Proceedings of 3rd Global Accounting, Finance and Economics Conference
5 - 7 May, 2013, Rydges Melbourne, Australia, ISBN: 978-1-922069-23-8
Super-efficiency Performance of Malaysian Banking Industry
Farhana Ismail*, Rossazana Ab-Rahim** and Nur-Zaimah Ubaidillah***
While past banking efficiency studies had tended to focus on quantifying
the efficiency of financial institutions, few attempts were undertaken to
compare the efficiency performance of domestic and foreign banks; and
even fewer to compare the super-efficiency performance of both banks. By
addressing the above discussion as the gap in the literature, this study
contributes to the existing literature by utilising Data Envelopment Analysis
to super-efficiency scores for individual banks. The first objective of this
study is to estimate technical efficiency and its decompositions, which are
pure technical and scale efficiency as well as to estimate super-efficiency
index of Malaysian banks for the study period 2000 to 2010. The results
indicate that in general, domestic banks perform better than foreign banks.
However, the super-efficiency results reveal that on efficiency performance
per individual banks; individual foreign banks are more efficient than
individual domestic banks. The findings are valid across technical efficiency
and its decompositions, which are pure technical efficiency and scale
efficiency.
JEL Codes: G21, D24 and L25
1. Introduction
The investigation of bank efficiency is important from both microeconomic and
macroeconomic point of view (Berger and Mester, 1997). From the micro perspective, the
issue of inefficient banking system is crucial given increasing competition and
improvements in the institutional, regulatory, and supervisory framework. From the macro
perspective, the efficiency of banking sector influences the cost of financial intermediation
and the soundness of financial market. Thus, an improvement in the banking performance
represents a better allocation of financial resources which results in higher private
investments that favors economic growth. As the main challenge of 10th Malaysian Plan is
to stimulate private investment, the New Economic Model of Malaysia has listed private
investments as one of the core of strategic reform initiatives to transform Malaysia to a
high income economy. On top of that, the second thrust of 10th Malaysian Plan states the
urgency to create conducive environment to unleash economic growth, by emphasizing on
12 sectors of National Key Economic Area (NKEAs); and financial services sector is listed
as one of the NKEAs to be exploited.
In the limelight of liberalization and innovation, the brisk development of financial
institutions has made banking systems vulnerable to financial crises. Thus, measurement
of the efficiency of financial institutions is important. Firms have been persistently putting
in effort to adapt and adjust themselves according to changes in the social and economic
environment, with the ultimate goal of improving their productive efficiencies (Harker and
Zenios, 1999). The construction of efficiency index is undertaken by employing non*Farhana Ismail, Faculty of Economics and Business,
Universiti Malaysia Sarawak, Malaysia. Email: ifarhana@feb.unimas.my
** Rossazana Ab-Rahim, Universiti Malaysia Sarawak, Malaysia
Email: arrossazana@feb.unimas.my
*** Nur-Zaimah Ubaidillah, Universiti Malaysia Sarawak, Malaysia
Email: unzaimah@feb.unimas.my
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Proceedings of 3rd Global Accounting, Finance and Economics Conference
5 - 7 May, 2013, Rydges Melbourne, Australia, ISBN: 978-1-922069-23-8
environment, with the ultimate goal of improving their productive efficiencies (Harker and
Zenios, 1999). The construction of efficiency index is undertaken by employing nonparametric approach, namely data envelopment analysis. This research wishes to
highlight that information obtained from this research are very useful for (a) informing
government policy with respect to the effects of deregulation, mergers or market structure
on efficiency; (b) addressing research issues on the efficiency of an industry, the ranks, or
the methods employed, or (c) improving managerial performance by identifying 'best
practices' and ' worst practices' (Berger and Humphrey, 1997).
