as
Bank Islam Malaysia Berhad (BIMB) in July 1983, with an initial paid-up capital of
RM80 million.
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The establishment of BIMB marked a new milestone for the development of the
Islamic financial system in Malaysia. BIMB carries out banking business similar to
other commercial banks, but along the principles ofSyariah. The bank offers deposit-
taking products such as current and savings deposit under the concept of Al-Wadiah
Yad Dhamanah (guaranteed custody) and investment deposits under the concept of
Al-Mudharabah (profit-sharing). The bank grants financing facilities such as working
capital financing under Al-Murabahah (cost-plus), house financing under Bai Bithaman
Ajil (deferred payment sale), leasing under Al-Ijarah (leasing), and project financing
underAl-Musyarakah (PLS).
It has been the aspiration of the government to create a vibrant and comprehensive
Islamic banking and finance system operating side-by-side with the conventional
system. A single Islamic bank does not fit the definition of a system. An Islamic
banking and finance system requires a large number of dynamic and pro-active players,
a wide range of products and innovative instruments, and a vibrant Islamic money
market. The first step in realising the vision was to disseminate Islamic banking on a
nationwide basis with as many players as possible and within the shortest period possible.This was achieved through the introduction of an Islamic Banking Scheme (IBS) or Skim
Perbankan Islam(SPI) in March 1993. The SPI allows conventional banking institutions
to offer Islamic banking products and services using their existing infrastructure, including
staff and branches. The scheme was launched on 4 March 1993 on a pilot basis involving
three banks. Following the successful implementation of the pilot run, Bank Negara
Malaysia (BNM) has allowed other commercial banks, finance companies, and merchant
banks to operate the scheme in July 1993 subject to the specific guidelines issued by the
central bank. From only three banks offering Islamic financing in March 1993, the number
of commercial banks that offered Islamic financing has increased to 15 (of which four are
foreign banks).The Islamic banking system, which forms the backbone of the Islamic financial
system, plays an important role in mobilising deposits and providing financing to facilitate
economic growth. The Malaysian Islamic banking system is currently represented by 15
banking institutions comprising nine domestic commercial banks, four foreign commer-
cial banks, and two Islamic banks that offer Islamic banking products and services
under the IBS. These Islamic banking institutions offer a broad range of Islamic financial
products and services such as savings, current and investment deposits, and financing pro-
ducts such as property financing, working capital financing, project financing, plant and
machinery financing, etc.
The ability of the Islamic banking institutions to arrange and offer products with attrac-
tive and innovative features at prices that are competitive with conventional products has
appealed to both Muslim and non-Muslim customers. This reflects that the Islamic banking
system, with its extensive distribution networks (numbering 152 full-fledged Islamic
banking branches and over 2000 Islamic banking counters), is effective as a financial inter-
mediator. Islamic banking has also spurred the efforts by other non-bank financial inter-
mediaries such as the development financial institutions, savings institutions, and
housing credit institutions to introduce Islamic schemes and instruments to meet their
customer demands.
Today, Malaysia has succeeded in implementing a dual banking system and has
emerged as among the first few nations to have a full-fledged Islamic banking system
operating side-by-side with the conventional banking system. Throughout the years,
Islamic banking has gained significance and has been on a progressive upward trend.
Since the year 2000, the Islamic banking industry has been growing at an average
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rate of 19% per annum in terms of assets. As at end-2004, total assets of the Islamic
banking sector increased to RM94.6 billion, which accounted for 10.5% of the total
assets in the banking system. The market share of Islamic deposits and financing
increased to 11.2% and 11.3% of the total banking sector deposits and financing,
respectively. The rapid progress of the domestic Islamic banking system, accentuated
by the significant expansion and development of Islamic banking and finance, has
become increasingly more important in meeting the changing requirements of the new
economy (BNM, 2004).
Related studies
Although there has been extensive literature examining the efficiency features of US
and European banking markets over recent years, the work on Islamic banking is
still in its infancy. Typically, studies on Islamic bank efficiency have focused on theor-
etical issues and the empirical work has relied mainly on the analysis of descriptive
statistics rather than rigorous statistical estimation (El-Gamal & Inanoglu, 2005).However, this is gradually changing as a number of recent studies have sought to
apply the approaches outlined above to estimate bank efficiency using various frontier
techniques.
Hussein (2003) provides an analysis of the cost-efficiency features of Islamic banks in
Sudan between 1990 and 2000. Using the stochastic cost frontier approach, he estimates
the cost efficiency for a sample of 17 banks over the period. The interesting contribution
of this paper is that specific definitions of Islamic financial products are used as outputs. In
addition, the analysis is also novel as Sudan has a banking system based entirely on Islamic
banking principles. The results show large variations in the cost efficiency of Sudanese
banks with the foreign-owned banks being the most efficient. State-owned banks are themost cost inefficient. The analysis is extended to examine the determinants of bank effi-
ciency. Here, he finds that smaller banks are more efficient than their larger counterparts.
In addition, banks that have higher proportion ofmusharakah and mudharabah finance
relative to total assets also have efficiency advantages. Overall, the substantial variability
in efficiency estimates is put down to various factors, not least the highly volatile
economic environment under which Sudanese banks have had to operate over the last
decade or so.
Hassan and Hussein (2003) examined the efficiency of the Sudanese banking system
during the period of 1992 and 2000. They applied a variety of parametric (cost and
profit efficiencies) and non-parametric DEA techniques to a panel of 17 Sudanese
banks. They found that the average cost and profit efficiencies under the parametric
approach were 55% and 50%, respectively, while it was 23% under the non-parametric
approach. During the period of study, they found that the Sudanese banking system
have exhibited 37% allocative efficiency and 60% technical efficiency, suggesting that
the overall cost inefficiency of the Sudanese Islamic banks were mainly due to technical
(managerially related) rather than allocative (regulatory).
