profitability of islamic bank

8/13/2019 Profitability of Islamic Bank

1/18

PROFITABLITY DETERMINANTS

OF ISLAMIC BANKS:

A COINTEGRATION APPROACH*

Creating Dynamic Leaders

Working Paper Series 004

By

Professor Sudin Haron

Dr Wan Nursofiza Wan Azmi

December 2004

*The paper was presented at the Islamic Banking Conference, Union Arab Bank, Beirut, Lebnon,5-7 December 2004.


2/18

TABLE OF CONTENTS

Protability Determinants of Islamic Banks:A Cointegration Approach

Abstract 2

Introduction 2

Literature Review 3

Methodology 6

Data Description 7

Empirical Findings 10

Conclusion 15

Abstract

Studies that measure the inuence of vari-

ous factors that determine the protability

of Islamic banks are still at the initial stage.

This is the rst attempt to investigate the

strength of inuence between both internal

and external variables and protability of Is-

lamic banks in selected countries using time-series techniques of cointegration and er-

ror-correction mechanism. This study found

a signicant long-run relationship between

protability measures of Islamic banks and

determining variables such as liquidity, de-

posit items, assets structure, ination and

money supply. However, dynamic short-run

analysis indicated a slow adjustment whichimplies that protability of Islamic banks

does not respond speedily to changes in the

explanatory variables in the short-run.

Introduction

In the last four decades, many studies have been

conducted to investigate the protability determi-

nants of conventional banks. Since the pioneering

work of Hester and Zoellner (1966), which mea-

sured the relationship between items in the balance

sheet and earnings of banks in the US, studies of

bank protability have expanded to the international

level (see for example Short, 1979; Bourke, 1989;

Molyneux and Thornton, 1992; and Steinherr and

Huveneers, 1994). In the Islamic banking literature,

the empirical work of Haron (1996a) was the rst at-

tempt to investigate factors that contributed towards

the protability of Islamic banks. However, most of

Creating Dynamic LeadersPage 2


3/18

the research used multiple regression analy-sis in measuring the relationship between the

determining factors and protability ratios. In

contrast to other studies, Chirwa (2003) ap-

plied time-series techniques of cointegration

and error-correction methods to test the struc-

ture-conduct-performance hypothesis and de-

termine whether a long-run relationship exists

between the prots of commercial banks and

concentration in the banking industry.

Cointegration analysis, introduced in the mid-1980s, has been regarded by many econome-

tricians as the most important development in

empirical modelling (Charemza and Deadman,

1992). Cointegration enables the estimation of

a relationship among non-stationary variables

where cointegration in the variables simply re-

veals the existence of a long-run equilibrium

relationship among them. Error correction

model (ECM), which is derived from cointegra-

tion, shows how this equilibrium relationship

is achieved, i.e. indicates the short-term dy-

namics in the movement towards this long-run

equilibrium.

Extending the work of Haron (1996a, 1996b,

2004), this paper investigates the strength of

inuence between both external and internal

variables and the protability of Islamic banks

using the cointegration and error-correction

methodology. To the best of our knowledge,

this is the rst study which employs such anadvance time series econometric techniques to

determine the protability of Islamic banks.

The paper is structured into 7 sections. Section

2 contains a brief review of the literature. Sec-

tion 3 discusses the methodology employed.

Section 4 provides the description of the data.

Section 5 presents the empirical results. Fi-

nally, Section 6 summarises the main ndings

and gives the conclusion of the study.

