An Essay on Returns to Scale of Banks in UAE
To analyze the impact of the 2008 global financial crisis on the banking sector in the UAE and provide recommendations for addressing the challenges faced by the industry.
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Added on 2023-06-15
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This study aims to show the significance of the banking industry in the economic sector and to understand the concepts of returns to scale and its applications in the banking industry. The efficiency and productivity of different banks in UAE is measured using this method of returns to scale for the last three years.
An Essay on Returns to Scale of Banks in UAE
To analyze the impact of the 2008 global financial crisis on the banking sector in the UAE and provide recommendations for addressing the challenges faced by the industry.
Added on 2023-06-15
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Asian Journal of Management Sciences & Education Vol. 4(1) January 2015__________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
Copyright © 2015 Leena and Luna International, Oyama, Japan.
43 | P a g e (株) リナアンドルナインターナショナル, 小山市、日本.
ISSN: 2186-845X ISSN: 2186-8441 Print
www.ajmse. leena-luna.co.jp
An Essay on Returns to Scale of Banks in UAE
Anomitra Banerjee1, Aqila Rafiuddin2
BITS Pilani, Dubai Campus, UAE.
1 anomitra.banerjee@gmail.com, 2 aqila@dubai.bits-pilani.ac.in
ABSTRACT
Over the last decade, Islamic banking has experienced global growth rates of 10-15
percent per annum, and has been moving into an increasing number of conventional
financial systems at such a rapid pace that Islamic financial institutions are present
today in over 51 countries. This study aims to show the significance of the banking
industry in the economic sector and to understand the concepts of returns to scale
and its applications in the banking industry. The efficiency and productivity of
different banks in UAE is measured using this method of returns to scale for the last
three years.
Keywords: Islamic Banking, Returns to Scale, Technical Efficiency, Data
Envelopment Analysis
INTRODUCTION
The United Arab Emirates (U.A.E.) is an alliance of seven emirates specifically Abu Dhabi,
Dubai, Sharjah, Umm Al Qaiwain, Ras Al Khaimah, Fujairah and Ajman. This nation is
generally an oil and gas trading country and it is additionally one of the primary parts of the
Gulf Cooperation Council (GCC). The nation intends to develop as the budgetary and
administration segment pioneer in the Middle East and be a center point for worldwide
Islamic account.
Like the vast majority of the creating nations, the saving money part makes up the center of
the budgetary framework in UAE and it works under the principles and regulations of the
UAE Central Bank. Under the Federal Law 10, the Central bank of UAE was made and from
that point on it assumed control over the obligations of the Currency Board. The Bank's
obligations incorporate prompting the legislature on monetary issues, issuing money and
keeping up the gold stores.
With collected holdings equal to 142% of GDP in 2008, the UAE managing an account
segment was thought to be the second biggest in GCC nations after Bahrain (Al-Hassan, et
al., 2010). By 2010, the aggregate quantities of authorized banks working in UAE were 52, of
which 24 were nationalized banks and 28 were remote banks. The managing an account
division in UAE is still described by a dominating proprietorship by government and
household shareholders. Nonetheless, it is still the minimum concentrated among all GCC
keeping money areas with the three biggest banks (Emirates NBD bank, National bank of
Abu Dhabi and Abu Dhabi Commercial bank) representing just 32% of the aggregate
managing an account holdings (Al-Hassan, et al., 2010). The UAE saving money division
performed amazingly well amid the 2003-08 oil blast, yet it is likewise amid the blast that the
dangers began to develop on banks' asset reports. Thriving monetary action and plentiful
liquidity coming about because of higher oil costs pushed inordinate credit development,
swelling and possession cost expanded particularly in the land segment. Amid the same time,
banks expanded their introduction to land and development part and also value markets
which prompted a development of vulnerabilities on their monetary records that took a toll
later when the worldwide emergency occurred in 2008.
Copyright © 2015 Leena and Luna International, Oyama, Japan.
43 | P a g e (株) リナアンドルナインターナショナル, 小山市、日本.
ISSN: 2186-845X ISSN: 2186-8441 Print
www.ajmse. leena-luna.co.jp
An Essay on Returns to Scale of Banks in UAE
Anomitra Banerjee1, Aqila Rafiuddin2
BITS Pilani, Dubai Campus, UAE.