El-Gamal and Inanoglu (2005) used the stochastic frontier approach to estimate the
cost efficiency of Turkish banks over the period 19902000. The study compared the
cost efficiencies of 49 conventional banks with four Islamic special finance houses
(SFHs). The Islamic firms comprised around 3% of the Turkish banking market.
Overall, they found that the Islamic financial institutions to be the most efficient and
this was explained by their emphasis on Islamic asset-based financing, which led to
lower non-performing loans ratios. It is worth mentioning that SFHs achieved high
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levels of efficiency despite being subjected to branching and other self-imposed con-
straints such as the inability to hold government bonds.
Despite the considerable development of the Islamic banking sector, studies focusing
on the efficiency of Islamic banks, particularly on the Malaysian Islamic banking industry
are still very limited. Several studies that have been devoted to assess the performance of
Islamic banks have generally examined the relationship between profitability and banking
characteristics. Samad and Hassan (1999) applied financial ratio analysis to investigate the
performance of a Malaysian Islamic bank over the period 1984 1997. Their results
suggest that, in general, the managements lack of knowledge was the main reason for
the slow growth of loans under the profit-sharing system. Despite that, the bank was
found to perform better compared with its conventional counterparts in terms of liquidity
and risk measurement (lower risks).
Methodology
Three different indices are frequently used to evaluate TECHCHs: the Fisher (1922),
Tornqvist (1936), and Malmquist (1953) indexes. According to Grifell-Tatje and Lovell
(1996), the Malmquist index has three main advantages relative to the Fischer and Tornq-
vist indices.2 First, it does not require the profit maximisation, or the cost minimisation,
assumption. Secondly, it does not require information on the input and output prices.
Finally, if the researcher has panel data, it allows the decomposition of productivity
changes into two components (technical efficiency change or catching up and technical
change or changes in the best practice). Its main disadvantage is the necessity to
compute the distance functions. However, the data envelopment analysis (DEA) technique
can be used to solve this problem.
Following Fare, Grosskopf, Norris, and Zhang (1994) among others, the output-orientedMalmquist productivity change index will be adopted for this study. Output orientationrefers
to the emphasis on the equi-proportionate increase of outputs, within the context of a given
level of input. The output-based Malmquist productivity change index may be formulated as:
Mt1j yt1;xt1;yt;xt
Dtj yt1;xt1
Dtj y
t;xt
Dt1j yt1;xt1
Dt1j y
t;xt
" #1=2(1)
whereMis the productivity of the most recent production point (xt 1, yt 1) relative to
the earlier production point (xt, yt) and Ds the output distance functions. Thus, a valuegreater than unity will indicate a positive factor productivity growth between two periods.
Following Fare et al. (1994), an equivalent way of writing this index is:
Mt1j yt1;xt1;yt;xt
Dt1j yt1;xt1
Dtjyt;xt
Dtjy
t1;xt1
Dt1j yt1;xt1
Dtjy
t;xt
Dt1j yt;xt
" #1=2(2)
In Equation (2), the ratio outside the brackets is equal to the change of technical effi-
ciency between time tand t 1. In other words, it represents the change in the relative
distance of the observed production from the maximum potential production. The com-
ponent inside the brackets of Equation (2) is the geometric mean of the two productivity
indexes and represents the shift in production technologies (technical change) between
time tand t 1.
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That is,
Technical efficiency (TE)Dt1j y
t1;xt1
Dtj yt;xt
(3)
Technological change (TECHCH) Dtjy
t1;xt1
Dt1j yt1;xt1
Dtjy
t;xt
Dt1j yt;xt
" #1=2(4)
Technical efficiency change (TE) in Equation (3) can be further decomposed as the
product of two components PTE change and scale efficiency change as follows
(Fare et al., 1994):
Dt1yt1;xt1
Dtyt;xt
Dt1j yt1;xt1
Dtjyt;xt
Dt1j yt1;xt1
Dtjyt;xt
Dtjyt;xt
Dt1j yt1;xt1" # (5)
The ratio outside the brackets in Equation (5) represents the pure technical efficiency
change, subject to a distance function (Dj) with variable returns to scale, between time t
and t 1 and is denoted by PECH hereafter. In other words,
Pure technical efficiency change (PEFFCH) Dt1 yt1;xt1
Dt yt;xt
(6)
The component inside the brackets of Equation (6) represents the effects of economies
of scale on productivity and is expressed as SECH which can be readily derived by divid-
ing TE of Equation (3) by PEFFCH of Equation (6) and would not involve its own com-
putations of additional distance functions. That is, scale efficiency change (SECH)
Scale efficiency change (SECH) TE
PEFFCH (7)
After incorporating Equations (5) (7) into Equation (2), we obtain the complete
decomposition of the MPI as follows:
MPI TE TECHCH
TECHCH PEFFCH SECH (8)
Another merit of defining the MPI using the output distance functions Dtis that the
MPI and its corresponding components (TE, TECHCH, PEFFCH, and SECH) are all cal-
culated in an index form and have a threshold value of one. In other words, if a derived
value is equal to one, it indicates that a banks performance remains unchanged in that
performance measure. A value of greater than one represents an improvement and a
value of less than one indicate a decline. The product of the index components of
TECHCH, PEFFCH, and SECH then amounts to the final MPI.