At a conceptual level, studies on banking efficiency fall into three categories - event
studies, operating performance studies and frontier analysis studies. In light of the
aforesaid criticisms on event studies and financial ratio approaches, the frontier approach
has begun to appeal to researchers (Weill, 2004; Bos and Kool, 2006; and Bader et al.,
2008). This approach has a few advantages over the accounting ratios such as the ability
to: (a) accommodate both multiple inputs and outputs; (b) to distinguish the estimation of
x-efficiency from scale and scope efficiencies, and; (c) to differentiate the improvements in
efficiency and market power effects (Iqbal and Molyneux 2005). Further advantages of the
frontier approach include its ability to provide a single aggregate measure of efficiency
score for each bank and ability to incorporate the effects of external factors on bank
performance. Thus, this study employs the frontier approach to measure efficiency in the
Malaysian banking sector.
Despite the fact that there are numbers of studies in quantifying the efficiency of financial
institutions, there have been only few attempts to compare efficiency of foreign banks and
domestic banks, in particular in Malaysian banking sector context. As far as this research
is concern, there are few studies only focusing on measuring and comparing the efficiency
performance of foreign and domestic banks in Malaysian context. Past efficiency studies
had tended to focus on quantifying the efficiency of financial institutions (Dogan and
Fausten, 2003; Batchelor, Kuppusamy and Allen, 2005; Sufian, 2006; Ahmad-Mokhtar,
Abdullah and Al-Habshi, 2007; Mohd-Said et al., 2008; Ismail and Abdul-Rahim, 2009;
Abd-Kadir, Selamat and Islam, 2010; Yeoh and Hoey, 2011; Ab-Rahim, Md-Nor and
Ramlee, 2012), few attempts were undertaken to compare the performance of domestic
and foreign banks in Malaysian banking system (Matthews and Ismail, 2005; Sufian and
Abdul-Majid, 2008; Mohd-Tahir, Abu-Bakar and Haron, 2010; and Ong, Lim and Teh,
2011) and as far as this research is concerned, there are no studies were undertaken to
provide the ranking of individual banks in Malaysian banking.
Thus, this study offers insight of the banking performance by constructing efficiency
indexes of individual banks in Malaysia. On top of that, this study also departs from
preceding studies by establishing a comprehensive ranking of individual banks in
Malaysia. This objective is made possible by devising the super-efficiency index all banks
in Malaysia. There is some concern that previous studies had neglected the importance of
constructing super-efficiency index of individual banks. Theoretically, banks that are
located at the frontier of production function are efficient. Methodologically, the
computation of efficiency is made possible by taking the weightage of utilization of inputs
over outputs produced. Thus, this research contributes to the efficiency literature by
devising super-efficiency index of all efficient banks with respect to technical efficiency
indexes of foreign and domestic banks in by employing non-parametric method, namely
Data Envelopment Analysis (DEA) over the period of 2000 to 2011.
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Proceedings of 3rd Global Accounting, Finance and Economics Conference
5 - 7 May, 2013, Rydges Melbourne, Australia, ISBN: 978-1-922069-23-8
2. Literature Review
Despite substantial structural changes and the pivotal role of the Malaysian banking
industry to the economy, research banking efficiency appears to be limited. A stream of
efficiency studies on the Malaysian banking industry was set in motion by Katib and
Mathews (2000). Employing DEA, the study investigated the characteristics of the
management structure and technical efficiency of 20 Malaysian commercial banks
between 1989 and 1995. On average, the results revealed the decreasing trend in
technical efficiency in the range of 68% to 80%. They further suggested that most
commercial banks are inefficient, with the main source of technical inefficiency being due
to scale inefficiency gains.