Literature Review

Researchers have examined and identied

various factors that have signicant inuence

on banks protability. In addition to dividing

the protability determinants into two catego-

ries, i.e. internal and external, these studies

have been able to postulate some protability

theories related to banking. Among the theo-

ries in the bank protability literature are the

structure-conduct-performance theory (Bain,

1951), efcient-structure theory (Demsetz,

1973; Peltzman, 1977), expense-preference

theory (Becker, 1957; Williamson, 1963) and

risk-aversion theory (Galbraith, 1967; Cave,

1970). However, ndings on the existence of

protability theories in banking vary among

the researchers. Majority of the previous prof-

itability studies have been of conventional

banks (see among others Hester and Zoellner,

1966; Emery, 1971; Mulllineaux, 1978; Kwast

and Rose, 1982; Smirlock, 1985; Molyneuxand Thornton, 1992; Steinherr and Huveneers,

1994). Only a handful of researches have been

conducted to determine the protability of Is-

lamic banks (see for example Haron, 1996a,

1996b, 2004 and M. Bashir, 2003).

Conventional bank protability studies involv-

ing internal determinants were pioneered by

Hester and Zoellner (1966), followed by Has-

lem (1968, 1969), Fraser and Rose (1971),

Mullineaux (1978), Smirlock (1985) andStienherr and Huveneers (1994) among oth-

ers. For an extensive literature on the effects

of internal determinants on bank protabil-

ity, see articles by Haron (1996a, 2004). In-

ternal variables can be broadly classied into

two categories: nancial statement variables

and non-nancial statement variables. The -

nancial statement variables are related to the

management of the balance sheet and income

statement. The balance sheet management is

directly related to assets and liabilities man-



4/18

agement. Hester and Zoellner (1966) studiedthe relationship between balance sheet items

and banks earnings and found signicant re-

lationships. Asset items showed positive as-

sociation whilst liability items had an adverse

effect on prots. Similarly, Mullineaux (1978)

established that balance sheet structure had

a signicant impact on protability. However,

depending on the nature of the items on the

balance sheet, the relationship can either be

negative or positive.

Pertaining to deposit structure, Heggested

(1977) reported that time and savings depos-

its had a signicant inverse relationship with

protability. Smirlocks (1985) ndings indi-

cated a signicant positive relationship be-

tween demand deposits and prots. In con-

trast, Fraser and Rose (1971) found that loan

rate; time deposit rate and loan-to-deposit ra-

tio had no effect on protability. Bourke (1989)

and Molynuex and Thorton (1992) found that

capital and staff expenses were positively re-

lated to banks protability. Similar relation-

ship was ascertained for overhead expenditure

by Steinherr and Huveneers (1994). Income

statement management, on the other hand, is

directly related to income and expense man-

agement. Areas such as managing interest

sensitivity and margin, allocation of expens-

es, and priority in expenditure are considered

to have an impact on a banks total income

and expenses (Haslem, 1968; and Fraser andRose, 1971).

Non-nancial statement variables encompass

variables that have an indirect relationship with

items in the nancial statements and include

the number of branches, status of branches,

location and size of branches and banks. The

number, status and location of branches are

regarded as controllable variables when deci-

sions related to them are within the discretion

of management. Likewise, size is considered

as an internal determinant on the postulationthat it is the responsibility of bank manage-

ment to expand the organisation through the

acquisition of additional assets and liabilities

(Steinherr and Huveneers, 1994). Investigat-

ing the effect of location and size on protabil-

ity, Emery (1971) and Vernon (1971) reported

a signicant relationship for location, whilst

Mullineaux (1978) found similar relationship

for size. On the contrary, studies by Vernon

(1971), Kwast and Rose (1982), Heggested

(1977) and Smirlock (1985) found that size

had no effect on protability. With regards

to number of branches, Hester and Zoellner

(1966) did not nd any effect this variable had

on a banks prot level.

Several external factors have been identied

in the conventional banking literature as hav-

ing an impact on protability. External factors

considered include regulation, competition,

concentration, market share, ownership, mon-

ey supply, ination and bank size. An exten-

sive discussion of this can be found in Haron

(1996b and 2004). Regulation is considered as

one of important determinants of prots for

conventional banks since the banking industry

is highly regulated. Regulation in the industry

is normally imposed on bank management and

the industry itself. Direct regulations on bank

management cover lending policy, deposit pol-

icy, interest rates and liquidity requirements.