To determine the final MPI, a close examination of Equations (2) and (5) reveal
that we have to compute TECHCH, TE, and PEFFCH and then derive SECH by dividing
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TE by PEFFCH. Each output distance function corresponds to one particular output-oriented
DEA linear programme. Among TECHCH, TE, and PEFFCH, there are six output distance
functions, and thus, a total of six different DEA models have to be formulated and solved:
Dt1
yt1
;xt1
;Dt1
yt
;xt ;D
t
yt
;xt ;D
t
yt1
;xt1
;Dt1
j yt1
;xt1
;Dt
j yt
;xt
(9)
To illustrate, assume that there are N financial institutions and that each varying
amounts ofKdifferent inputs to produce Mdifferent outputs. Thejth financial institutions
is therefore represented by the vectorsxjyjand the K Ninput matrixXand the M N
output matrixYrepresent the data of all financial institutions in the sample. In other words,
xjis the input combinations for bankj, whereasyjis the output combinations for bankj.3
The purpose is to construct a non-parametric envelopment frontier over the data points
such that all observed points lie on or below the production frontier. The calculations
exploit the fact that the input distance functions, D, used to construct the Malmquist
index are the reciprocals of Farrell (1957) output orientation technical efficiency measures.The convexity constraintNil = 1 is introduced in Equations (10) (13) to assume variable
returns to scale. By solving the equations with the same data under constant returns to scale
and variable returns to scale, measures of overall technical efficiency, TE, and pure tech-
nical efficiency, PTE, are obtained. Hence, dividing the overall technical efficiency, TE,
by pure technical efficiency, PTE, yields a measure of scale efficiency, SE
Dtjyt;xt1 maxu;l u
s.t.yjt Ytl 0
uxjt Xtl 0l 0
10
Dt1j yt1;xt11 maxu;l u
s.t.yjt1 Yt1l 0
uxjt1 Xt1l 0
l 0
11
Dt1j yt;xt1 maxu;l u
s.t.yjt Yt1l 0
uxjt Xt1l 0
l 0
12
Dtjyt1;xt11 maxu;l u
s.t.yjt1 Ytl 0
uxjt1 Xtl 0
l 0
13
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Data sample, inputs outputs definition, and the choice of variables
For the empirical analysis, all Malaysian conventional banks that offered Islamic banking
window services were incorporated in the study. The annual balance sheets and income
statements used to construct the variables for the empirical analysis were taken from pub-
lished balance sheet information in annual reports of each individual bank.
The definition and measurement of inputs and outputs in the banking function remains
a contentious issue among researchers. To determine what constitutes inputs and outputs
of banks, one should first decide on the nature of banking technology. In the banking
theory literature, there are two main approaches competing with each other in this
regard: the production and intermediation approaches (Sealey & Lindley, 1977).
Under the production approach, a financial institution is defined as a producer of ser-
vices for account holders; that is, they perform transactions on deposit accounts and
process documents such as loans. Hence, according to this approach, the number of
accounts or its related transactions is the best measure for output, while the number of
employees and physical capital is considered as inputs. Previous studies that adopted
this approach are by Sherman and Gold (1985), Ferrier and Lovell (1990), and Fried,
Lovell, and Eeckaut (1993) among others.
The intermediation approach on the other hand assumes that financial firms act as an inter-
mediary between savers and borrowers and posits total loans and securities as outputs,
whereas deposits along with labour and physical capital are defined as inputs. Previous
banking efficiency studies that adopted this approach are, among others, Charnes, Cooper,
Huang, and Sun (1990), Bhattacharya, Lovell, and Sahay (1997), and Sathye (2001).
For the purpose of this study, a variation of the intermediation approach or asset
approach originally developed by Sealey and Lindley (1977) will be adopted in the defi-
nition of inputs and outputs used.4 According to Berger and Humphrey (1997), the pro-
duction approach may be more suitable for branch efficiency studies, as at most timesbank branches basically process customer documents and bank funding, while investment
decisions are mostly not under the control of branches.
The aim in the choice of variables for this study is to provide a parsimonious model and
to avoid the use of unnecessary variables that may reduce the degree of freedom. All vari-
ables are measured in millions of Ringgit (RM). We model Malaysian Islamic banks as
multi-product firms producing two outputs by employing three inputs. Accordingly, we
assume Malaysian Islamic banks produce total loans (y1) and income (y2) by employing
total deposits (x1), labour (x2), and fixed assets (x3). Data for the empirical analysis are
sourced from individual banks IBS annual balance sheet and income statements.5
Table 1 presents the summary of statistics for the outputs and inputs for MalaysianIslamic banking operations. A few conclusions can be drawn. First, over the 4-year
period, total assets of Malaysian Islamic banking operations grew by about 71% to
RM4.82 trillion in 2004 from RM2.82 trillion in 2001. Secondly, it is apparent that
there has been increasing awareness among the Malaysian public about Islamic banking
and finance during this period, substantiated by the growth in total loans (financing) to
the domestic economy and deposits from the Malaysian public in the same period.
During the years (20012004), total loans and deposits grew by about 115% and by
about 79%, respectively. Thirdly, conclusion could also be made about employment in
the Islamic banking industry during this period. It is clear from Table 1 that the Malaysian
Islamic banking and finance industry has created significant employment for the period.
As data on the number of employees are not readily made available, we use personnel
expenses as a proxy measure. From Table 1 it is apparent that personnel expenses have
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expanded by 108% during the 4-year period. Finally, the Islamic banking and finance
industry has increasingly generated awesome returns to Malaysian Islamic banks.
During the period of study, we have witnessed more than 122% increase in the mean
income of Malaysian Islamic banks, from a mere RM87, 122.43 billion in 2001 to
RM193,769.33 billion in 2004.
Results
In this section, we will discuss the productivity change of the Malaysian Islamic banking
industry, measured by the MPI, and assign the changes in total factor productivity change
(TFPCH) to technological change (TECHCH) and efficiency change (EFFCH). We also
attempt to attribute any change in EFFCH to changes in pure technical efficiency
(PEFFCH) and/or scale efficiency (SECH). The summary of annual means of TFPCH,
TECHCH, EFFCH, and its decomposition into PEFFCH and SECH for the years
20012004 is presented in Table 2. Because 2001 is the reference year, the Malmquist
TFPCH index and its components take an initial score of 1.000 for 2001. Hence, any
score greater (lower) than 1.000 in subsequent years indicates an improvement
(worsening) in the relevant measures. Annual values of the indices for the industry and
each Malaysian Islamic banks sub-group are provided in Tables 25.
Table 1. Descriptive statistics for inputs and outputs.
