Title
Efficiencies of Islamic Banks vis-à-vis Domestic Conventional Banks during 2008-2015: Empirical
Evidence from Bangladesh
Abdus Samad, Ph.D.
Professor of Economics
Department of Finance and Economics
Utah Valley University
500 West University PKY
Orem, UT 84058
USA
Phone: 801-863-8368
Fax: 801-863-7218
Submitted for presentation to the 13th Asian Business Research Conference to be held in Dhaka,
Bangladesh on December 25th -26th, 2015
Abstract
This paper first estimates the various efficiencies of all domestic private banks of Bangladesh during
2008-2012. The efficiencies estimated by Data Envelopment Analysis (DEA) are the pure technical
efficiency (PTE), Technical efficiency (TE) and scale efficiency. Second, the efficiencies, PTE, TE, and SE of
the domestic private conventional banks (DCONBK) are compared with those of the Islamic banks of
Bangladesh. This study finds: (i) larger percentage of the Islamic banks were more efficient in all three
efficiencies—PTE, TE, and SE—than the conventional banks in loan financing and operating income. (ii)
Whereas the average PTE, TE, and SE of Islamic banks, in general, was higher than the national average
of all domestic private banks, the average of the conventional banks was below the national average
efficiency. (iii) All parametric tests (ANOVA, Welch F-test, t-test, and Satterthwaite Welch t-test) reject,
in general, the null hypothesis of equality of mean efficiency between the Islamic banks and the
conventional banks suggesting that the Islamic banks’ efficiency, PTE, TE and SE, was significantly higher
than that of conventional banks during 2008-2012.
JEL Classification: G21; G28
Key Words: Bank efficiency, commercial Bank, DEA, Bangladesh
1. Introduction
The examination bank efficiency is important from both microeconomic and Macroeconomic points of
view (Berger and Mester, 1997). From a microeconomic perspective, the study of bank efficiency is
important due to the increase in competition in the banking sector. The competition in the Bangladesh
banking industry is enhanced not only due to the entering of foreign banks but also due the increase in
the number domestic banks. The growing economy of Bangldesh opens the door of more conventional.
As a result, competition among banks in Bangladesh has enhanced.
From a macroeconomic point of view, the efficiency of banks affects the structure and stability of the
whole financial system (Rossi et al. 2005). The inefficiency of banks increases the cost of intermediation
and harms the allocation of funds and the profitability of bank leading bank failure (Samad, 2014). The
increased efficiency of banks in deposits mobilization and loans advancing is a key to successful
entrepreneur for enhancing the economic growth of a country (Schumpeter, 1911).
The efficiency of the productivity of banks including Islamic banks is of great interest to public
authorities supervising and regulating banks, bank managements and bank depositors and borrowers.
Each of them is interested to know the productive efficiency of banks. In a competitive market
environment, bank depositors and borrowers are certainly interested to know the efficiency status of
individual bank before they deposit their hard earned savings. The borrowers of bank move to the banks
which are more efficient in advancing loans.
The efficiency study of Bangladesh banking is important for several reasons. First, there are tremendous
growth of banks and financial institutions in Bangladesh. When Bangladesh was born in 1971, there was
no private bank. The five banks that Bangladesh inherited from Pakistan at the time of liberation were
Sonali Bank, Rupali Bank, Janata Bank, Agrani Bank, and Pubali bank. These banks were nationalized by
the-then government of Bangladesh and became the public sector banks. When the privatization policy
was introduced in 1982, there was just one private domestic bank (Pubali Bank) in Bangladesh.
Currently, there are there are forty one private banks excluding four government owned banks
Second, the banking industry of Bangladesh is dominated by conflicting groups of banks and there are
strong competitions among them for market share. The conflicting groups of bank that are competing
are the government owned (public) banks verses privately owned banks, foreign banks verses domestic
banks, and interest based conventional banks verses interest free Islamic banks. Out of forty five banks,
four banks are owned by the government of Bangladesh, eleven banks are foreign banks and thirty
banks are private domestic banks. Out of thirty private domestic banks, seven are Islamic banks
operating side by side with thirty privately owned domestic banks in Bangladesh. Among privately
owned domestic banks there are seven Islamic banks and the rest of the commercial banks are interest
based conventional banks. Thus, the banking industry of Bangladesh is dominated by four types of
commercial banks: (i) Bangladesh government owned banks (ii) domestic conventional banks (iii)
domestic Islamic banks, and (iv) foreign banks. The commercial banks of Bangladesh from each group
are individually competing for deposits and loans market share.
Third, the operation of Islamic banks is a new phenomenon compared to that of conventional banks.
Conventional banks are centuries old. They have long experience of portfolio managements, deposit
mobilizations, and loan financing compared to those of Islamic banks.
Fourth, the review of literature shows that there is no extensive study of efficiency of conventional
banks vis-à-vis Islamic banks for an extended period of five years. Unlike the previous efficiency studies
by Samad (2015A 2015B, 2009) which focused only on the technical efficiency (TE) efficiency and only on
year 2010, this study focused on the examination of pure technical efficiency (PTE), technical efficiency
(TE), and scale efficiency (SE). This study is extended to cover five years during 2008-2012.
The paper is organized as: Section 2 provides the review of literature. Data, methodology, and
specification of variables are described in Section 3. Empirical results and conclusions are provided in
Section 4.
2. Review of Literature
The literature of bank efficiency studies in the US and Europe is large. A few of them can be cited as
Berger and Humphery (1992), Berger and Humphery (1997), Aly et al (1990), Barr et al (2002), Merger
and Mester (2003), Casu and Girardone (2002), and Andries and Cocris (2010).
However, the number of bank efficiency studies covering less developed countries is limited, and for the
banking systems of Southeast Asian countries, including Bangladesh, such studies are almost nonexistent.
El-gamal and Inanoglu (2004) estimated the comparative cost efficiency of the Turkish banks for the
period 1990-2000 using the data envelopment analysis (DEA) method. They found that the Islamic banks
were more efficient due to Islamic banks’ asset-based financing.
Samad (2004) compared the performance of Islamic banks and conventional commercial banks of
Bahrain with respect to (a) profitability, (b) liquidity, and (c) capital management. A comparison of
eleven financial ratios for the period 1991-2001 found that there was no difference in profitability and
liquidity performance between Islamic and conventional banks for that period.
There were two important studies for the Malaysian banking sector. Sufian and Majid (2006)
investigated the comparative efficiency of the foreign and domestic banks of Malaysia during 20012005. They found that banks’ scale inefficiency dominated pure technical efficiency during the period.
They also found that the foreign banks had higher technical efficiency than the domestic banks. Sufian
(2009) estimated the various efficiencies and the determinants of these efficiencies. His studies found
that the efficiencies were negatively related to bank expenses and economic conditions, while the
efficiencies were positively related to loan intensity.
There has been some analysis of bank efficiency in India. For the most part, these types of analyses
have used financial indicators for measuring bank efficiency as in the articles by Rammohan and Roy
(2004) and Sarkar et al. (1998). Rammohan and Roy found that public sector banks are more efficient
than the private sector banks in India. In another study, Kumbhakar and Sarkar (2003) used a cost
efficiency approach for measuring bank efficiency and also concluded that private sector banks had
higher levels of efficiency contrasted to public sector banks in that country.
Another group of Indian scholars has used the DEA approach in measuring bank efficiency, including
Saha and Ravishankar (2000), Bhattacharyya et al. (1997) and Sanjeev (2006). Bhattacharyya et al.