In the banking system, regulations include thecondition of entry, establishment of new ven-

tures, mergers and acquisitions. Studies by Pel-

zman (1968), Vernon (1971), Emery (1971),

McCall and Peterson (1977), Mullineaux (1978)

and Smirlock (1985) concluded that regulation

had a signicant impact on banks protability.

Fraser and Rose (1972) found conicting re-

sults when examining whether the opening of

new institutions had any signicant effect on

the protability of competing institutions.




5/18

The rst researcher who measured the effectsof competition on bank protability was Emery

(1971). He used market entry as a proxy for

competition and found that competition had no

signicant impact on prots. Heggested and

Mingo (1976) used market structure instead

and found that market power of an individual

bank increases with the degree of monopoly.

Amongst the researchers who have examined

the effect of concentration on protability are

Emery (1971), Vernon (1971), Fraser and

Rose (1982) and Smirlock (1985). The nd-

ings of Emery; and Fraser and Rose indicated

that concentration had a signicant positive

relationship with prots. Vernon, on the other

hand, found an inverse relationship between

them. The effect of concentration was insig-

nicant in Smirlocks study.

Market share is also considered a determi-

nant of protability under the assumption that

the greater the market share, the greater is a

banks control over the prices and services it

offers to its customers. This assumption was

veried by Heggested and Mingo (1976). How-

ever, Heggested (1977) and Mullineaux (1978)

found that market share is inversely related to

protability. In a related study, Short (1979)

believed that government ownership would

have an impact on protability on the grounds

that government banks are non-prot oriented

banks. This conrms the hypothesis that the

higher amount of a banks capital owned bythe government, the lower is the prot gener-

ated by these banks. Molyneux and Thornton

(1992) also found a signicant positive rela-

tionship between ownership and protability.

In the case of growth in the market, Bourke

(1989) believed that market expansion could

produce a capability for earning increased

prots. In his study and a similar study by Mo-

lyneux and Thornton (1992), they found that

market expansion, represented by growth in

money supply, had a signicant relationshipwith prots. Revell (1980) contended that in-

ation could also be a factor contributing to

the variations in a banks protability. He pro-

posed that ination affected banks through a

number of different routes such as interest

rates and asset prices, exchange rates and

operating costs.

Finally, Emery (1971) and Vernon (1971)

were among the earliest researchers to link

bank size with protability. The size of a bankis associated with the concept of economies

of scale. Economic theory postulates that if

an industry is subject to economies of scale,

large institutions will be more efcient and

thus are able to produce services at a lower

cost, ceteris paribus. Since large banks are as-

sumed to enjoy economies of scale, they are

able to produce their outputs or services more

cheaply and efciently than can small banks.

As a result, large banks will earn higher rates

of prot if entry is restricted. Smirlock (1985)

believed that large banks are likely to have

greater product and loan diversication. This

increased in diversication implies less risk

and hence a lower required rate of return.

Within the Islamic banking literature, Haron

(1996a, 1997b, 2004) identied internal and

external factors that contributed towards the

protability of Islamic banks. Haron (1996a)

found evidence to suggest that all three sourc-

es of funds (current, savings and investment

accounts) for Islamic banks are positively re-

lated to protability. His study validates the

current practices of Islamic banks which use

mark-up principles in their nancing activities

where an inverse relation between prot-shar-

ing principles and protability measure ratios

were found. Other internal variables which

were found to have a signicant positive re-

lationship with prot include liquidity, capital

and reserves and total expenses.



6/18

In another study, Haron (1996b) examined theimpact of external factors which may have an

inuence on the protability of Islamic banks.

The author identied competition, regulation,

market share, interest rate, money supply, in-

ation and bank size as the external determi-

nants.

An interesting nding reported by Haron was

that Islamic banks which operate in a competi-

tive market earned more than those operat-

ing in a monopolistic market. Furthermore, hisndings suggest that the theory which posits

that the bigger the share of bank in the mar-

ket, the more protable it would be does not

apply to Islamic banks. Similar results were

established for money supply. However, Ha-

ron found that interest rate, ination and size

have signicant positive impact on the prots

of Islamic banks. These results conrm to the

empirical ndings in the conventional banking

literature.