2001 (RMb) 2002 (RMb) 2003 (RMb) 2004 (RMb)
OutputsTotal loans (y1)
Minimum 26,377 20,796 17,096 12,023Mean 1,441,734.71 1,873,301 2,499,915.20 3,094,485.80Maximum 6,409,411 8,253,532 11,703,438 14,581,517Standard deviation 1,937,174.37 2,442,768.01 3,263,292.70 3,868,114.68
Income (y2)Minimum 3407 3961 5917 10,802Mean 87,122.43 107,506.93 159,752.20 193,769.33Maximum 431,401 490,847 571,711 611,655Standard deviation 127,206.77 153,407.31 166,571.12 193,355.08
InputsTotal deposits (x1)
Minimum 79,679 62,266 97,797 627,564Mean 2,384,403.93 3,117,977.21 3,726,400.40 4,269,593.13Maximum 9,064,966 12,166,584 12,577,435 15,965,833Standard deviation 3,019,347.63 3,833,396.16 4,094,701.14 4,510,658.40
Labour (x2)Minimum 389 743 895 653Mean 7737.71 8703.93 14,726.2 16,115.47Maximum 72,398 75,172 88,137 93,865Standard deviation 18,798.22 19,579.20 26,396.60 27,972.43
Assets (x3)Minimum 140,156 93,056 150,511 834,447
Mean 2,817,694.50 3,512,071.79 4,381,516.13 4,821,954.73Maximum 10,358,576 13,204,458 15,578,265 15,578,265Standard deviation 3,415,938.21 4,222,744.81 4,757,408.56 4,570,657.78
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Table 2. TFPCH of Malaysian Islamic banking sector all banks.
EFFCH TECHCH PEFFCH SECH TFPCH
Panel A (2001 2002)Affin Bank Berhad 0.978 1.348 1.000 0.978 1.319
Alliance Bank Berhad 0.677 1.227 0.717 0.944 0.831Arab-Malaysian Bank Berhad 0.600 1.219 0.689 0.871 0.732EON Bank Berhad 0.893 1.151 0.922 0.968 1.027Hong Leong Bank Berhad 1.067 1.438 1.051 1.015 1.535Maybank Berhad 1.000 1.122 1.000 1.000 1.122Public Bank Berhad 0.842 1.286 1.000 0.842 1.082RHB Bank Berhad 0.886 1.018 0.929 0.953 0.901Southern Bank Berhad 1.222 1.129 1.290 0.947 1.380Standard Chartered Bank Berhad 1.443 1.296 1.000 1.443 1.870Hong Kong Bank Berhad 1.000 1.040 1.000 1.000 1.040OCBC Bank Berhad 0.623 1.136 0.586 1.062 0.708Citibank Berhad 1.000 1.211 1.000 1.000 1.211
Bank Islam Malaysia Berhad 0.750 1.301 1.000 0.750 0.976Geometric mean 0.901 1.203 0.925 0.974 1.084Maximum 1.443 1.438 1.290 1.443 1.870Minimum 0.600 1.018 0.586 0.750 0.708Standard deviation 0.231 0.118 0.175 0.155 0.321
Panel B (2002 2003)Affin Bank Berhad 1.022 1.138 1.000 1.022 1.164Alliance Bank Berhad 0.831 1.341 0.819 1.015 1.114Arab-Malaysian Bank Berhad 1.448 0.947 1.267 1.142 1.371EON Bank Berhad 1.228 1.096 1.084 1.133 1.346Hong Leong Bank Berhad 1.000 1.236 1.000 1.000 1.236
Maybank Berhad 1.000 1.229 1.000 1.000 1.229Public Bank Berhad 1.156 0.962 1.000 1.156 1.111RHB Bank Berhad 0.996 1.216 1.141 0.873 1.211Southern Bank Berhad 1.080 0.941 0.919 1.175 1.017Standard Chartered Bank Berhad 0.741 0.939 0.576 1.285 0.695Hong Kong Bank Berhad 0.946 0.992 0.970 0.975 0.938OCBC Bank Berhad 0.973 1.330 1.356 0.717 1.293Citibank Berhad 1.000 1.029 1.000 1.000 1.029Bank Islam Malaysia Berhad 1.106 0.926 1.000 1.106 1.025
Geometric mean 1.025 1.085 0.992 1.033 1.112Maximum 1.448 1.341 1.356 1.285 1.371Minimum 0.741 0.926 0.576 0.717 0.695Standard deviation 0.170 0.152 0.185 0.141 0.180
Panel C (2003 2004)Affin Bank Berhad 0.911 0.793 0.989 0.921 0.722Alliance Bank Berhad 2.537 0.994 3.910 0.649 2.521Arab-Malaysian Bank Berhad 0.926 0.947 1.199 0.772 0.877EON Bank Berhad 1.000 0.984 1.000 1.000 0.984Hong Leong Bank Berhad 1.000 0.858 1.000 1.000 0.858Maybank Berhad 1.000 1.111 1.000 1.000 1.111Public Bank Berhad 0.963 0.878 1.000 0.963 0.845RHB Bank Berhad 1.451 0.974 1.178 1.232 1.413Southern Bank Berhad 1.015 0.915 1.249 0.813 0.928Standard Chartered Bank Berhad 0.512 0.913 1.735 0.295 0.468
(Continued)
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Total factor productivity growth of Malaysian Islamic banks
As depicted in Panels AC of Table 2, the Malmquist results suggest that during theperiod of 2001 2004, Malaysian Islamic banks have exhibited TFPCH progress in
years 2002 and 2003 before declining in year 2004. With respect to year 2001, the
average TFPCH increase was 8.4% in year 2002, increasing to 11.2% in year 2003
before exhibiting 4.6% TFPCH regress in year 2004. During the years 2002 and 2003,
TFPCH progress of the Malaysian Islamic banks was mainly due to TECHCH, which
increased by 20.3% and 8.5%, respectively. On the other hand, the decline in the Malay-
sian Islamic banks TFPCH during the year 2004 was mainly due to the decline in
TECHCH of 6.7% during that year. The empirical evidence seems to suggest that the
Malaysian Islamic banks have exhibited 9.9% EFFCH decrease in 2002 before increasing
by 2.5% in 2003. From Table 2 it is apparent that the Malaysian Islamic banks TECHCHdeclined by 6.7% in 2004; however, they have continued to record positive EFFCH of
2.3% during the year, albeit lower compared with the level recorded in 2003. The
decomposition of the EFFCH index into its PEFFCH and SECH components suggest
that the dominant source of the decrease in Malaysian Islamic banks EFFCH during
the year 2002 was managerially related rather than scale-related, implying that the Malay-
sian Islamic banks were less efficient in controlling their costs during the years, rather than
operating at the wrong scale of operations. Similarly, the results suggest that SECH has
largely led to the increase in Malaysian Islamic banks efficiency during the year 2003.