(1997) determined in their study that public sector banks were the best performing banks in India during
the late 1980s and early 1990s. Shanmugam and Das (2004) used a stochastic frontier analysis (SFA)
process for measuring technical efficiencies of Indian commercial banks and found that a group of state
banks were more efficient than a comparable group of foreign banks during a period from 1992-1999.
Andries and Cocris (2010) analyzed the comparative efficiency of banks in several southern European
countries during the period of 2000-2006 using both DEA and SFA analytic processes. They found that
the banks in Romania, the Czech Republic, and Hungary all operated at relatively low levels of technical
efficiency.
Samad has done several evaluations of the Bangladesh banking system. Samad’s (2009) review of
technical efficiency using data for 2000 found that the average efficiency of those banks was 69.6.
However, this study focused on the TE only for the year2000.
Samad (2007) also examined the comparative performance of foreign banks verses domestic banks in
Bangladesh using various financial ratios of bank performance and found no difference in profit
performance between domestic banks and foreign banks in the period 2000-2001. In yet another
analysis, Samad (2010) estimated the technical efficiency of Grameen bank micro-financing activities in
Bangladesh as developed by Nobel Laureate, Dr. Muhammad Yunus.
Samad (2013) investigated the efficiency of Islamic banks using the time varying Stochastic Frontier
function on the Islamic banks of 16 countries. Mean efficiencies between the pre global financial crisis
and the post global crisis were estimated at 39 and 38 percent respectively and the difference was not
statistically significant.
The current analysis is different from the previous studies (Samad 2009, 2010, 2013) in several ways.
First, this study is extended to cover five years during 2008-2012, not just the one year. Second, this
study focuses to estimate the pure technical efficiency (PTE), technical efficiency (TE), and scale
efficiency (SE), not just the TE. Third, this study concentrates in estimating the efficiencies of
intermediary approach, value-added approach, and operating approach, not just the efficiencies of
intermediary approach.
3. Data, Methodology, and Specification of Variables
3.1 Data
This study covers the period 2008-2012. Thirty domestic private banks are considered. The input and out
data for all variables—loans, deposits, net income (profits), labors, and capitals of each bank—were
obtained from Bank-Insurance and Financial Institutions Activities published by the Division of Banks and
Financial Institutions of the Ministry of Finance, Government of Bangladesh. The value of variables is in
local currency and in million except labor. Table A, in Appendix 1, provides the descriptive statistics of
the input and output used in this study
3.2 Methodology
In the first stage, Data Envelopment Analysis (DEA) method is used to estimate the various efficiencies
such as PTE, TE, and SE of all domestic private banks including Islamic banks. In the second stage,
parametric tests such as t-test, ANOVA, Welch F-test, and Satterthwaite Welch t-test are performed in
determining whether there are any significant differences in the efficiencies between the domestic
conventional banks and the Islamic banks.
There are important methodologies for obtaining the efficiencies of any decision making unit (DMU)
such as bank:
(i) Stochastic frontier function/method (SFM) developed by Aigner, Lovell, and Schmidt (1977) and later
refined by Pitt and Lee (1981) and Batties and Colie (1992). The SFM is a parametric approach.
(ii) Data Envelope Analysis (DEA) method. DEA is a linear programming and a non-parametric method.
Originally the method was proposed by Farrell (1957) but the method did not get wide attention until
the DEA was first used by Charnes, Cooper, and Rhodes (CCR) (1978). The model proposed by CCR
assumed constant returns to scale (CRS). Under the CCR model, DEA was used to measure the efficiency
of each DMU as the maximum ratio of weighted outputs to weighted inputs. The CCR model
presupposes no significant relationship between scale efficiency (SE) of operation and technical
efficiency (TE) under the assumption of CRS and thus provides the overall technical efficiency (OTE) also
called allocative/economic efficiency.
The CRS assumption is not justifiable because all DMUs do not operate at optimum scale. Firms
or DMUs may operate under economies of scale (i.e. increasing returns to scale, IRS) or diseconomies of
scale (i.e. decreasing returns to scale, DRS). So, the estimated measure of TE under the assumption of
optimum scale (CRS) is contaminated with scale efficiencies. This leads to the extension of another DEA
model by Banker, Charnes, and Cooper (BCC) (1984) in which variable returns to scale (VRS) was
assumed to estimate the efficiency of DMUs. The VRS assumption of BCC model provides the measures
of pure technical efficiency (PTE) which is a measure of TE devoid of scale efficiency (SE) effect. Thus,
scale inefficiency of a DMU occurs when PTE score of a DMU is not equal to TE score.
This paper applies BCC (1984) DEA method in estimating the efficiencies of DMU. The BCC inputoutput model which is estimated in this paper to evaluate the relative to frontier is:
max z = 𝑢𝑢j
v, y
1
Subject to vxj =1, - v X + u Y≤ 0, v ≥ 0, u ≥ 0, u j free from sign, where a set of observed DMUs { DMUj;
j= 1, 2, …….n}; xj, yi input and output vectors; row vector u, v output and input multipliers; and X and Y
input and output matrices. Note that the goal of input oriented DEA model is minimize the use of input,
relative to virtual output given condition that no DMU can operate beyond the production possibility
frontier and the constraints of non-negative weights.
Using the duality in linear programming, as the most DEA program is a dual form, one can write
the above (1) in an envelopment which can simplify the burden of calculation as:
min θ
ø, λ
(2)
Subject to θ is a scalar and λ is a I x I semi-positive vector of constraint, θxj – Xλ ≥ 0, Yλ≥ yj. The value of
θ obtained is the efficiency score of the i-th DMU. It satisfies: θ ≤ 1, with a value of 1 indicating a point
on the frontier and is thus technically efficient firm/DMU, according to Farrell (1957).
The efficiency score, θ (PTE), TE, and SE of each DMU (each bank) obtained is presented in the
empirical section.
Once the efficiencies, PTE, TE, and SE were obtained, comparisons of efficiencies between the
conventional banks and the Islamic banks were also performed. Results are provided in the empirical
section in Tables 5, 6, and 7
3.3 Specification of Variables
The physical measures of output and input are distinct in many industries. For examples, in agriculture,
the output is paddy, wheat or com and is measured in tons or kg. Inputs are land, labor, and capital. In
electricity, the output is kilowatt-hours of electricity. Inputs are the number of workers and the value of
electric generators
There is no agreement in the physical measures of output in the banking sector. Banks are multi-product
firms and produce a variety of products and services as loans to customers, safekeeping, intermediation,
and accounting services for deposits (Benston and Smith, 1976). Some have argued that a bank's
primary product is loans. From an asset point of view, the production of deposit services is essentially
viewed as inputs which are used to make loans (Sealey and Lindley, 1977).
There are four approaches found in the literature. (i) Intermediation approach, (ii) Production approach,
(iii) Operating approach, and (iv) value added approach.
Intermediate approach suggests that banks primarily act as an intermediary between savers (lender)
and borrowers, i.e. banks collect deposits from the savers and provides loans to the borrowers. In this
approach, loans and advances are considered as outputs of banks whereas labor, capital and deposits
are considered as inputs.
In the production approach (Benston 1965), a bank is defined a producer of variety of services for bank
account holders i.e. a bank performs transactions on deposit accounts (deposit, withdrawal,
safekeeping) and loan accounts (processing loans, letter of credits). In this approach, the number of
accounts or the number of transaction related to them is best measure of output whereas labor and
capital are considered as inputs.