Unlike the works of Haron (1996a, 1996b)

which used international data, M. Bashir

(2003) examined the determinants of prot-

ability in Islamic banks operating in the Middle

East. Analogous to the studies by Haron, M.

Bashir divided these determinants into internal

and external factors. Several conclusions were

reached. Firstly, he found a positive relation-

ship between capital ratio, loan ratio, foreign

ownership and favourable macroeconomic en-

vironment with protability. Secondly, taxes

and reserve ratio were found to have an in-

verse and statistically effect on Islamic banks

performance. He also found evidence to sup-

port the importance of consumer and short-

term funding, non-interest earning assets and

overheads in promoting banks revenues.

In his recent article, Haron (2004) examined

jointly the effect of both internal and external

factors that contributed towards the protabil-

ity of Islamic banks. His study found that in-

ternal factors such as liquidity, total expendi-

tures, funds invested in Islamic securities, and

the percentage of the prot-sharing ratio be-

tween the bank and the borrower of funds are

highly correlated with the level of total income

received by the Islamic banks. Similar effects

were found for external factors such as interest

rates, market share and size of the bank. One

of the signicant contributions of Harons work

is that Islamic banks in a competitive market

were found to be better managed than theircounterparts. Therefore, Haron believed that

protectionism policy adopted by some Muslim

governments is inappropriate and could distort

future development of Islamic banking.

Methodology

This paper uses cointegration and error cor-

rection model which are all conducted within

a vector autoregression (VAR) framework, to

examine the factors that determine the prof-

itability of Islamic banks. These techniques

represent recent advances in time series

econometric. The concept of cointegration was

introduced by Granger (1983, 1986) and fur-

ther developed by Engle and Granger (1987).

Cointegration enables the estimation of a re-

lationship among non-stationary variables

where cointegration in the variables simply re-

veals the existence of a long run equilibrium

relationship among them.

However, when using the VAR model to analyse

economic relationships, all variables are re-

quired to be stationary. Hence, it is necessary

to rst test for the stationarity of each vari-

able by conducting unit root tests. To do this,

the paper employed the Augmented Dickey-

Fuller (ADF) test. A multivariate test for coin-

tegration developed by Johansen (1988) and




7/18

Johansen and Juselius (1990) is used in thisstudy. The Johansen-Juselius (JJ) procedure of

cointegration test is based on the maximum

likelihood estimation of the VAR model. The

test is carried out through a VAR system such

as follows:

Pt = 1 Pt-1 + 2 Pt-2 + . . . + k Pt-k

+ + t , t = 1, . . . , T (1)

where Pt is a (n 1) vector of I(1) variables;i are (n n) matrices of parameters; is

a (n 1) vector of constant; t is a vector

of normal distributed error with zero mean

and constant variance; and k is the maximum

number of lag length processing the white

noise. Differencing equation (3), the system

can be rewritten as:

Pt = 1Pt-1 + . . . + k Pt-k + Pt-1

+ + t (2)

denes the impact matrix, which relates the

change, Pt to the levels, Pt-k of k periods

earlier. The rank of determines the number

of distinct cointegrating vector, r. If the rank of

is zero, then there are no combinations of

the variables which are stationary, i.e. there

are no cointegrating vectors. Hence, equa-

tion (2) is reduced to a standard VAR model

of the rst difference. If is of full rank, then

all variables are stationary. If the rank is rsuch that (0 < r < n), then there is cointegra-

tion between the variables with r cointegrating

vectors. The trace and maximum eigenvalue

statistics are calculated to test for the pres-

ence of r cointegrating vectors.