During the year, the SECH of Malaysian Islamic banks increased by 3.3% while the
PEFFCH declined by 0.8%. In contrast, during the year 2004 the results suggest that
Malaysian Islamic banks have exhibited 22.0% decline in the SECH, which was offset
by the 26.6% increase in PEFFCH during the year.
Panels AC of Table 3 present the results for the Malaysian domestic Islamic banks
(DOM_BNKS). As observed, the DOM_BNKS have exhibited TFPCH progress during
all years, 7.5% in 2002 relative to 2001, increasing strongly to exhibit 18.5% TFPCH pro-
gress in 2003 relative to 2002 before declining markedly to record 6.6% increase in
TFPCH in 2004 relative to 2003. The decomposition of the TFPCH index into its
TECHCH and EFFCH components suggest that the decline in the DOM_BNKS TFPCH
in 2004 was largely a result of the decline in TECHCH of 6.3% during the year. In contrast,
the strong increase in the DOM_BNKS TFPCH in 2003 was also a result of the strong
increase in TECHCH, which increased by 24.7%. The results thus suggest that like theTFPCH index, the DOM_BNKS TECHCH index also follow an inverted U-shaped beha-
viour during the period of our study. The decomposition of the EFFCH index into its
Table 2. Continued.
EFFCH TECHCH PEFFCH SECH TFPCH
Hong Kong Bank Berhad 1.026 0.967 1.031 0.995 0.992OCBC Bank Berhad 2.065 1.016 2.039 1.013 2.098Citibank Berhad 0.329 0.856 1.000 0.329 0.282Bank Islam Malaysia Berhad 1.266 0.896 1.000 1.266 1.134
Geometric mean 1.023 0.933 1.258 0.813 0.954Maximum 2.537 1.111 3.910 1.266 2.521Minimum 0.329 0.793 0.989 0.295 0.282Standard deviation 0.568 0.080 0.794 0.287 0.592
Note: EFFCH, efficiency change; TECHCH, technological change; PEFFCH, pure technical efficiency change;SECH, scale efficiency change; TFPCH, total factor productivity change.
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Table 3. TFPCH of Malaysian Islamic banking sector domestic banks.
EFFCH TECHCH PEFFCH SECH TFPCH
Panel A (2001 2002)Affin Bank Berhad 0.978 1.333 1.000 0.978 1.304
Alliance Bank Berhad 0.730 1.104 1.000 0.730 0.805Arab-Malaysian Bank Berhad 0.717 1.069 0.745 0.963 0.767EON Bank Berhad 0.936 1.089 0.955 0.980 1.019Hong Leong Bank Berhad 1.064 1.416 1.000 1.064 1.506Maybank Berhad 1.000 1.110 1.000 1.000 1.110Public Bank Berhad 1.000 1.181 1.000 1.000 1.181RHB Bank Berhad 0.930 0.997 0.901 1.032 0.928Southern Bank Berhad 1.225 1.150 1.006 1.219 1.409Bank Islam Malaysia Berhad 0.921 1.059 1.000 0.921 0.975
Geometric mean 0.939 1.145 0.957 0.982 1.075Maximum 1.225 1.416 1.006 1.219 1.506Minimum 0.717 0.997 0.745 0.730 0.767
Standard deviation 0.149 0.129 0.083 0.122 0.249
Panel B (2002 2003)Affin Bank Berhad 1.022 1.138 1.000 1.022 1.164Alliance Bank Berhad 0.725 1.521 1.000 0.725 1.103Arab-Malaysian Bank Berhad 1.223 1.138 1.340 0.913 1.392EON Bank Berhad 1.069 1.282 1.047 1.021 1.370Hong Leong Bank Berhad 1.000 1.244 1.000 1.000 1.244Maybank Berhad 1.000 1.233 1.000 1.000 1.233Public Bank Berhad 1.000 1.165 1.000 1.000 1.165RHB Bank Berhad 0.916 1.320 1.120 0.818 1.209Southern Bank Berhad 0.854 1.177 1.000 0.854 1.006
Bank Islam Malaysia Berhad 0.791 1.302 1.000 0.791 1.030
Geometric mean 0.950 1.247 1.046 0.908 1.185Maximum 1.223 1.521 1.340 1.022 1.392Minimum 0.725 1.138 1.000 0.725 1.006Standard deviation 0.144 0.115 0.109 0.110 0.128
Panel C (2003 2004)Affin Bank Berhad 0.911 0.793 1.000 0.911 0.722Alliance Bank Berhad 2.537 0.995 1.000 2.537 2.525Arab-Malaysian Bank Berhad 0.916 0.957 1.001 0.914 0.877EON Bank Berhad 1.000 0.985 1.000 1.000 0.985
Hong Leong Bank Berhad 1.000 0.858 1.000 1.000 0.858Maybank Berhad 1.000 1.111 1.000 1.000 1.111Public Bank Berhad 0.937 0.910 1.000 0.937 0.852RHB Bank Berhad 1.451 0.974 1.178 1.232 1.413Southern Bank Berhad 1.002 0.924 1.000 1.002 0.926Bank Islam Malaysia Berhad 1.266 0.896 1.000 1.266 1.134
Geometric mean 1.138 0.937 1.017 1.120 1.066Maximum 2.537 1.111 1.178 2.537 2.525Minimum 0.911 0.793 1.000 0.911 0.722Standard deviation 0.500 0.086 0.056 0.492 0.524
Note: EFFCH, efficiency change; TECHCH, technological change; PEFFCH, pure technical efficiency change;
SECH, scale efficiency change; TFPCH, total factor productivity change.