Consistent with the mixed findings reported in the aforesaid studies, Dogan and Fausten
(2003) suggested that regulatory reform and liberalisation were not sufficient conditions for
productivity improvement. Krishnasamy, Alfieya Hanum Ridzwan and Perumal (2003)
investigated the nature of productivity changes for ten commercial banks in Malaysia over
the period 2000 to 2001 as a result of the mergers. The findings indicated that eight banks
registered positive total factor productivity growth except for two banks (EON Bank and
Public Bank). The growth in productivity was attributed to technological change rather than
technical efficiency change. Nevertheless, the merger had not resulted in better scale
efficiency except for two banks. Also employing the Malmquist indices, a study by Sufian
and Ibrahim (2005) found that the inclusion of off-balance sheet items resulted in an
increase in the estimated productivity levels of all banks during the period 2001 to 2003.
Existing studies that compares the efficiency performance of Malaysian domestic and
foreign banks are Matthews and Ismail, 2005; Sufian and Abdul-Majid, 2008; Mohd-Tahir,
Abu-Bakar and Haron, 2010; and Ong, Lim and Teh, 2011. In line with other Malaysian
studies, the abovementioned studies utilised the non-parametric frontier approach or DEA
to measure the banking efficiency of Malaysian banks.
Matthew and Mahadzir Ismail (2006) examined technical efficiency and productivity with
respect to domestic and foreign commercial banks in Malaysia between 1994 and 2000.
The results ruled that the main source of productivity growth was technical change and
foreign banks had a higher efficiency level than domestic banks in this respect. The
results are also supported by Ong, Lim and Teh (2011) that stated that foreign banks are
more efficient than domestic banks in respect to ATM utilisation and profit generation.
However, all preceding studies did not explicitly rank the performance of commercial
banks in the national banking industry. The majority of the studies has either estimated the
efficiency and productivity growth measures from a cost-minimizing framework or has
used a non-parametric technique designed to obtain results on technical inefficiency of
inputs. Further, the above-mentioned studies that concentrated on the efficiency
performance of banks suffer from a major methodological flaw. These studies pool the
data under the assumption that both domestic and foreign banks share a common
technology with identical frontiers. Since the domestic and foreign banks in Malaysia
provide service to different markets, the assumption of a common frontier is not justified.
Therefore, this study employs separate frontiers in estimating the efficiency index of
foreign and domestic banks in Malaysia.
3
Proceedings of 3rd Global Accounting, Finance and Economics Conference
5 - 7 May, 2013, Rydges Melbourne, Australia, ISBN: 978-1-922069-23-8
3. Data and Methodology
The main non-parametric method, DEA, was introduced by Charnes, Cooper and
Rhoades (1978) and is an analytical tool used to measure relative efficiency of firms
throughout the process of transforming inputs into outputs. Since its initial inception in
1978, DEA has evolved into more complex applications. This methodology is a nonparametric method as it requires no assumption on the functional form of the efficient
frontier, thereby making it a powerful tool in modelling complex and multi-faceted
applications. The fundamental decision to measure types of efficiency depends on the
questions being addressed which are based on economic optimization in reaction to
market prices and competition (Berger and Mester, 1997). This study employs inputoriented DEA as it is believed that domestic commercial banks should dwell well on the
sources of input waste (Isik and Hasan, 2003). The main advantage of DEA is that it does
not require a priori assumption about the analytical form of the production function and it
places less structure on the frontier (Serrano-Cinca et al., 2005).
3.1 Input and Output Variables
This study includes all domestic and foreign banks in Malaysia and covers the period from
2000 to 2011. The bank level data used are taken from BankScope spreadsheets
published by Bureau Van Dijk (BVD), supplemented with the published balance sheet and
income statement information in annual reports of individual banks. All financial variables
reported are in nominal values (Ringgit Malaysia), so to facilitate comparison over time; all
the variables are deflated by the consumer price index (CPI) to obtain real values in 2000
price constant.
In the banking theory literature, there are two main approaches which are the production
and intermediation approaches (Sealey and Lindley, 1977). This study employs
intermediation approach in choosing the variables. Based on the list of inputs and outputs
in the preceding studies as well as data availability; the input variables used are personnel
expenses, capital which is the book value of premises and fixed assets, deposits and
short term funding (hereafter denoted as deposits) whereas the output variables are
represented by total loans, total securities and off-balance sheet items.