If cointegration is found, error correction mod-

els are constructed. However, if no cointegra-

tion is found, the analyses will be based on

the regression of the rst differences of the

variables using a standard VAR model. Error

correction model (ECM), which is derived fromcointegration, shows how this equilibrium re-

lationship is achieved. According to Engle and

Granger (1987) cointegration implies, and is

implied by, the existence of an error correc-

tion term. This means that changes in the de-

pendent variable are a function of the level of

disequilibrium in the cointegrating relationship

(captured by the error correction term) as well

as changes in other explanatory variables.

Once the variables are found to be cointegrat-

ed, a vector correction model (VECM) will be

used to investigate the dynamic interactions

among them in the system. The Granger rep-

resentation states that for two cointegrated

variables, an ECM can be found in the follow-

ing form:

Yt = 0 + 1Xt + 2t-1 + t (3)

where t-1 represents the error correction

term which captures the adjustment toward

the long-run equilibrium and 2 is the short-

run adjustment coefcient.

Data Description

The data for this study are pooled time-se-

ries cross-sectional data taken from the an-

nual reports of Islamic banks from various

countries. The banks chosen are Bank IslamMalaysia Berhad (Malaysia), Islamic Bank of

Bangladesh (Bangladesh), Dubai Islamic Bank

(United Arab Emirates), Jordan Islamic Bank

(Jordan) and Albaraka Islamic Investment

Bank (Bahrain). Sample period for this study

is from 1984 to 2002.

In line with previous studies on bank protabil-

ity, this study also divides protability deter-

minants into two categories, namely, internal

and external variables. The summary of the in-



8/18

dependent variables used in the study is givenin Table 1. Haron (1996a) argued that Islamic

banks are indeed commercial banks but oper-

ate on an interest-free basis. Hence, internal

variables such as liquidity, capital structure,

deposits structure, nancing structure and

expenditure items which inuence the prot-

ability of conventional banks are hypothesised

to have similar impact on the performance of

Islamic banks.

The variable LIQ is expected to have a positiverelationship with protability (Molyneux and

Thornton, 1992; Steinherr and Huveneers,

1994; and Haron, 2004). The ratio CRTA is

used as a proxy for measuring the impact of

capital structure on protability. It is posited

that the higher amount of capital injected,

the more condent customers will be and

the more deposits that will be placed at the

bank. Bourke (1989), Molyneux and Thorn-

ton (1992), Steinherr and Huveneers (1994)

and Haron (1996a) found a positive relation-

ship between capital structure and protability

measures ratios which where deated against

total assets.

Deposit structure is represented by three vari-

ables, i.e. current (DECA), savings (DESA)

and investment (DEIA) accounts. Hester and

Zoellner (1966) and Heggested (1977) found

that savings and time deposits were inversely

related to protability, while a positive rela-

tionship has been found for current account

deposits by Smirlock (1985). Under assets

structure, the two variables for earning assets

used in this study are FIPS and FIMK.

The ndings of previous research indicated that

asset items have a positive relationship with

protability. However, Haron (1996a) found

that for Islamic banks, where a relationship

existed, asset items had an inverse relation-

ship with protability measures. In the case

of expenditure items, total operating expen-ditures (TEXP) is used as a proxy. TEXP is hy-

pothesised to be inversely related with prot.

External variables, on the other hand, are

variables outside the control of bank manage-

ment. The external variables used in this study

are market share, money supply, interest rate,

ination and size of the bank. Market share is

considered as one of the determinants of prof-

itability since the bigger the market, the larger

is the banks potential prots. Market share is

represented by the ratio MKTSH.

According to Short (1979) and Smirlock (1985),

market share is positively related to prots.

However, Heggested (1977) and Mullineaux

(1978) found otherwise. As in Bourke (1989),

money supply was used as a proxy for market

growth. The author believed that growth in to-

tal market may be considered as a potential

variable in the sense that an expanding market

would produce an environment for increasing

prots. In his study, Haron (1996b) reported

a positive relationship between money supply

and the protability of Islamic banks.