1 anomitra.banerjee@gmail.com, 2 aqila@dubai.bits-pilani.ac.in
ABSTRACT
Over the last decade, Islamic banking has experienced global growth rates of 10-15
percent per annum, and has been moving into an increasing number of conventional
financial systems at such a rapid pace that Islamic financial institutions are present
today in over 51 countries. This study aims to show the significance of the banking
industry in the economic sector and to understand the concepts of returns to scale
and its applications in the banking industry. The efficiency and productivity of
different banks in UAE is measured using this method of returns to scale for the last
three years.
Keywords: Islamic Banking, Returns to Scale, Technical Efficiency, Data
Envelopment Analysis
INTRODUCTION
The United Arab Emirates (U.A.E.) is an alliance of seven emirates specifically Abu Dhabi,
Dubai, Sharjah, Umm Al Qaiwain, Ras Al Khaimah, Fujairah and Ajman. This nation is
generally an oil and gas trading country and it is additionally one of the primary parts of the
Gulf Cooperation Council (GCC). The nation intends to develop as the budgetary and
administration segment pioneer in the Middle East and be a center point for worldwide
Islamic account.
Like the vast majority of the creating nations, the saving money part makes up the center of
the budgetary framework in UAE and it works under the principles and regulations of the
UAE Central Bank. Under the Federal Law 10, the Central bank of UAE was made and from
that point on it assumed control over the obligations of the Currency Board. The Bank's
obligations incorporate prompting the legislature on monetary issues, issuing money and
keeping up the gold stores.
With collected holdings equal to 142% of GDP in 2008, the UAE managing an account
segment was thought to be the second biggest in GCC nations after Bahrain (Al-Hassan, et
al., 2010). By 2010, the aggregate quantities of authorized banks working in UAE were 52, of
which 24 were nationalized banks and 28 were remote banks. The managing an account
division in UAE is still described by a dominating proprietorship by government and
household shareholders. Nonetheless, it is still the minimum concentrated among all GCC
keeping money areas with the three biggest banks (Emirates NBD bank, National bank of
Abu Dhabi and Abu Dhabi Commercial bank) representing just 32% of the aggregate
managing an account holdings (Al-Hassan, et al., 2010). The UAE saving money division
performed amazingly well amid the 2003-08 oil blast, yet it is likewise amid the blast that the
dangers began to develop on banks' asset reports. Thriving monetary action and plentiful
liquidity coming about because of higher oil costs pushed inordinate credit development,
swelling and possession cost expanded particularly in the land segment. Amid the same time,
banks expanded their introduction to land and development part and also value markets
which prompted a development of vulnerabilities on their monetary records that took a toll
later when the worldwide emergency occurred in 2008.
Asian Journal of Management Sciences & Education Vol. 4(1) January 2015__________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
ISSN: 2186-845X ISSN: 2186-8441 Print
www.ajmse. leena-luna.co.jp
Leena and Luna International, Oyama, Japan. Copyright © 2015
(株) リナアンドルナインターナショナル, 小山市、日本 P a g e | 44
LITERATURE REVIEW
Two most important approaches used for estimating efficiency which have been stated in
previous researches are the non-parametric and the parametric approach. A generalization
which can be made is that the parametric approach specifies a functional form for the cost,
revenue, profit, or production relationship within inputs, outputs and others (for instance,
environmental factors), and allows for any random error. The most renowned technique
utilized in the parametric approach is Stochastic Frontier Approach (SFA). On the other hand,
the DEA (Data Envelopment Analysis) is the most renowned technique used in the
nonparametric. The efficiency (relative) of each bank is computed using various inputs and
various outputs by using the DEA analysis.
First, a completely widespread study undertaken by Humphrey and Berger (1997) surveyed
more than 120 studies which utilized frontier methods to estimate the efficiency and
performance of different financial institutions in more than 21 countries. Majority of the
researches are performed between the years 1990 and 1998 in the U.S. banking industry. It
was emphasized to study the efficiency of banks in regions other than the US since very few
studies were done outside the US. Berger and Humphrey pointed out variations and spread in
estimates of efficiency between non-parametric and parametric methods. Research as well as
critical analysis of observed financial institution efficiency estimates so that the implications
of efficiency results can be addressed in the fields of research, government policy and
managerial performance was done by them.
Mohd Zaini Abd Karim (2001) investigated whether there were significant differences in
bank efficiency across selected ASEAN countries (Indonesia, Malaysia, Philippines, and
Thailand). The study indicated that the major proportion of a total variability is associated
with inefficiency of input used. It also markedly points out the fact that inefficiency tends to
reduce with bank size and increase with government ownership.