3.2 DEA Envelopment Model
The envelopment form of the ‘virtual’ input-output combination under constant returns to
scale (CRS) model as introduced by Charnes et al. (1978) is as below:
Min , ,
s.t.
(1)
where  is the efficiency score for the ith decision making unit (DMU) and it should be
solved n times. Under the assumption of variable returns to scale (VRS) model as
proposed by Banker et al. (1984); the convexity constraint
is applied to (1).
Min , ,
s.t.
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Proceedings of 3rd Global Accounting, Finance and Economics Conference
5 - 7 May, 2013, Rydges Melbourne, Australia, ISBN: 978-1-922069-23-8
(2)
3.3 Super-efficiency DEA Model
It is important to point that the efficiency scores for all efficient DMUs are equal to 1 in the
CRS and VRS models. Thus, the ranking of efficient DMUS are impossible. Andersen and
Petersen (1993) introduced the super-efficiency DEA model. This model estimates
efficiency scores by eliminating the data on the efficient DMU from the reference set which
results in super-efficient scores of the fully efficient DMU. Therefore, the score for efficient
DMU can, in principle, take any value greater than or equal to 1. Next, these scores are
used to rank the efficient DMUs and thereby eliminate some (but not all) of the ties that
occur for efficient DMUs. Nevertheless, the inefficient units which are not on the efficient
frontier are unaffected. Andersen and Petersen’s model for estimating super-efficiency
score for DMU under CRS and VRS models are outlined as below:
Min, super,
s.t.
(3)
where 
is the super-efficiency score for the efficient DMU. Under the assumption of
variable returns to scale (VRS) the convexity constraint
is applied to (3).
super
4. Results and Discussion
In this section, the empirical results from CRS and VRS as well as DEA super-efficiency
models are presented in Table I through Table 3.
Table I: Technical Efficiency of Malaysian Commercial Banks
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
AFF
68.55
62.35
61.06
56.36
48.92
53.26
60.05
73.89
74.83
80.32
66.15
72.42
ALL
112.10
66.66
66.18
51.64
56.56
62.96
67.00
68.64
66.28
59.21
77.25
77.25
AM
93.58
99.63
92.72
91.44
81.53
73.40
78.40
86.64
118.31
268.54
114.98
176.70
CIMB
64.37
60.22
60.56
61.53
54.20
64.46
69.36
63.21
63.08
73.43
64.75
70.97
EON
83.73
86.66
50.97
52.71
62.17
68.08
62.46
66.69
62.97
64.63
63.76
76.34
HL
73.44
79.14
73.07
60.01
56.11
78.58
86.35
55.64
70.88
60.28
61.30
61.16
MAY
58.93
65.13
70.76
61.10
56.54
60.12
61.77
62.28
64.15
65.42
63.33
64.78
PUB
76.96
72.75
68.15
69.20
65.29
66.45
60.35
55.38
53.13
49.58
58.69
52.42
RHB
64.15
67.50
62.10
60.56
58.17
77.75
76.18
75.17
82.12
70.29
69.11
72.02
BB
47.83
51.62
53.74
60.59
43.87
64.32
52.24