Although interest is prohibited in Islamic bank-

ing, Islamic banks operate in an environment

where interest rates do exist. Hence, it is pro-

posed that the interest rate variable (INT) be

included in this study so as to observe wheth-

er INT have any indirect impact upon Islamicbanks prots. Haron (1996b) observed that

INT is closely related to the protability level

of Islamic banks.

This paper uses Consumer Price Index (CPI) as

a proxy for ination. Studies by Bourke (1989)

and Molyneux and Thornton (1992) established

a signicant positive relationship between in-

ation and prots. Similarly, Haron (1996b)

found that CPI had a positive relationship with

all protability measures but the relationship




9/18

Variables Represented By Source

INTERNAL

Liquidity

Capital Structure

Deposits Structure

Assets Structure

Expenditure Item

Total financing as a percentage of total deposits(LIQ)

Capital and reserves as a percentage of total assets(CRTA)

Total deposits in current accounts as a percentage oftotal assets (DECA)

Total deposits in savings accounts as a percentage oftotal assets (DESA)

Total deposits in investment accounts as a percentageof total assets (DEIA)

Total funds in profit-loss sharing principles as a per-centage of total assets (FIPS)

Total funds in mark-up principles as a percentage oftotal assets (FIMK)

Total expenditure as a percentage of total assets(TEXP)

Samples annual report








EXTERNAL

Market Share

Money Supply

Interest Rate

Inflation

Size

Total deposits of the Islamic banks as a percentage ofa countrys total deposits (MKTSH)

Growth in money supply (M2) for each country foreach year (MON)

The discount rate for each country for each year(INT)

Percentage increase in consumer price index for eachcountry for each year (CPI)

Total assets in common currency (US dollar) in loga-

rithm (LogSIZE)

Samples annual report andIMF Financial Statistics

IMF Financial Statistics




was not statistically signicant. It is also hy-

pothesised that ination will have a positive

impact on Islamic banks. This study consid-

ers the size of bank in logarithm (LogSIZE) as

an external variable. Short (1979) found that

LogSIZE was positively and signicantly corre-

lated to protability. On the contrary, Steinherr

and Huveneers (1994) found this to be insig-

nicant. Harons (1996b) study indicated that

the larger the banks size, the higher is the

Table 1: Independent variables used in the study



10/18


total income accruing to the bank. In additionto the above independent variables, this study

replicates the work of Haron (1996a, 1996b,

2004) and thus, uses the following variables

as proxies for protability:

Variable Proxy

TITA Total income as a per-

centage of total assets

BITA Banks portion of in-

come as a percentage of

total assets

ATCR Net profit after taxes as

a percentage of capital

and reserves


The rst ratio, TITA, is used to capture the ef-

fects of internal and external determinants on

a banks protability. Similarly, BITA ratio will

also capture the effect of these determinants

on protability. It is expected that all determi-

nants will have similar impacts on both TITA

and BITA. On the other hand, the ATCR ratio

measures the effects of protability determi-

nants on returns to shareholders. Hence, TITA

and BITA capture the effects of determinants

on protability, while ATCR measures the ef-

fects of determinants on the potential incomes

to shareholders.

Empirical Findings

In line with Granger (1986), a necessary but

not sufcient condition for cointegration is

that each of the series should be integrated

of the same order. Accordingly, each series is

tested for stationarity. The null hypothesis for

the presence of a unit root (non-stationarity)

is tested using ADF test both with and without

a time trend. The stationarity test results arepresented in Table 3.

The test is applied to both levels as well as to

the rst differences of the series. For series

levels, the null hypothesis cannot be rejected

at the 5% signicance level. However, when

the data are differenced, non-stationarity can

be rejected for all data series. This nding is

not sensitive to the inclusion of a deterministic

trend variable in the ADF regression equation.

Hence, the results imply that each data seriesare integrated of order one, i.e. I(1).

Given that all the data series are I(1), the next

stage in the study is to test for the presence

of cointegration. In this analysis, the JJ proce-

dure of cointegration test based on the maxi-

mum likehood estimation of the VAR model is

employed. Table 4 and 5 present the results of

the cointegration tests. In all cases, a single

cointegrating equation is observed from both

the trace and maximum eigenvalue statistics.