In the operative approach, banks are viewed as financial units with primary objective to generate
maximum income with the expenditures of the business unit (Leightner and Lovel 1998). So, in this
approach a bank’s income is output and the costs incurred to generate revenue are the inputs of banks.
The value added approach is the most recent one used by Drake et al. (2006). In the value added
approach, load and deposits are considered as output because they are the significant components of a
bank’ value added.
Lack of transaction data, this paper uses the intermediate approach, the value added approach, and the
operative approach in estimating the efficiencies of banks in Bangladesh.
4. Empirical Results
[Insert Table 1 ]
First, Table 1 shows that the average (μ) PTEs of banks in loan financing was 0.93, 0.98, 0.90, 0.83, and
0.94 during 2008-2012 respectively. This result suggests that the average redundancy of inputs were
seven percent, two percent, ten percent, and six percent in 2008, 2009, 2010, 2011, and 2012
respectively. Banks could easily operate on the efficient frontier without incurring these percentages of
resources.
On the other hand, the TEs of banks were 0.83, 0.98, 0.87, 0.82, and 0.91 during 2008-2012 respectively.
Second, bank efficiencies increased during 2008 and 2009. The number of efficient banks, represented
by ø, was high, five and nine, during 2008 and 2009 respectively and then declined in the subsequent
years.
Third, the results show that almost all banks operate under excess capacity, i.e. DRS. The number of
efficient banks operating at the lowest cost of production (CRS) i.e. neither on IRS or DRS was 1, 4, 2, 1,
and 0 during 2008-2012 respectively.
[Insert Table 2]
Table 2 shows that the average (μ) PTEs of banks in value-added (loan-deposit) approach during 20082012 was 0.91, 0.92, 0.89, 0.90, and 0.88 respectively. The PTE increased during 2000 and 2009.
The efficiency (PTE) result indicates that the average redundancy of inputs, which banks could avoid and
still maintained the same production, was 9 percent, 8 percent, 11 percent, 10 percent, and 12 percent
during 2008-2012 respectively.
The TEs of banks during 2008-2012 were 0.87, 0.87, 0.83, 0.84, and 0.81 respectively. The comparison of
efficiency between PTE and TE shows that the average PTE was higher than the TE of the banks during
2008-2012.
The result of SE suggests that almost all of the banks in Bangladesh were operating under DRS i.e. they
had excess capacity. The number of scale efficient banks, i.e. banks operating at CRS , was only 1, 1, 0, 2,
and 0 during 2008-2012 respectively.
[Insert Table 3]
Table 3 shows that the average PTE ( μ) of the domestic private banks of Bangladesh was 0.93, 0.94,
0.91, 0.92, and 0.86 during 2008-2012 respectively. The PTE result indicates that banks’ average
redundancy of inputs, which banks could avoid and still maintained the highest output, was 7 percent, 6
percent, 9 percent, 8 percent, and 14 percent during the same period 2008-2012 respectively.
The result of TE shows that the average TE of the domestic private banks of Bangladesh was 88 percent,
89 percent, 88 percent, 83 percent, and 83 percent during 2008-2012 respectively. The comparison of
efficiency between PTE and TE shows that the average PTE was higher than the TE of banks during 20082012.
SE efficiency results shows almost all of the banks in Bangladesh were operating under DRS i.e. they had
excess capacity. The number of scale efficient banks, i.e. banks operating at CRS, was only 1, 1, and 2
during 2008-2010 respectively. There was no scale efficient bank during 2011-2012.
[Insert Table 4]
Table 4 shows that the average PTE of the Islamic banks is higher than the average PTE of all domestic
private banks (Conventional and Islamic). While the average efficiency of all domestic private banks
were 94 percent, 99 percent, 91 percent, 84 percent, and 94 percent during 2008, 2009, 2010, 2011, and
2012 respectively, the Islamic banks’ average efficiency (PTE) was 96 percent, 99 percent, 97 percent, 91
percent, and 95 percent. On the other hand, the conventional banks’ average efficiency (PTE) was 93
percent, 98 percent, 90 percent, 83 percent, and 94 percent respectively.
With regard to TE, table 4 shows that the average TE of the Islamic banks was higher than the national
average of all domestic private banks. While the national average efficiency of all domestic private banks
were 89 percent, 98 percent, 89 percent, 83 percent, and 91 percent during 2008, 2009, 2010, 2011, and
2012 respectively, the Islamic banks’ average efficiency (PTE) was 91 percent, 99 percent, 96 percent, 86
percent, and 92 percent. On the other hand, the conventional banks’ average efficiency (PTE) was 80
percent, 98 percent, 87 percent, 82 percent, and 91 percent respectively.
The results of average scale efficiency (SE) show that the conventional banks’ average was at par with
the national average of all banks during 2008, 2009, and 2010 while the Islamic banks’ average was
higher during the same periods.
Table 4 shows that during 2008- 2012 that the range of average efficiency (PTE), TE, and SE of Islamic
banks was 91 percent to 99 percent, 91 percent to 99 percent, and 86 percent to 99 percent whereas
the range efficiency of conventional banks was 83 percent to 98 percent, 80 percent to 98 percent, and
94 percent to 99 percent.
Table 4 shows that during 2008- 2012, pure technically efficient bank were twenty percent (6/29), thirty
one percent (9/29), sixteen percent (5/30), ten percent (3/30), and three percent respectively. A
comparative analysis of PTE shows that technically efficient (PTE) Islamic banks and conventional banks
were 42 (3/7) percent and 13.6 (3/22) percent in 2008, 42 (3/7) percent and 27 (6/22) percent in 2009,
57 (4/7) percent and 4 (1/22) percent in 2010, 42 (3/7) percent and 0 (zero) percent in 2011, and 14
(1/7) percent and 0 (zero) percent in 2012. Thus, the comparative percentage analysis of PTE suggests
that Islamic banks were more efficient than the conventional banks in the commercial banking industry
of Bangladesh.
Constant returns to scale efficient banks (TE) during 2008- 2012 were 3 percent, 13.7 percent, 6 percent,
3 percent, and 0 (zero) percent respectively.
A comparative analysis of TE shows that technically efficient (TE) Islamic banks and conventional banks
were 14 (1/7) percent and 0 (zero) percent in 2008, 28.5 (2/7) percent and 9 (2/22) percent in 2009,
28.7 (2/7) percent and 0 (zero) percent in 2010, 14 (1/7) percent and 0 (zero) percent in 2011, and 0
(zero) percent and 0 (zero) percent in 2012. Thus, the comparative percentage analysis of TE suggests
that Islamic banks were more efficient than the conventional banks in the commercial banking of
Bangladesh.
With regard to scale efficiency, it was found that only 3.4 (1/29) percent in 2008, 24 (7/29) percent in
2009, 10 (3/30) percent in 2010, 13 (4/30) percent in 2011, and 3 (1/30) percent privately owned
domestic banks were scale efficient in Bangladesh.
A comparative analysis of SE shows that scale efficient (SE) Islamic banks and conventional banks were
14 (1/7) percent and 0 (zero) percent in 2008, 42.5 (3/7) percent and 18 (4/22) percent in 2009, 28.7
(2/7) percent and 4 (1/22) percent in 2010, 28.5 (2/7) percent and 17 (4/23) percent in 2011, and 0
(zero) percent and 3 (1/30) percent in 2012. Thus, the comparative percentage analysis of TE suggests
that Islamic banks were more efficient than the conventional banks in the banking industry of
Bangladesh.