57.69
51.04
54.37
32.55
29.67
X
X
30.29
26.89
29.32
32.31
36.94
31.11
68.77
41.26
27.34
39.97
CHI
36.55
33.02
36.02
53.22
37.56
33.49
41.18
39.21
38.82
48.81
61.28
1633.58
TOK
44.92
41.07
36.98
40.29
41.56
37.40
41.01
44.79
50.52
60.73
52.64
52.36
CITI
44.58
44.65
47.43
44.42
37.14
54.97
49.67
53.77
63.44
62.43
53.29
54.23
DEU
143.67
52.20
63.28
25.98
82.14
32.29
40.30
61.90
126.35
79.81
61.29
83.71
HSBC
40.68
38.66
36.54
42.29
40.18
41.28
39.23
41.06
45.58
42.65
41.24
30.41
JP
82.67
53.22
22.88
20.92
101.64
90.38
56.48
20.48
36.67
40.83
65.56
122.70
AMER
5
Proceedings of 3rd Global Accounting, Finance and Economics Conference
5 - 7 May, 2013, Rydges Melbourne, Australia, ISBN: 978-1-922069-23-8
Table 1 – Continued
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
OCBC
59.05
53.69
53.19
56.24
59.50
63.82
68.76
66.46
65.95
59.61
60.67
57.32
STD
58.25
56.06
51.89
60.68
39.59
49.84
59.97
56.36
62.87
55.90
54.61
55.38
NOV
149.17
102.51
97.29
89.37
66.96
138.66
92.54
88.03
80.82
92.42
89.79
130.25
ROY
86.52
42.97
15.50
33.38
12.37
41.43
31.90
34.90
27.26
23.43
28.16
24.82
UOB
49.06
52.05
57.58
47.39
53.95
56.10
61.03
62.98
61.94
46.15
42.16
45.25
ALL
73.27
61.04
54.92
53.01
53.88
60.97
58.78
57.56
65.26
68.19
59.54
140.17
DOB
77.31
73.34
67.28
62.73
59.94
67.23
69.10
67.51
72.86
87.97
71.04
80.45
FOR
70.24
51.81
46.35
46.28
49.68
56.64
51.63
50.67
60.00
54.49
51.58
181.51
Note: AFF = Affin Bank; ALLI = Alliance Bank; AM= AMBank; CIMB = CIMB Bank; EON = EON Bank; HL =
Hong Leong Bank; May = Maybank; RHB = RHB Bank; PUB = Public Bank; BB = Bangkok Bank; AMER =
Bank of America; CHI = Bank of China; TOK = Bank of Tokyo-Mitsubishi UJF; CITI = Citibank; DEU =
Deustche Bank; HSBC = HSBC Bank; JP = JP Morgan Chase Bank; OCBC = OCBC Bank; STD = Standard
Chartered Bank; NOV = The Bank of Nova Scotia; ROY = The Royal Bank of Scotland; UOB = United
Overseas Bank; ALL= all banks; DOM = domestic banks; and FOR = foreign banks .
Table I presents the technical efficiency (TE) scores of 23 commercial banks (9 domestic
banks and 13 foreign banks). The results indicate that Malaysian banking industry has
been characterized with large asymmetry among banks with their average TE scores
range between 25.98% and 100% (fully efficient) throughout year 2000 to 2011. As for the
whole industry, the highest TE (140.17%) scores is recorded in year 2000, while the
lowest scores (53.01%) is found in year 2008. The deterioration in banks efficiency during
2008 might be attributed to the slowdown in the global economy. Besides, the results also
indicate that domestic banks has higher technical efficiency index as compared to foreign
banks. This means that domestic banks perform technically better than foreign banks
during the study period.