David A. Grigorian and Vlad Manole (2002), used both cross-country and cross-regional
settings, and applied the DEA approach, while trying to calculate the correct measure of
commercial bank efficiency in a multiple input/output framework for transition economies,
and to identify the effects of policy framework on the performance of commercial banks. The
results of the study illuminated the fact that banks with a larger market share and a larger
controlling foreign ownership are more likely to be efficient than those with a smaller market
which was owed to their significantly better risk management and operational techniques.
ECONOMIES OF SCALE
Economies of scale measure the relationship between the level of yield and the expense of
delivering an unit of yield. The movement is said to have (increasing) economies of scale
when the normal expense of creating a unit of yield falls as yield increments. It could be
nearby implying that normal expenses may drop for a few levels of creation yield and
afterward later settle or increment. It can likewise be worldwide implying that normal
expenses keep on dropping as yield increments.
Measuring of yields and inputs is hypothetically direct in the assembling and farming
industry. Be that as it may, the proper estimation of yield is less clear while measuring the
scale economies for administration firms. An example of such a circumstance is the health
awareness industry. The test of evaluating the yield is additionally risky in the managing an
account segment because of many-sided quality in measuring yield and perceiving yields
from inputs. The best measure of bank yield is a point on which there is no true general
ISSN: 2186-845X ISSN: 2186-8441 Print
www.ajmse. leena-luna.co.jp
Leena and Luna International, Oyama, Japan. Copyright © 2015
(株) リナアンドルナインターナショナル, 小山市、日本 P a g e | 44
LITERATURE REVIEW
Two most important approaches used for estimating efficiency which have been stated in
previous researches are the non-parametric and the parametric approach. A generalization
which can be made is that the parametric approach specifies a functional form for the cost,
revenue, profit, or production relationship within inputs, outputs and others (for instance,
environmental factors), and allows for any random error. The most renowned technique
utilized in the parametric approach is Stochastic Frontier Approach (SFA). On the other hand,
the DEA (Data Envelopment Analysis) is the most renowned technique used in the
nonparametric. The efficiency (relative) of each bank is computed using various inputs and
various outputs by using the DEA analysis.
First, a completely widespread study undertaken by Humphrey and Berger (1997) surveyed
more than 120 studies which utilized frontier methods to estimate the efficiency and
performance of different financial institutions in more than 21 countries. Majority of the
researches are performed between the years 1990 and 1998 in the U.S. banking industry. It
was emphasized to study the efficiency of banks in regions other than the US since very few
studies were done outside the US. Berger and Humphrey pointed out variations and spread in
estimates of efficiency between non-parametric and parametric methods. Research as well as
critical analysis of observed financial institution efficiency estimates so that the implications
of efficiency results can be addressed in the fields of research, government policy and
managerial performance was done by them.
Mohd Zaini Abd Karim (2001) investigated whether there were significant differences in
bank efficiency across selected ASEAN countries (Indonesia, Malaysia, Philippines, and
Thailand). The study indicated that the major proportion of a total variability is associated
with inefficiency of input used. It also markedly points out the fact that inefficiency tends to
reduce with bank size and increase with government ownership.
David A. Grigorian and Vlad Manole (2002), used both cross-country and cross-regional
settings, and applied the DEA approach, while trying to calculate the correct measure of
commercial bank efficiency in a multiple input/output framework for transition economies,
and to identify the effects of policy framework on the performance of commercial banks. The
results of the study illuminated the fact that banks with a larger market share and a larger
controlling foreign ownership are more likely to be efficient than those with a smaller market
which was owed to their significantly better risk management and operational techniques.
ECONOMIES OF SCALE
Economies of scale measure the relationship between the level of yield and the expense of
delivering an unit of yield. The movement is said to have (increasing) economies of scale
when the normal expense of creating a unit of yield falls as yield increments. It could be
nearby implying that normal expenses may drop for a few levels of creation yield and
afterward later settle or increment. It can likewise be worldwide implying that normal
expenses keep on dropping as yield increments.
Measuring of yields and inputs is hypothetically direct in the assembling and farming
industry. Be that as it may, the proper estimation of yield is less clear while measuring the
scale economies for administration firms. An example of such a circumstance is the health
awareness industry. The test of evaluating the yield is additionally risky in the managing an
account segment because of many-sided quality in measuring yield and perceiving yields
from inputs. The best measure of bank yield is a point on which there is no true general
Asian Journal of Management Sciences & Education Vol. 4(1) January 2015__________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
Copyright © 2015 Leena and Luna International, Oyama, Japan.