[Insert Table 5]
Table 5 shows that the average PTE of the Islamic banks is higher than the national average PTE of all
domestic private banks (Conventional and Islamic) except in 2010. While the average efficiency of all
domestic private banks were 91 percent, 92 percent, 97 percent, 90 percent, and 88 percent during
2008, 2009, 2010, 2011, and 2012 respectively, the Islamic banks’ average efficiency (PTE) was 93
percent, 94 percent, 92 percent, 94 percent, and 92 percent. On the other hand, the conventional
banks’ average efficiency (PTE) was 90 percent, 92 percent, 88 percent, 89 percent, and 87 percent
respectively. Conventional banks operate below the national average.
With regard to TE, table 5 shows that the average TE of the Islamic banks was higher than the national
average of all domestic private banks except in 2008. While the national average efficiency of all
domestic private banks were 87 percent, 87 percent, 83 percent, 84 percent, and 81 percent during
2008, 2009, 2010, 2011, and 2012 respectively, the Islamic banks’ average efficiency (TE) was 86
percent, 88 percent, 85 percent, 86 percent, and 83 percent. On the other hand, the conventional
banks’ average efficiency (TE) was 87 percent, 87 percent, 83 percent, 83 percent, and 81 percent
respectively. During the same period, the conventional banks’ average was at par with the national
average except 2011 and 21012 when the average efficiency of conventional banks was below the
national average.
The results of average scale efficiency (SE) show that the conventional banks’ average was higher than
the national average of all banks during 2008, 2009, and 2010 while the Islamic banks’ average was
lower than the national average of all bank during the entire period under study.
Table 5 shows that the efficient (PTE) banks were 10 (3/29) percent, 17 (5/29) percent, 13 (4/30)
percent, 16.6 (5/30) percent, and 6(2/30) percent during 2008, 2009, 2010, 20111, and 2012
respectively.
The number of efficient Islamic banks (PTE) was 14 (1/7) percent, 14 (1/7) percent, 28 (2/7) percent,
42.8 (3/7) percent, and 14 (2/7) percent during 2008, 2009, 2010, 20111, and 2012 respectively. On the
other hand, the number of efficient convention banks was 9 (2/22) percent, 18 (4/22) percent, 6 (2/30)
percent, and 6 (2/30) percent during 2008, 2009, 2010, and 20111 respectively. There was no single
efficient conventional bank during 2012. The comparative analysis of PTE between the Islamic banks and
the conventional banks shows that the Islamic banks were more efficient that the conventional banks
during the same period 2008-2012.
Technical efficiency results show that only one conventional bank was found to be efficient in 2008,
2009, and 2011. Only one Islamic bank was found to be technically efficient in the value added
production during same period.
As far as the CRS efficiency is concerned, conventional banks outperformed the Islamic banks. The
number of efficient conventional banks was 5, 2, 1, 1, and 1 during 2008, 2009, 2010, 20111, and 2012
respectively. On the other hand, the number of efficient Islamic banks was 1, 0, 0, and 1 during the same
period.
[Insert Table 6]
Table 6 shows that the average PTE of the Islamic banks is higher than the national average PTE of all
domestic private banks (Conventional and Islamic) except in 2011 and 2012. While the average
efficiency of all domestic private banks were 93 percent, 94 percent, 91 percent, 92 percent, and 86
percent during 2008, 2009, 2010, 2011, and 2012 respectively, the Islamic banks’ average efficiency
(PTE) was 95 percent, 95 percent, 97 percent, 92 percent, and 98 percent. On the other hand, the
conventional banks’ average efficiency (PTE) was 93 percent, 94 percent, 90 percent, 92 percent, and 86
percent respectively. Conventional banks’ average was at par with the national average of all banks
during the period except in 2010.
The average TE of the Islamic banks was higher than the national average of all domestic private banks
only in 2008 and 2010. While the national average efficiency of all domestic private banks were 88
percent, 89 percent, 88 percent, 83 percent, and 88 percent during 2008, 2009, 2010, 2011, and 2012
respectively, the Islamic banks’ average efficiency (TE) was 91 percent, 88 percent, 95 percent, 83
percent, and 82 percent. On the other hand, the conventional banks’ average efficiency (TE) was 87
percent, 87 percent, 83 percent, 83 percent, and 81 percent respectively. During the same period, the
conventional banks’ average was at par with the national average except 2010 when the average
efficiency of conventional banks was below the national average.
The results of average scale efficiency (SE) show that the Islamic banks and conventional banks’ average,
in general, was at par with the national average of all banks.
Table 3 shows that in operating approach (Income), only 17 (5/29) percent banks in 2008, 20.6 (6/29)
percent banks in 2009, 20 (6/30) percent banks in 2010, and 10 (3/30) percent banks in 2011 were pure
technically efficient. No bank was found pure technically efficient.
A comparative analysis of efficiency (PTE) shows that during 2008, 2009, 2010, 2011 and 2012, Islamic
banks’ and conventional banks’ efficiency were 42.8 (3/7) percent and 9 (2/22) percent, 28.5 (2/7)
percent and 18 (4/22), 71 (5/7) percent and 4 (1/23) percent, and 28.5 (2/7) percent and 3 (1/30)
percent respectively. It clearly demonstrates that the Islamic banks were more efficient than the
conventional banks
The average technical efficiency (TE) of the Islamic banks was higher than that of conventional banks
during 2008, 2009, and 2010.
As far as the scale efficiency is concerned, the efficient Islamic banks during 2008, 2009, and 2010 were
14 (1/7) percent, 0 percent, 28 (2/7) percent respectively. Conventional banks’ efficiency during the
same period was 0 (zero) percent, 4.5 (1/22) percent, 0 (zero) percent respectively. It, thus, shows that
the Islamic banks were more efficient than the conventional banks.
[Insert Table 7]
Table 7 shows that the average PTE and TE of Islamic banks in loan financing were significantly higher
than those of conventional banks during the study period 2008-2012 except in 2008. The null hypothesis
of equality mean efficiency in PTE and TE between the conventional banks and the Islamic banks was
rejected during these periods
The null hypothesis tests show that there is no significant difference in SE between the conventional
banks and the Islamic banks except during 2011 and 2012 when Islamic banks had significantly higher
scale efficiencies.
[Insert Table 8]
Table 8 shows that the average PTE of Islamic banks in value added production was not significantly
different than those of conventional banks during the study period 2008-2012 except in 2011 and 2012.
The null hypothesis of equality mean efficiency in PTE between the conventional banks and the Islamic
banks was not rejected during 2008-2010. The null hypothesis of equality of mean PTE efficiency was
rejected at 5 percent level of significance in 2011 and 20012.
The result of TE efficiency test shows that there was no significant difference between the conventional
banks and the Islamic banks during the study period except in 2008.
The result of SE efficiency test shows that there was no significant difference between the conventional
banks and the Islamic banks during the entire study period.
[Insert Table 9]
The results of PTE tests, Table 9, show that there was no significant difference in PTE between the
conventional banks and the Islamic banks except in 2010 when the average PTE of the Islamic banks was
significantly higher than that of the conventional banks.
The result of TE efficiency test shows that there was no significant difference between the conventional
banks and the Islamic banks during the study period except in 2010 when the average PTE of the Islamic
banks was significantly higher than that of the conventional banks.