Table 2: Pure Technical Efficiency of Malaysian Commercial Banks
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
AFF
86.7
81.6
82.0
72.3
62.7
63.8
76.2
74.2
75.9
81.7
75.9
74.0
ALL
170.0
81.5
76.2
64.4
61.1
68.0
76.4
79.2
73.1
71.9
81.8
78.8
AM
106.5
115.9
103.0
107.0
96.9
88.8
92.8
88.0
121.9
384.2
125.1
206.8
CIMB
95.8
88.5
87.1
89.8
77.8
89.9
95.4
93.2
94.5
97.2
91.8
86.3
EON
97.4
106.6
78.0
75.0
78.2
85.5
79.8
84.3
81.3
84.8
76.9
82.9
HL
92.0
119.5
92.9
82.2
81.6
106.6
108.7
70.2
87.9
73.4
78.7
71.2
MAY
0.0
119.1
151.0
95.4
85.0
91.6
93.5
94.6
98.2
98.5
94.4
91.5
PUB
123.4
94.2
89.9
100.7
96.4
110.6
78.3
78.3
89.4
79.3
80.3
69.7
RHB
95.5
97.9
89.6
87.9
81.7
102.0
97.2
91.7
106.3
96.6
96.3
93.3
BB
55.5
56.2
57.6
62.5
47.5
70.1
61.1
65.1
55.3
59.7
33.0
29.7
84.2
64.9
61.8
111.9
97.2
84.6
96.3
41.7
31.0
57.7
AMER
X
X
2000
CHI
36.9
33.2
42.1
72.8
77.6
124.1
119.2
100.1
89.0
85.5
101.6
3034.9
TOK
50.3
42.9
38.3
40.4
41.6
37.4
43.2
46.4
54.3
67.5
58.5
60.2
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Proceedings of 3rd Global Accounting, Finance and Economics Conference
5 - 7 May, 2013, Rydges Melbourne, Australia, ISBN: 978-1-922069-23-8
Table 2 – Continued
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
CITI
79.0
72.7
83.6
92.8
64.7
92.9
81.4
91.0
106.5
112.2
90.8
87.2
DEU
160.9
56.9
65.5
27.6
92.0
34.3
43.6
64.4
182.5
82.7
65.4
84.7
0.0
72.2
65.7
77.4
74.1
80.6
75.1
73.9
85.8
89.9
88.2
59.3
84.0
62.0
48.0
41.5
104.3
100.1
73.8
56.1
51.5
47.6
67.6
185.9
0.0
97.9
96.2
97.2
96.7
98.9
112.2
98.5
101.3
92.8
99.6
83.7
STD
177.3
99.9
91.2
367.1
71.8
84.9
101.2
91.8
104.4
90.4
86.0
87.1
NOV
210.4
102.7
102.2
91.3
67.7
154.4
100.1
95.4
83.5
93.3
89.9
135.2
ROY
86.8
45.6
16.7
42.4
12.8
41.6
33.6
41.0
41.1
35.8
32.3
26.0
UOB
0.0
106.0
99.1
91.9
97.2
95.7
92.0
91.9
90.1
82.7
66.7
69.9
ALL
106.4
83.5
79.1
88.4
74.1
87.9
83.3
79.7
89.5
93.2
77.8
220.7
DOB
108.4
100.5
94.4
86.1
80.1
89.6
88.7
83.8
92.1
118.6
89.0
94.9
FOR
104.6
70.7
68.5
90.0
70.0
86.7
79.5
76.9
87.8
75.5
70.1
307.8
HSBC
JP
OCBC
2000
Note: AFF = Affin Bank; ALLI = Alliance Bank; AM= AMBank; CIMB = CIMB Bank; EON = EON Bank; HL =
Hong Leong Bank; May = Maybank; RHB = RHB Bank; PUB = Public Bank; BB = Bangkok Bank; AMER =
Bank of America; CHI = Bank of China; TOK = Bank of Tokyo-Mitsubishi UJF; CITI = Citibank; DEU =
Deustche Bank; HSBC = HSBC Bank; JP = JP Morgan Chase Bank; OCBC = OCBC Bank; STD = Standard
Chartered Bank; NOV = The Bank of Nova Scotia; ROY = The Royal Bank of Scotland; UOB = United
Overseas Bank; ALL= all banks; DOM = domestic banks; and FOR = foreign banks .