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PEFFCH and SECH components suggest that the dominant source of the decrease in the
DOM_BNKS EFFCH in 2002 was purely technically related, whereas on the other handthe decline in the DOM_BNKS efficiency in 2003 was scale-related rather than manage-
rially related. Similarly, the results suggest that SECH has largely resulted in the increase
Table 4. TFPCH of Malaysian Islamic banking sector domestic banks (ex-full-fledgedIslamic banks.
EFFCH TECHCH PEFFCH SECH TFPCH
Panel A (2001 2002)
Affin Bank Berhad 0.978 1.333 1.000 0.978 1.304Alliance Bank Berhad 0.730 1.104 1.000 0.730 0.805Arab-Malaysian Bank Berhad 0.717 1.069 0.745 0.963 0.767EON Bank Berhad 0.936 1.089 0.955 0.980 1.019Hong Leong Bank Berhad 1.064 1.416 1.000 1.064 1.506Maybank Berhad 1.000 1.110 1.000 1.000 1.110Public Bank Berhad 1.000 1.189 1.000 1.000 1.189RHB Bank Berhad 0.930 0.997 0.901 1.032 0.928Southern Bank Berhad 1.223 1.151 1.006 1.216 1.407
Geometric mean 0.941 1.156 0.952 0.988 1.088Maximum 1.223 1.416 1.006 1.216 1.506Minimum 0.717 0.997 0.745 0.730 0.767
Standard deviation 0.157 0.133 0.086 0.126 0.260
Panel B (2002 2003)Affin Bank Berhad 1.022 1.138 1.000 1.022 1.164Alliance Bank Berhad 0.725 1.521 1.000 0.725 1.103Arab-Malaysian Bank Berhad 1.223 1.138 1.340 0.913 1.392EON Bank Berhad 1.069 1.282 1.047 1.021 1.370Hong Leong Bank Berhad 1.000 1.244 1.000 1.000 1.244Maybank Berhad 1.000 1.233 1.000 1.000 1.233Public Bank Berhad 1.000 1.165 1.000 1.000 1.165RHB Bank Berhad 0.916 1.320 1.132 0.809 1.209Southern Bank Berhad 0.854 1.177 1.000 0.854 1.006
Geometric mean 0.970 1.242 1.053 0.921 1.204Maximum 1.223 1.521 1.340 1.022 1.392Minimum 0.725 1.138 1.000 0.725 1.006Standard deviation 0.139 0.121 0.115 0.108 0.121
Panel C (2003 2004)Affin Bank Berhad 0.911 0.793 1.000 0.911 0.722Alliance Bank Berhad 2.537 0.995 1.000 2.537 2.525Arab-Malaysian Bank Berhad 0.916 0.957 1.001 0.914 0.877EON Bank Berhad 1.000 0.985 1.000 1.000 0.985Hong Leong Bank Berhad 1.000 0.858 1.000 1.000 0.858Maybank Berhad 1.000 1.111 1.000 1.000 1.111
Public Bank Berhad 0.937 0.910 1.000 0.937 0.852RHB Bank Berhad 1.451 0.974 1.165 1.246 1.413Southern Bank Berhad 1.002 0.924 1.000 1.002 0.926
Geometric mean 1.125 0.941 1.017 1.106 1.059Maximum 2.537 1.111 1.165 2.537 2.525Minimum 0.911 0.793 1.000 0.911 0.722Standard deviation 0.529 0.090 0.055 0.522 0.556
Note: EFFCH, efficiency change; TECHCH, technological change; PEFFCH, pure technical efficiency change;SECH, scale efficiency change; TFPCH, total factor productivity change.
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in the DOM_BNKS EFFCH during the year 2004. In the same year, the DOM_BNKS
SECH increased by 12.0% and the PEFFCH increased by 1.7%.
To further check for the robustness of our results, we have also examined the results of
domestic Malaysian Islamic banks (DOM_BNKS) excluding the full-fledged Islamic banks
(DOM_X_BNKS). The results are presented in Panels A C of Table 4. Similar to
the results for the DOM_BNKS, during the period of study, the results suggest that
DOM_X_BNKS have exhibited TFPCH progress during all years albeit higher. The
results from Panels AC of Table 4 suggest that the DOM_X_BANKS have exhibited
8.8% TFPCH growth in 2002 relative to 2001, 20.4% progress in 2003 relative to 2002
and 5.9% growth in 2004 relative to 2003. Again, similar to the results for the domestic
Malaysian Islamic banks, the decomposition of the TFPCH index into its TECHCH and
EFFCH components suggest that the DOM_X_BNKS TFPCH growth during the years
2002 and 2003 was largely attributed to TECHCH, while EFFCH, which increased by
12.5%, has resulted in the TFPCH progress in 2004. It is apparent that the exclusion of
the full-fledged Malaysian Islamic banks has resulted in higher TECHCH during the
years 2002 and 2004. The results of the decomposition of the DOM_X_BNKS EFFCH
Table 5. TFPCH of Malaysian Islamic banking sector foreign banks.