The result of SE efficiency test shows that there was no significant difference between the conventional
banks and the Islamic banks during the study period when the average SE of the conventional banks was
significantly higher than that of the Islamic banks.
Conclusions
This employees the Data Envelopment Analysis (DEA) in estimating various efficiencies such as PTE, TE,
and SE of the domestic private banks, conventional banks as well as Islamic banks, of Bangladesh during
2008-2012.
In loan financing, the estimate of PTE shows that the Islamic banks operate at a higher efficiency level
that the national average efficiency level of all private banks, conventional and Islamic banks during
2008-2012. Conventional banks operate below the national average of PTE. While the national average
efficiency of all domestic private banks were 94 percent, 99 percent, 91 percent, 84 percent, and 94
percent during 2008, 2009, 2010, 2011, and 2012 respectively, the Islamic banks’ average efficiency
(PTE) was 96 percent, 99 percent, 97 percent, 91 percent, and 95 percent. On the other hand, the
conventional banks’ average efficiency (PTE) was 93 percent, 98 percent, 90 percent, 83 percent, and 94
percent respectively. The rejection of the null hypothesis of the equality of PTE efficiency test suggests
that Islamic banks had significantly higher PTE than the conventional banks during the period except in
2008.
The average TE of Islamic banks was higher than the national average of all domestic private banks.
While the national average efficiency of all domestic private banks were 89 percent, 98 percent, 89
percent, 83 percent, and 91 percent during 2008, 2009, 2010, 2011, and 2012 respectively, the Islamic
banks’ average efficiency (TE) was 91 percent, 99 percent, 96 percent, 86 percent, and 92 percent. On
the other hand, the conventional banks’ average efficiency (TE) was 80 percent, 98 percent, 87 percent,
82 percent, and 91 percent respectively. The rejection of the null hypothesis of the equality of TE
efficiency test suggests that Islamic banks had significantly higher PTE than the conventional banks
during the period except in 2008 and 2009
The results of average scale efficiency (SE) show that the conventional banks’ average was at par with
the national average of all banks during 2008, 2009, and 2010 while the Islamic banks’ average was
higher during the same periods. The null hypothesis tests show that there were no significant difference
in SE between the conventional banks and the Islamic banks during the period except in 2011 and 2012
when Islamic banks had significantly higher SE.
In the value added production, the Islamic banks average was higher than the national average PTE of all
domestic private banks (Conventional and Islamic) except in 2010. While the average efficiency of all
domestic private banks were 91 percent, 92 percent, 97 percent, 90 percent, and 88 percent during
2008, 2009, 2010, 2011, and 2012 respectively, the Islamic banks’ average efficiency (PTE) was 93
percent, 94 percent, 92 percent, 94 percent, and 92 percent. On the other hand, the conventional
banks’ average efficiency (PTE) was 90 percent, 92 percent, 88 percent, 89 percent, and 87 percent
respectively. Conventional banks operate below the national average. The result of the null hypothesis
tests shows no significant differences in PTE between the conventional banks and Islamic banks during
the period except in 2011 and 2012 when the average PTE of the Islamic banks was significantly higher
than that of the conventional banks.
The average TE of the Islamic banks was higher than the national average of all domestic private banks
except in 2008. While the national average efficiency of all domestic private banks were 87 percent, 87
percent, 83 percent, 84 percent, and 81 percent during 2008, 2009, 2010, 2011, and 2012 respectively,
the Islamic banks’ average efficiency (TE) was 86 percent, 88 percent, 85 percent, 86 percent, and 83
percent. On the other hand, the conventional banks’ average efficiency (PTE) was 87 percent, 87
percent, 83 percent, 83 percent, and 81 percent respectively. During the same period, the conventional
banks’ average was at par with the national average except 2011 and 21012 when the average efficiency
of conventional banks was below the national average. The result of the null hypothesis tests shows no
significant differences in TE between the conventional banks and Islamic banks during the study period
except in 2008.
The results of average scale efficiency (SE) show that the conventional banks’ average was higher than
the national average of all banks during 2008, 2009, and 2010 while the Islamic banks’ average was
lower than the national average of all bank during the entire period under study. The result of the null
hypothesis tests shows no significant differences in SE between the conventional banks and Islamic
banks during the study period.
In operating approach, the average PTE of the Islamic banks is higher than the national average PTE of
all domestic private banks (Conventional and Islamic) except in 2011 and 2012. Conventional banks’
average was at par with the national average of all banks during the period except in 2010. The null
hypothesis tests show no significant difference in PTE between the conventional banks and the Islamic
banks except in 2010
The average TE of the Islamic banks was higher than the national average of all domestic private banks
only in 2008 and 2010. During the same period, the conventional banks’ average was at par with the
national average except 2010 when the average efficiency of conventional banks was below the national
average. The null hypothesis tests show no significant difference in TE between the conventional banks
and the Islamic banks except in 2010
The results of average scale efficiency (SE) show that the Islamic banks and conventional banks’ average,
in general, was at par with the national average of all banks. The null hypothesis tests show no
significant difference in TE between the conventional banks and the Islamic banks except in 2012 when
conventional banks were found to have significantly higher scale efficiency.
References: available during presentation
Appendix 1
Table A
Descriptive Statistics of Inputs and Outputs*
Year
2008
2009
2010
2011
2012
2,517.4
4176.8
2,628.2
4123.6
2,847.8
4081.1
3,049.6
4367.4
3,327.8
7665.0
1,021.8
1006.8
1,957.8
2720.3
2,564.6
2928.4
3,542.0
4361.6
3,847.6
4611.8
Mean
SD
Expenditure
57,330.5
64,489.59
69,319
73,672.2
85,798.1
87,351.0
102,054.1
101,583.6
122,332.1
116,907.1
Mean
SD
4681.6
4244.7
5505.6
4865.8
6,546.8
6151.8
8,622.6
7068.6
12,003.2
10009.8
46,599.4
46177.4
53,450.3
48520.7
73,519.1
65534.1
86,302.1
73418.7
96,692.1
83700.1
Mean
SD
Loans and
Deposits
6,982.1
5883.5
8,285.1
6726.9
14,379.3
28057.8
13,079.4
10461.7
27,604.8
74865.4
Mean
SD
103,929.7
110114.4
122,770.0
121902.1
159,317.3
150372.0
188,356.2
172895.4
219,024.3
199581.3
Inputs
Labor
Mean
SD
Fixed Capital
Mean
SD
Deposits
Outputs
Loans and
Advances
Mean
SD
Income
* All variables are in million TK, the local currencies of Bangladesh, except labor.