45 | P a g e (株) リナアンドルナインターナショナル, 小山市、日本.
ISSN: 2186-845X ISSN: 2186-8441 Print
www.ajmse. leena-luna.co.jp
accord. In different scholarly writings, bank yield has been measured from numerous points
of view like advances, stores, holdings and credits in addition to stores.
The use of average bank cost per dollar of bank assets eliminates the complex problem of
defining a bank’s output. A decline in the average cost ratio as bank size increases implies
that economies of scale exist. An assumption that is implicit while using the average cost per
dollar of assets is that banks’ “true” output is a constant fraction of assets, irrelevant to the
bank’s size. However, if a bank’s output mix varies as it expands or it can use different
technologies thus allowing the bank to produce more services per dollar of bank assets
without resulting in a decline in total cost, then the implicit assumption that all banks’ output
is a constant fraction of assets gives the wrong results.
Our analysis focusses on estimating economies of scale individually for each CB specialty
lending group because the mix of services provided by a CB specialty lender probably does
not change in a systematic way as CBs grow in size.
CCR MODEL
Once the data is given, we measure the value of efficiency of each DMU once and hence
need n optimizations, one for each DMUj to be measured. Let the DMUj to be measured on
any trial be assigned as DMUo where o ranges over 1, 2,..., n.
We now find the solution of the following fractional programming problem to get values for
the input "weights" (vi) {i = l,...,m) and the output "weights" (ur) {r = 1,...,s) which are
variables.
The constraints imply that the fraction of "virtual output" by "virtual input" should not be
more than 1 for each DMU. The main aim is to get weights (vi) and (ur) that maximize the
ratio of DMUo, the DMU which is being measured. Due to the constraints, the optimal
objective value θ* is maximum 1. The constraint for non-negativity (2.5) is insufficient for
the fractional terms in (2.4) to obtain a positive value. We explain this in managerial
language by primarily assuming that all outputs and inputs have some non -zero value and
this is reflected in the weights Ur and Vi which are being designated some positive value.
Substituting the above fractional program (FPo) by the consequent linear program (LPo),
Copyright © 2015 Leena and Luna International, Oyama, Japan.
45 | P a g e (株) リナアンドルナインターナショナル, 小山市、日本.
ISSN: 2186-845X ISSN: 2186-8441 Print
www.ajmse. leena-luna.co.jp
accord. In different scholarly writings, bank yield has been measured from numerous points
of view like advances, stores, holdings and credits in addition to stores.
The use of average bank cost per dollar of bank assets eliminates the complex problem of
defining a bank’s output. A decline in the average cost ratio as bank size increases implies
that economies of scale exist. An assumption that is implicit while using the average cost per
dollar of assets is that banks’ “true” output is a constant fraction of assets, irrelevant to the
bank’s size. However, if a bank’s output mix varies as it expands or it can use different
technologies thus allowing the bank to produce more services per dollar of bank assets
without resulting in a decline in total cost, then the implicit assumption that all banks’ output
is a constant fraction of assets gives the wrong results.
Our analysis focusses on estimating economies of scale individually for each CB specialty
lending group because the mix of services provided by a CB specialty lender probably does
not change in a systematic way as CBs grow in size.
CCR MODEL
Once the data is given, we measure the value of efficiency of each DMU once and hence
need n optimizations, one for each DMUj to be measured. Let the DMUj to be measured on
any trial be assigned as DMUo where o ranges over 1, 2,..., n.
We now find the solution of the following fractional programming problem to get values for
the input "weights" (vi) {i = l,...,m) and the output "weights" (ur) {r = 1,...,s) which are
variables.
The constraints imply that the fraction of "virtual output" by "virtual input" should not be
more than 1 for each DMU. The main aim is to get weights (vi) and (ur) that maximize the
ratio of DMUo, the DMU which is being measured. Due to the constraints, the optimal
objective value θ* is maximum 1. The constraint for non-negativity (2.5) is insufficient for
the fractional terms in (2.4) to obtain a positive value. We explain this in managerial
language by primarily assuming that all outputs and inputs have some non -zero value and
this is reflected in the weights Ur and Vi which are being designated some positive value.
Substituting the above fractional program (FPo) by the consequent linear program (LPo),
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