EFFCH TECHCH PEFFCH SECH TFPCH
Panel A (2001 2002)Standard Chartered Bank Berhad 1.443 1.296 1.000 1.443 1.870Hong Kong Bank Berhad 1.000 1.040 1.000 1.000 1.040OCBC Bank Berhad 0.905 1.168 1.000 0.905 1.057Citibank Berhad 1.000 1.211 1.000 1.000 1.211
Geometric mean 1.069 1.175 1.000 1.069 1.256Maximum 1.443 1.296 1.000 1.443 1.870Minimum 0.905 1.040 1.000 0.905 1.040Standard deviation 0.242 0.107 0.000 0.242 0.391
Panel B (2002 2003)Standard Chartered Bank Berhad 0.823 0.887 0.695 1.184 0.730Hong Kong Bank Berhad 1.000 0.890 1.000 1.000 0.890OCBC Bank Berhad 1.105 1.418 1.000 1.105 1.567Citibank Berhad 1.000 1.011 1.000 1.000 1.011
Geometric mean 0.977 1.031 0.913 1.069 1.007
Maximum 1.105 1.418 1.000 1.184 1.567Minimum 0.823 0.887 0.695 1.000 0.730Standard deviation 0.117 0.251 0.153 0.089 0.364
Panel C (2003 2004)Standard Chartered Bank Berhad 0.578 0.994 1.438 0.402 0.574Hong Kong Bank Berhad 1.000 1.279 1.000 1.000 1.279OCBC Bank Berhad 1.000 1.696 1.000 1.000 1.696Citibank Berhad 0.470 1.041 1.000 0.470 0.489
Geometric mean 0.722 1.224 1.095 0.659 0.883Maximum 1.000 1.696 1.438 1.000 1.696Minimum 0.470 0.994 1.000 0.402 0.489
Standard deviation 0.278 0.321 0.219 0.327 0.579
Note: EFFCH, efficiency change; TECHCH, technological change; PEFFCH, pure technical efficiency change;SECH, scale efficiency change; TFPCH, total factor productivity change.
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into its PEFFCH and SECH components suggest that the exclusion of the full-fledged
Malaysian Islamic banks has resulted in higher SECH during the years 2002 and 2003.
On the other hand, PEFFCH seems to have declined in 2002, increased in 2003, and
remained the same in 2004.
The results for the foreign Islamic banks (FOR_BNKS) are presented in Panels AC
of Table 5. As observed, during the period of study the FOR_BNKS TFPCH was on a
declining trend, exhibiting TFPCH progress of 25.6% in 2002 before declining substan-
tially to exhibit TFPCH increase of only 0.7% in 2003 relative to 2002. It is also apparent
from Panel C of Table 5 that the FOR_BNKS have exhibited 11.6% TFPCH regress in
2004. The decomposition of the TFPCH index into its TECHCH and EFFCH components
suggest that the decline in the FOR_BNKS TFPCH in 2004 was largely attributed to the
decline in EFFCH of 27.8% during the year. Unlike the DOM_BNKS, the results suggest
that EFFCH has largely resulted in the increase in the FOR_BNKS TFPCH in 2002 and
2003. The FOR_BNKS TFPCH regress during the year 2004 was also the result of the
decline in EFFCH. The decomposition of the EFFCH index into its PEFFCH and
SECH components suggest that the dominant source of the decrease in the FOR_BNKSEFFCH in 2003 was managerially related, whereas on the other hand the decline in the
FOR_BNKS efficiency in 2004 was scale-related rather than managerially related. Simi-
larly, the results suggest that SECH has largely resulted in the increase in the FOR_BNKS
EFFCH during the year 2002. During the year 2002, the FOR_BNKS SECH increased by
6.9% while the PEFFCH was stagnant.
Univariate tests
After examining the Malmquist results, the issue of interest now is whether the two samples
were drawn from the same population and whether the domestic and foreign banks possessthe same technology. The null hypothesis tested was that the domestic banks and foreign
banks were drawn from the same population or environment. We tested the null hypothesis
that the domestic and foreign banks were drawn from the same population and have identical
technologies by using a series of parametric (ANOVA and t-test) and non-parametric
(KolmogorovSmirnov, Mann Whitney (Wilcoxon Rank-Sum), and Kruskall Wallis)
tests. Based on most of the results presented in Table 6, we failed to reject the null hypothesis
at the 0.05 levels of significance that the domestic banks and foreign banks were drawn from
the same population and have identical technologies. This implies that there is no significant
difference between the domestic and foreign banks technologies (frontiers) and that it is
appropriate to construct a combined frontier. Furthermore, the results from Levenes test
for equality of variances do not reject the null hypothesis that the variances among domestic
banks and foreign banks were equal, implying that we could assume the variances among
domestic and foreign banks to be equal. Our findings corroborate with those by, among
others, Sathye (2001) and Isik and Hassan (2002).
Conclusion and directions for future research
This paper attempts to investigate the productivity changes of Malaysian Islamic banks
during the period of 20012004, by applying a non-parametric MPI method. The preferred
methodology has allowed us to isolate efforts to catch up to the frontier (efficiency change)
from shifts in the frontier (technological change). Also, the Malmquist index enables us to
explore the main sources of efficiency change: either improvements in management practices
(PTE change) or improvements towards optimal size (scale efficiency change). Additionally,
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Table 6. Summary of parametric and non-parametric tests for the null hypothesis that domestic banks (db) and foreign b(frontiers).
Test groups
Parametric test Non-parametric
Individual tests Analysis of variance(ANOVA) test
t-test KolmogorovSmirnov (K S)test
MannWhitneyRank-Sum
Hypotheses Meandb= meanfb Distributiondb= distributionfb Mediandb= mTest statistics F(p . F) T(p . t) K S (p . KS) z(p .
Productivity change(TFPCH)
0.101 (0.752) 0.318 (0.752) 0.342 (1.000) 20.168 (0
Technological change(TECHCH)
0.598 (0.282) 0.531 (0.598) 0.586 (0.883) 20.445 (0
Efficiency change(EFFCH)
0.820 (0.053) 0.229 (0.820) 0.488 (0.971) 20.088 (
Pure technical efficiencychange (PEFFCH)
0.533 (0.395) 0.628 (0.533) 0.537 (0.936) 20.084 (
Scale efficiency change(SECH)
0.590 (0.295) 0.543 (0.526) 0.683 (0.739) 20.571 (
Note: Test methodology follows among others, Aly, Grabowski, Pasurka, and Rangan (1990), Elyasiani and Mehdian (1992), and Isik antest) and non-parametric (KolmogorovSmirnov, MannWhitney, and KruskallWallis) tests test the null hypothesis that the domestic
efficiency population (environment).The numbers in parentheses are the p-values associated with the relative test.