Table 1
Loan efficiency of the DMU1
DMU
1CB
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24IS
25
26
27
28
29
30
μ
ø
0.88
0.83
0.95
0.87
0.86
0.85
0.92
0.97
2008
TE
0.80
0.80
0.89
0.81
0.84
0.82
0.85
0.88
1
1
0.99
0.93
0.96
1
0.91
0.95
0.96
0.96
0.97
0.93
0.90
0.95
1
0.91
0.93
0.90
1
0.97
1
0.93
0.87
0.93
0.92
0.87
0.91
0.91
0.89
0.94
0.92
0.92
0.90
0.91
0.88
0.89
0.85
0.89
0.91
0.88
1
0.94
0.90
0.83
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
ø
0.99
0.96
0.99
0.99
0.96
0.97
0.98
1
2009
TE RTS
0.98 DRS
0.96 IRS
0.98 IRS
0.98 IRS
0.95 IRS
0.97 IRS
0.98 IRS
1
CRS
DRS
DRS
DRS
DRS
DRS
IRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
IRS
DRS
DRS
CRS
DRS
DRS
1
1
1
0.97
0.98
0.99
0.99
1
1
0.99
0.99
0.96
0.97
0.99
1
1
0.99
0.98
0.99
0.99
1
0.98
0.98
0.98
0.99
0.97
0.98
0.99
0.98
0.97
1
0.99
0.99
0.96
0.97
0.98
0.97
1
0.99
0.97
0.99
0.99
1
0.98
DRS
DRS
DRS
IRS
IRS
IRS
IRS
IRS
CRS
IRS
DRS
IRS
IRS
IRS
DRS
CRS
IRS
IRS
IRS
IRS
CRS
ø
0.84
0.84
0.92
0.90
0.86
0.83
0.89
0.88
0.98
0.91
0.95
0.93
0.86
0.91
0.92
0.92
0.85
1
0.88
0.95
0.91
0.90
0.87
1
1
0.94
0.88
1
1
1
0.90
2010
TE
0.83
0.83
0.88
0.88
0.84
0.81
0.87
0.84
0.95
0.87
0.91
0.91
0.84
0.88
0.90
0.91
0.82
0.81
0.87
0.92
0.89
0.89
0.88
0.88
1
0.94
0.88
0.99
1
0.96
0.87
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
IRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
CRS
DRS
DRS
DRS
CRS
DRS
ø
0.81
0.80
0.80
0.87
0.80
0.81
0.83
0.85
0.83
0.85
0.83
0.84
0.79
0.81
0.89
0.84
0.88
0.82
0.82
0.84
0.89
0.81
0.82
1
1
0.87
0.81
0.86
0.84
1
0.83
2011
TE
0.81
0.79
0.80
0.83
0.79
0.81
0.81
0.84
0.83
0.82
0.82
0.83
0.79
0.81
0.86
0.83
0.86
0.81
0.82
0.83
0.86
0.80
0.81
0.81
1
0.84
0.81
0.84
0.83
0.88
0.82
RTS
DRS
IRS
DRS
DRS
IRS
IRS
DRS
DRS
DRS
DRS
DRS
DRS
IRS
DRS
DRS
IRS
IRS
IRS
IRS
DRS
DRS
IRS
DRS
DRS
CRS
DRS
IRS
DRS
DRS
DRS
ø
0.95
0.91
0.94
0.95
0.95
0.94
0.95
0.96
0.94
0.97
0.95
0.94
0.93
0.93
0.94
0.93
0.92
0.92
0.92
0.94
0.92
0.91
0.04
1
0.92
0.94
0.94
0.95
0.95
0.98
0.94
2012
TE
0.91
0.90
0.91
0.92
0.91
0.92
0.91
0.93
0.92
0.92
0.91
0.92
0.90
0.90
0.92
0.92
0.92
0.91
0.91
0.91
0.91
0.90
0.91
0.92
0.91
0.92
0.91
0.92
0.93
0.93
0.91
1.ø=PTE, μ = average, and RTS= Return to scale, DRS= Decreasing Returns to scale, IRS== Increasing Returns to scale, CRS= = Constant Returns to scale
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DTS
DRS
DRS
DRS
DRS
DRS
Table 2
Value Added (loan +Deposit) efficiency of the DMU1
DMU
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
μ
ø
0.88
0.86
0.92
0.89
0.80
0.83
0.87
0.96
2008
TE
0.87
0.86
0.83
0.86
0.80
0.83
0.84
0.86
1
0.98
0.98
0.90
0.92
0.99
0.86
0.90
0.92
0.92
0.95
1
0.84
0.80
1
0.86
0.88
0.93
0.94
0.92
0.98
0.91
0.96
0.84
0.87
0.84
0.86
0.92
0.85
0.90
0.88
0.87
0.87
1
0.84
0.79
0.81
0.85
0.87
0.91
0.85
0.87
0.86
0.87
RTS
DRS
IRS
DRS
DRS
IRS
IRS
DRS
DRS
ø
0.89
0.85
0.94
0.88
0.85
0.85
0.90
0.97
2009
TE
0.85
0.81
0.84
0.83
0.82
0.85
0.85
0.87
DRS
DRS
DRS
DRS
DRS
DRS
DRS
IRS
DRS
DRS
DRS
CRS
DRS
DRS
DRS
IRS
DRS
IRS
DRS
DRS
DRS
1
1
1
0.90
0.92
0.93
0.93
0.89
1
0.92
0.97
0.99
0.87
0.83
0.98
0.98
0.89
0.92
0.94
0.91
1
0.92
0.94
0.85
0.90
0.84
0.85
0.89
0.90
0.83
1
0.89
0.89
0.98
0.86
0.80
0.81
0.95
0.88
0.90
0.87
0.88
0.90
0.87
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
CRS
DRS
DRS
DRS
DRS
DRS
DRS
IRS
DRS
IRS
DRS
DRS
DRS
ø
0.88
0.83
0.89
0.87
0.85
0.84
0.89
0.94
0.96
1
0.91
0.90
0.86
0.88
0.90
0.87
0.86
1
0.88
0.92
0.87
0.87
0.84
1
0.90
0.88
0.87
0.85
0.88
1
0.89
2010
TE
0.82
0.80
0.82
0.80
0.80
0.82
0.82
0.84
0.87
0.92
0.83
0.84
0.82
0.82
0.84
0.82
0.85
0.99
0.83
0.84
0.83
0.82
0.79
0.81
0.97
0.83
0.84
0.80
0.83
0.88
0.83
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
ø
0.88
0.84
0.89
0.90
0.86
0.86
0.88
0.93
0.88
1
0.92
0.92
0.86
0.90
0.92
0.88
0.91
0.88
0.88
0.92
1
0.86
0.85
1
1
0.91
0.89
0.90
0.89
1
0.90
2011
TE
0.84
0.82
0.81
0.82
0.82
0.83
0.82
0.82
0.81
0.94
0.82
0.82
0.83
0.82
0.85
0.83
0.90
0.82
0.81
0.82
1
0.81
0.80
0.83
1
0.85
0.85
0.83
0.82
0.86
0.84
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
CRS
DRS
DRS
DRS
CRS
DRS
DRS
DRS
DRS
DRS
2012
TE
0.78
0.79
0.80
0.80
0.79
0.80
0.79
0.81
0.82
0.80
0.81
0.82
0.78
0.82
0.85
0.83
0.87
0.81
0.82
0.95
0.80
0.78
0.78
0.92
0.82
0.82
0.81
0.80
0.86
ø
0.84
0.82
0.90
0.87
0.84
0.85
0.87
0.92
0.87
0.95
0.92
0.91
0.82
0.90
0.90
0.87
0.87
0.89
0.87
0.91
0.96
0.85
0.83
1
0.95
0.88
0.88
0.87
0.88
1
0.88 0.81
1.ø=PTE, μ = average, and RTS= Return to scale, DRS= Decreasing Returns to scale, IRS== Increasing Returns to scale, CRS= = Constant Returns to scale
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
Table 3
Operating (Income) efficiency of the DMU1
DMU
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
μ
ø
0.88
0.83
0.95
0.87
0.86
0.85
0.92
0.97
2008
TE
0.80
0.80
0.89
0.81
0.84
0.82
0.85
0.88
1
1
0.98
0.93
0.96
1
0.91
0.95
0.96
0.96
0.97
0.93
0.90
0.95
1
0.91
0.93