Table 2 presents the pure technical efficiency (PTE) scores of all commercial banks in
Malaysia during the period of study (2000 to 2011). The results of PTE scores confirm the
previous finding that on average, domestic banks perform better than foreign banks. Next,
Table 3 shows results from the DEA super-efficiency model which enables for the ranking
of individual banks to be undertaken. The results show that banks like Bank of China,
AMBank, Standard Chartered Bank, Bank of Nova Scotia and Maybank have been
consistently been among the relatively more efficient banks. On the other hand, The Royal
Bank of Scotland, Bank of Tokyo-Mitsubishi UJF and Bangkok Bank are among the less
efficient banks. This might due to differences in term of total asset that hold by each
banks.
Table 3: Ranking of Malaysian Commercial Banks (2000-2011)
BANK
a
TE
SUPER
TE
RANK
PTE
SUPER
PTE
RANK
AFF
64.85
64.85
9
75.58
75.58
18
ALL
69.31
69.31
6
81.87
81.87
14
AM
100.00
114.66
2
100.00
136.40
2
CIMB
64.18
64.18
10
90.59
90.59
9
EON
66.76
66.76
8
84.23
84.23
13
HL
68.00
68.00
7
88.74
88.74
11
7
Proceedings of 3rd Global Accounting, Finance and Economics Conference
5 - 7 May, 2013, Rydges Melbourne, Australia, ISBN: 978-1-922069-23-8
Table 3 – Continued
BANK
a
TE
SUPER
TE
RANK
PTE
SUPER
PTE
RANK
MAY
62.86
62.86
11
100.00
101.17
5
PUB
62.36
62.36
5
90.87
90.87
7
RHB
69.59
69.59
12
94.68
94.68
8
BB
49.96
49.96
18
54.44
54.44
20
AMER
36.42
36.42
21
73.15
73.15
19
CHI
100.00
174.39
1
100.00
326.44
1
TOK
45.36
45.36
19
48.42
48.42
21
CITI
50.83
50.83
17
87.88
87.88
12
DEU
71.08
71.08
4
80.04
80.04
15
HSBC
39.98
39.98
20
76.56
76.56
17
JP
59.54
59.54
14
76.87
76.87
16
OCBC
60.35
60.35
13
97.72
97.72
6
STD
55.12
55.12
15
100.00
121.11
3
NOV
100.00
101.48
3
100.00
110.52
4
Note: AFF = Affin Bank; ALLI = Alliance Bank; AM= AMBank; CIMB = CIMB Bank; EON = EON Bank; HL =
Hong Leong Bank; May = Maybank; RHB = RHB Bank; PUB = Public Bank; BB = Bangkok Bank; AMER =
Bank of America; CHI = Bank of China; TOK = Bank of Tokyo-Mitsubishi UJF; CITI = Citibank; DEU =
Deustche Bank; HSBC = HSBC Bank; JP = JP Morgan Chase Bank; OCBC = OCBC Bank; STD = Standard
Chartered Bank; NOV = The Bank of Nova Scotia; ROY = The Royal Bank of Scotland; UOB = United
Overseas Bank; ALL= all banks; DOM = domestic banks; and FOR = foreign banks.
5. Summary and Conclusions
Bank efficiency studies are crucial from both macroeconomic and microeconomic
perspectives. From the micro perspective, knowing the cost efficiency and the profit
efficiency can offer important insights into the efficiency and its decompositions. Given
increasing competition and liberalization in the banking market, the information on sources
of efficiency is useful for the banking players to identify the strengths and the weaknesses
of their performance. From the macro perspective, the efficiency of the banking industry is
closely related to the issue of banking stability which is fundamental to economic growth
(Lozano-Vivas and Pastor 2006). Thus, study on the banking efficiency contributes to the
government’s policy to review the performance of banks.
8
Proceedings of 3rd Global Accounting, Finance and Economics Conference
5 - 7 May, 2013, Rydges Melbourne, Australia, ISBN: 978-1-922069-23-8
Acknowlegement
Financial support from Universiti Malaysia Sarawak through Small Grant Scheme [SGS
03(S83)/819/2011(7)] is gratefully acknowledged. All remaining flaws are the
responsibilities of the authors.
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