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we have also performed a series of parametric and non-parametric tests to examine whether
the domestic and foreign banks were drawn from the same set of population.
Our results suggest that Malaysian Islamic banks productivity have exhibited an
inverted U-shaped behaviour during the period of our study. The Malaysian Islamic
banks have exhibited 8.4% productivity progress in year 2002, increasing to record the
highest productivity change of 11.2% in 2003, before declining to record 4.6% pro-
ductivity regress in 2004. Our results suggest that the domestic banks have exhibited
higher productivity growth compared with their foreign counterparts. The decomposition
of the productivity change index suggests that Malaysian Islamic banks productivity pro-
gress was mainly attributable to technological change rather than efficiency change during
the years 2002 and 2003, whereas the opposite was true during the year 2004 when the
results suggest that Malaysian Islamic banks have exhibited higher efficiency change.
Further decomposition of the efficiency change index into its pure technical and scale effi-
ciency components suggests that during the period of study pure technical efficiency has
largely resulted in an increase in the Malaysian Islamic banks efficiency. However, the
results may have to be interpreted with caution as Malaysian Islamic banks were foundto have exhibited pure technical efficiency decline in 2000 and 2003 before increasing
strongly in 2004, which has eliminated the negative effects of 2002 and 2003.
Further, to address the issue whether the domestic and foreign banks were drawn from
the same sample of population or environment, or whether the domestic and foreign banks
have the same technological (frontiers) attribution, we have performed a series of para-
metric and non-parametric tests. Our results from the parametric and non-parametric
tests could not reject the null hypotheses at the 0.05 levels of significance that the domestic
and foreign banks were drawn from the same population or environment, suggesting that it
is appropriate to construct a single frontier for both the domestic and foreign banks.
The general conclusion that can be drawn from the findings is that, in recent years, thefull-fledged Islamic banks seems to have under-performed their window-based Islamic
banking peers, due to sub-optimal scale of operations. The principal findings for the
period under study indicate that technical efficiency scores are improving more for the
conventional banks offering Islamic banking products and services than for the full-
fledged Islamic banks. Thus, the results suggest that for the full-fledged Islamic bank to
be efficient, they need to reduce their size. The results are generally consistent with
earlier studies, which have found that the larger banks tend to be less efficient.
The emergence of two foreign banks, i.e. Citibank and Hong Kong Bank, as the global
leaders may be mainly explained by (1) advantages gained from their long-term involvement
in the Malaysian banking sector, (2) their ability to mobilise Islamic banking funds from the
Middle East (due to their wide international presence), and (3) their dynamism and innova-
tiveness in introducing and promoting new Islamic banking and finance products, to meet
domestic needs. Foreign banks are also considered to possess inherent economies of scale,
as a direct extension of their other international operations and so are capable of competing
with the incumbent domestic banks. From the policy-making perspective, the results may
imply that the opening up of the Islamic banking sector to the entry of foreign banks as an
important measure in the on-going process of efficiency improvement and innovation, as
well as increasing globalisation of the Malaysian financial system.
Due to its limitations, the paper could be extended in a variety of ways. Further analy-
sis into the investigation of Malaysian Islamic banks productivity is suggested to consider
the risk exposure factors. To establish overall Islamic banks performance, risk exposure
factors should be taken into consideration along with the productive efficiency measures.
The best banks may not necessarily be the most efficient producer of loans, but also ones
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that balances high efficiency with low risk assumptions. Investigation of changes in the
efficiency changes over time by employing the DEA method could yet be another exten-
sion to the paper. Future research into the efficiency and productivity of Malaysian Islamic
banks could also consider the production function along with the intermediation function.
Despite these limitations, the findings of this study are expected to contribute signifi-
cantly to the existing knowledge on the operating performance of the Malaysian Islamic
banking industry. Nevertheless, the study has also provided further insight into the
banks specific management style as well as the policymakers in regard to attaining
optimal utilisation of capacities, improvement in managerial expertise, efficient allocation
of scarce resources, and most productive scale of operation of the banks in the industry. This
may facilitate directions for sustainable competitiveness of future Islamic banking oper-
ations in Malaysia.
Notes
1. Riba, the English translation of which isusury, is prohibited in Islam and is acknowledged by allMuslims. The prohibition ofriba is clearly mentioned in the Quran, the Islams holy book andthe traditions of Prophet Muhammad (sunnah). The Quran states: Believers! Do not consumeriba, doubling and redoubling. . . (3.130); God has made buying and selling lawful and ribaunlawful. . . (2:274).
2. The Malmquist total factor productivity index was not invented by Malmquist. In his paper(Malmquist, 1953), he brought input functions of distance into an analysis of consumption, devel-oping a method for the empirical measurement of standard of living. The change in livingstandards is defined as the ratio of two input functions of distance. Before the Malmquistpaper, the input function of distance was brought into a paper by Debreu (1951), and theoutput function of distance was introduced by Shephard in his book (Shephard, 1953). Thenatural development of their papers was the definition of the index of change of total factor
productivity as the ratio of two input or output functions of distance. Some 31 years had topass before it arrived. The Malmquist index of change in total factor productivity was proposedin a paper for the first time in Caves, Christensen, and Diewert (1982) Today, these indices areentitled partially oriented indices of change in total factor productivity. In the case of productiontechnology that satisfies the constant yields axiom, the indices are the same.
3. For easy understanding, the study denotes byj,y, andx to represents a particular bankj, outputsand inputs, respectively. In other words, it denotes the possible combinations of outputs andinputs for a particular bankj at time tand t 1.
4. Humphrey (1985) presents an extended discussion of the alternative approaches of what a bankproduces.
5. Only data from IBS accounts are used. Malaysian conventional banks offering Islamic bankingwindow services are required to maintain a separate IBS account. Hence, the data used are not
contaminated with the conventional banking operations.
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