0.90
1
0.97
1
0.93
0.87
0.93
0.92
0.87
0.91
0.91
0.89
0.94
0.92
0.92
0.90
0.91
0.88
0.89
0.85
0.89
0.91
0.88
1
0.94
0.90
0.88
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
ø
0.92
0.88
1
0.94
0.90
0.87
0.92
0.98
2009
TE
0.86
0.85
0.89
0.86
0.85
0.87
0.87
0.91
DRS
DRS
DRS
DRS
DRS
DRS
DRS
IRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
IRS
DRS
DRS
CRS
DRS
DRS
0.96
1
1
0.92
0.93
0.92
0.94
0.95
1
0.94
0.97
0.97
0.90
0.94
1
1
0.90
0.93
0.97
0.92
0.99
0.94
0.92
0.89
0.94
0.87
0.88
0.90
0.93
0.86
1
0.91
0.93
0.91
0.89
0.85
0.84
0.80
0.89
0.91
0.92
0.90
0.92
0.89
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
IRS
CRS
DRS
DRS
IRS
DRS
DRS
DRS
IRS
DRS
IRS
DRS
DRS
DRS
ø
0.84
0.84
0.92
0.90
0.86
0.83
0.89
0.88
0.98
0.91
0.95
0.93
0.86
0.91
0.92
0.92
0.85
1
0.88
0.95
0.91
0.90
0.87
1
1
0.94
0.88
1
1
1
0.91
2010
TE
0.83
0.83
0.88
0.88
0.84
0.81
0.87
0.84
0.95
0.87
0.91
0.91
0.84
0.88
0.90
0.91
0.82
0.81
0.87
0.92
0.89
0.89
0.86
0.88
1
0.94
0.88
0.99
1
0.96
0.88
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
IRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
CRS
DRS
DRS
DRS
CRS
DRS
ø
0.91
0.89
0.95
0.96
0.90
0.89
0.93
0.97
0.92
0.97
1
0.96
0.90
0.92
0.94
0.92
0.89
0.89
0.92
0.96
0.92
0.89
0.91
1
0.81
0.92
0.89
0.90
0.90
1
0.92
2011
TE
0.83
0.83
0.82
0.84
0.83
0.82
0.83
0.84
0.83
0.89
0.83
0.83
0.83
0.82
0.85
0.83
0.85
0.81
0.81
0.82
0.87
0.82
0.82
0.83
0.80
0.83
0.83
0.81
0.82
0.87
0.83
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
ø
0.80
0.81
0.88
0.91
0.84
0.84
0.86
0.91
0.87
0.97
0.89
0.89
0.81
0.87
0.88
0.85
0.86
0.87
0.87
0.90
0.84
0.85
0.80
0.82
0.86
0.86
0.87
0.85
0.88
0.91
0.86
2012
TE
0.79
0.80
0.85
0.88
0.83
0.82
0.83
0.88
0.85
0.86
0.86
0.86
0.80
0.84
0.87
0.84
0.83
0.84
0.85
0.87
0.80
0.83
0.78
0.80
0.75
0.84
0.85
0.83
0.85
0.87
0.83
1.ø=PTE, μ = average, and RTS= Return to scale, DRS= Decreasing Returns to scale, IRS== Increasing Returns to scale, CRS= = Constant Returns to scale
RTS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
IRS
DRS
DRS
DRS
IRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
DRS
Table 4
Comparison of Efficiencies between Domestic Conventional Banks and Domestic Islamic Banks
Intermediate Approach (Loan)
Year
2008
2009
2010
Pure Technical Efficiency
Total Domestic Private Banks
i7+c22=29 i7+c22=29 i7+c23=30
# of Efficient Conventional Banks
3
6
1
# of Efficient Islamic Banks
3
3
4
Total Efficient Banks
6
9
5
Islamic Bank Average Efficiency
0.96
0.99
0.97
Conventional Bank Average efficiency
0.93
0.98
0.90
Average of all (DCBK & ISBK)
0.94
0.99
0.91
Technical efficiency
Total Domestic Private Banks
i7+c22=29 i7+c22=29 i7+c23=30
# of Efficient Conventional Banks
0
2
0
# of Efficient Islamic Banks
1
2
2
Total Efficient Banks
1
4
2
Islamic Bank Average Efficiency
0.91
0.99
0.96
Conventional Bank Average efficiency
0.80
0.98
0.87
Average of all (DCBK & ISBK)
0.89
0.98
0.89
Scale Efficiency
Total Domestic Private Banks
i7+c22=29 i7+c22=29 i7+c23=30
# of Efficient Conventional Banks
0
4
1
# of Efficient Islamic Banks
1
3
2
Total Efficient Banks
1
7
3
Islamic Bank Average Efficiency
0.95
0.99
0.96
Conventional Bank Average efficiency
0.94
0.99
0.96
Average of all (DCBK & ISBK)
0.94
0.99
0.96
2011
2012
i7+c23=30
0
3
3
0.91
0.83
0.84
i7+c23=30
0
1
1
0.95
0.94
0.94
i7+c23=30
0
1
1
0.86
0.82
0.83
i7+c23=30
0
0
0
0.92
0.91
0.91
i7+c23=30
4
2
4
0.86
0.98
0.95
i7+c23=30
1
0
1
0.92
0.97
0.96
Table 5
Comparison of Efficiencies between Private Domestic Conventional Banks and Islamic Banks
Value Added Approach (Loan Deposit)
2008
2009
2010
Year
Pure Technical Efficiency
Total Domestic Private Banks
# of Efficient Conventional Banks
# of Efficient Islamic Banks
Total Efficient Banks
Islamic Bank Average Efficiency
Conventional Bank Average efficiency
Average of all (DCBK & ISBK)
Technical efficiency
Total Domestic Private Banks
# of Efficient Conventional Banks
# of Efficient Islamic Banks
Total Efficient Banks
Islamic Bank Average Efficiency
Conventional Bank Average efficiency
Average of all (DCBK & ISBK)
Scale Efficiency
Total Domestic Private Banks
# of Efficient Conventional Banks
# of Efficient Islamic Banks
Total Efficient Banks
Islamic Bank Average Efficiency
Conventional Bank Average efficiency
Average of all (DCBK & ISBK)
2011
2012
(7+22)=29
2
1
3
0.93
0.90
0.91
(7+22)=29
4
1
5
0.94
0.92
0.92
(7+23)=30
2
2
4
0.92
0.88
0.97
(7+23)=30
2
3
5
0.94
0.89
0.90
(7+23)=30
0
2
2
0.92
0.87
0.88
(7+22)=29
1
0
1
0.86
0.87
0.87
(7+22)=29
1
0
1
0.88
0.87
0.87
(7+23)=30
0
0
0
0.85
0.83
0.83
(7+23)=30
1
1
2
0.86
0.83
0.84
(7+23)=30
0
0
0
0.83
0.81
0.81
(7+22)=29
5
1
6
0.92
0.96
0.95
(7+22)=29
2
0
2
0.93
0.95
0.94
(7+23)=30
1
0
1
0.92
0.94
0.93
(7+23)=30
1
1
2
0.91
0.93
0.93
(7+23)=30
1
0
1
0.90
0.92
0.92
Table 6
Comparison of Efficiencies between Private Domestic Conventional Banks and Islamic Banks
Operative Approach (Income)
2008
2009
Year
Pure Technical Efficiency
Total Domestic Private Banks
# of Efficient Conventional Banks
# of Efficient Islamic Banks
Total Efficient Banks
Islamic Bank Average Efficiency
Conventional Bank Average efficiency
Average of all (DCBK & ISBK)
Technical efficiency
Total Domestic Private Banks
# of Efficient Conventional Banks
# of Efficient Islamic Banks
Total Efficient Banks
Islamic Bank Average Efficiency
Conventional Bank Average efficiency
Average of all (DCBK & ISBK)
Scale Efficiency
Total Domestic Private Banks
# of Efficient Conventional Banks
# of Efficient Islamic Banks
Total Efficient Banks
Islamic Bank Average Efficiency
Conventional Bank Average efficiency
Average of all (DCBK & ISBK)
2010
2011
2012
(7+22)=29
2
3
5
0.95
0.93
0.93
(7+22)=29
4
2
6
0.95
0.94
0.94
(7+23)=30
1
5
6
0.97
0.90
0.91
(7+23)=30
1
2
3
0.92
0.92
0.92
(7+23)=30
0
0
0
0.86
0.86
0.86
(7+22)=29
0
1
1
0.91
0.88
0.88
(7+22)=29
1
0
1
0.88
0.89
0.89
(7+23)=30
0
2
2
0.95
0.87
0.88
(7+23)=30
0
0
0
0.83
0.83
0.83
(7+23)=30
0
0
0
0.82
0.83
0.83
(7+22)=29
1
1
2
0.95
0.94
0.94
(7+22)=29
2
0
2
0.94
0.92
0.94
(7+23)=30
1
4
5
0.97
0.96
0.96
(7+23)=30
0
0
0
0.90
0.90
0.90
(7+23)=30
0
0
0
0.95
0.97
0.96
Table 7
Summary of Null Hypothesis Tests for Loan Efficiency between Domestic Conventional Banks and
Islamic Banks
Test
Statistics
PTE 2008
F (Prob)> F
F (Prob)> F
t (Prob)> t
Satterthwaite
Welch t-test1
H0: μDCBK = μISBK
t (Prob)> t
1.30
1.57
-1.14
-1.25
TE 2008
2.29
20.5
-1.51
-1.43
SE 2008
0.20
0.11
-0.45
-0.33
PTE 2009
2.55
-4.37**
-1.59
-2.09**
TE 2009
2.49
2.60
-1.57
-1.61
SE 2009
0.006
0.004
-0.08
0.06
PTE 2010
11.04*
10.34*
-3.32*
-3.21*
Fail to reject
H0
Fail to reject
H0
Reject H0
TE 2010
25.85*
20.31*
-5.08*
-4.50*
Reject H0
SE 2010
0.007
0.005
0.08
0.07
PTE 2011
15.18*
5.87**
-3.89*
-2.42**
Fail to reject
H0
Reject H0
TE 2011
5.87**
2.23
-2.42**
-1.49
Reject H0
SE2011
76.67*
24.32*
8.74*
4.93*
Reject H0
PTE2012
4.63**
2.43
-2.15**
-1.55
Reject H0
TE 2012
4.23**
4.68**
-2.05**
-2.16**
Reject H0
SE2012
118.87*
183.92*
10.90*
13.56*
Reject H0
Hypothesis
ANOVA test
H0: μDCBK = μISBK
Parametric test types
Welch F-test!
t-test
H0: μDCBK = μISBK H0: μDCBK = μISBK
1.Test allows for unequal cell variance, *= Significant at 1 percent level, ** = Significant at 5 percent, *** = Significant at 10 percent level
Decision
Fail to reject
H0
Fail to reject
H0
Fail to reject
H0
Reject H0
Table 8
Summary of Null Hypothesis Tests for Loan-Deposit between Domestic Conventional Banks and
Islamic Banks
Parametric test types
Welch F-test!
t-test
H0: μDCBK = μISBK H0: μDCBK = μISBK
Test
Statistics
PTE 2008
F (Prob)> F
F (Prob)> F
t (Prob)> t
Satterthwaite
Welch t-test1
H0: μDCBK = μISBK
t (Prob)> t
0.83
1.09
-0.91
-1.04
TE 2008
5.77**
4.32***
-2.40**
-2.07***
SE 2008
1.89
1.53
1.37
1.24
PTE 2009
1.15
1.60
-1.07
-1.26
TE 2009
0.21
0.28
-0.46
-0.52
SE 2009
0.47
0.34
0.68
0.58
PTE 2010
2.30
1.56
-1.51
-1.25
TE 2010
0.58
0.41
-0.76
-0.64
SE 2010
1.16
0.55
1.07
0.74
PTE 2011
5.44**
3.96***
-2.33**
-1.99***
TE 2011
1.37
1.00
-1.16
-1.00
SE2011
0.99
0.54
0.99
0.73
PTE2012
5.23**
3.32***
-2.28**
-1.82***
TE 2012
0.86
0.66
-0.92
0.81
SE2012
1.76
0.98
1.33
0.99
Hypothesis
ANOVA test
H0: μDCBK = μISBK
1.Test allows for unequal cell variance, *= Significant at 1 percent level, ** = Significant at 5 percent, *** = Significant at 10 percent level
Decision
Fail to reject
H0
Reject H0
Fail to reject
H0
Fail to reject
H0
Fail to reject
H0
Fail to reject
H0
Fail to reject
H0
Fail to
Reject H0
Fail to reject
H0
Reject H0
Fail to reject
H0
Fail to reject
H0
Reject H0
Fail to reject
H0
Fail to reject
H0
Table 9
Summary of Null Hypothesis Tests for Operating Income between Domestic Conventional Banks and
Islamic Banks
Parametric test types
Welch F-test!
t-test
H0: μDCBK = μISBK H0: μDCBK = μISBK
Test
Statistics
PTE 2008
F (Prob)> F
F (Prob)> F
t (Prob)> t
Satterthwaite
Welch t-test1
H0: μDCBK = μISBK
t (Prob)> t
1.86
2.03
-1.36
-1.42
TE 2008
2.04
1.8
-1.43
-1.36
SE 2008
0.02
0.01
(0.87)
-0.11
PTE 2009
0.82
0.75
-0.90
-0.87
TE 2009
0.33
0.28
0.58
0.52
SE 2009
1.49
0.70
1.22
0.83
PTE 2010
14.22*
13.32*
-3.77*
-3.65*
Fail to reject
H0
Fail to reject
H0
Reject H0
TE 2010
19.77*
13.59***
-4.44*
-3.68**
Reject H0
SE 2010
0.20
0.16
-0.45
0.40
PTE 2011
0.29
0.14
0.54
0.37
TE 2011
0.71
0.54
0.84
0.74
Fail to reject
H0
Fail to reject
H0
SE2011
0.08
0.04
-0.28
-0.22
PTE 20112
0.16
0.21
-0.41
-0.46
TE 2012
0.56
0.39
0.75
0.62
SE2012
252.10*
88.91*
15.87*
9.42
Hypothesis
1.
ANOVA test
H0: μDCBK = μISBK
Decision
Fail to reject
H0
Fail to reject
H0
Fail to reject
H0
Fail to reject
H0
Fail to reject
H0
Fail to reject
H0
Fail to reject
H0
Fail to reject
H0
Reject H0
Test allows for unequal cell variance, *= Significant at 1 percent level, ** = Significant at 5 percent, *** = Significant at 10 percent level