The ndings imply that a single-long-term re-

lationship exists among the variables under

consideration. Therefore, it can be concluded

that the prot models are cointegration re-

gressions.

Having established the presence of a single

contegrating vector, we tested whether each

of the variables enter the cointegrating vector

signicantly by way of imposing restrictionsand likelihood ratio tests which are asymptoti-

cally distributed as a chi-squared distribution

with one degree of freedom. Table 6 reports

results of the Johansens cointegration test for

internal variables.

Table 2: Proxies of protability


11/18

Table 3: The ADF test statistics for a unit root

Note: * indicates the 5% level of signicance

Table 4: Cointegration test statistics of the internal variables

Note: * indicates rejection of the null hypothesis at the 5% level ofsignicance



12/18



Table 5: Cointegration test statistics of the external variables

Note: * indicates rejection of the null hypothesis at the 5% level of signicance

Table 6: Cointegration results for internal variables

*, ** and *** denotes signicant at 1%, 5% and 10% level.

This study found that liquidity had a signicant

positive relationship with TITA and BITA, but

not signicant with ATCR. The positive relation-

ship between protability ratios and liquidity is

in line with the ndings of Haron (1996a) and

the conventional banking theory which postu-

lates that an increase in nancing is followed

by an increase in prots. A signicant relation-

ship was also found between capital structure

and BITA, but not with TITA and ATCR which

implies that additional capital will not generate

more income for the bank. In the case of BITA,

for every 1% increase in capital the percent-

age of BITA would increase by 0.1%.


13/18

Amongst the deposit structure variables, DEIAwas the only variable which had a signicant

relationship with all three protability ratios.

For DECA, a positive relationship was found

with BITA. The result indicates that a 1% in-

crease in current account holdings will increase

the banks portion of income by 0.064%. Giv-

en that current account facility is a cost-free

service, the more funds deposited into this ac-

count, the higher prots will be made available

to Islamic banks.

Intriguingly, DECA had no signicant relation-

ship with TITA implying that an increase in cur-

rent accounts does not generate more income

to the bank, but only function as a cost saving

measure. On other words, Islamic banks do

not pay any rewards to their depositors. These

results are in line with the ndings of Haron

(1996a, 2004). DESA was found to have a sig-

nicant positive relationship with TITA. Every

1% rise in savings account, total income will

increase by 0.26%. This is in line with nor-

mal banking practices whereby Islamic bank

could use the funds deposited in this account

for productive purposes and thus, generating

additional revenue for the bank.

As for assets structure variables, both FIPS and

FIMK were found to have a signicant but in-

verse relationship with protability measures.

For every 1% increase in FIPS, total income

will decrease by 0.092%. This nding couldsupport the existing perceptions and attitudes

of Islamic bankers, whereby prot sharing

principles (musyarakah and mudharabah) are

considered the most risky principles in Islam-

ic banking business. Lack of monitoring pro-

grams could also lead to the high occurrences

of non-performing loans for loans given based

on prot sharing principles.

In the case of FIMK, it had negative relation-

ship with TITA and BITA. Each 1% increase in

FIMK will decrease TITA by 2.686% and BITAby 0.042%. This nding is in contradiction

to the standard banking practices. In gener-

al, additional nancing would increase banks

revenue. However, there is a possibility that

because of the high concentration of funds in

FIMK led to less charges imposed to customers

and thus, resulting in an inverse relationship

with TITA and BITA.

Total expenditure is found to have an inverse

relationship with TITA and BITA and a posi-

tive relationship with ATCR. However, a signi-

cant relationship is only found with TITA. This

is hard to explain because expenditure items

usually have a positive relationship with total

income. One possible reason for this is that

the expenses incurred did not contribute to

the income generated activities.

The cointegration results for external variables

are presented in Table 7 below. MKTSH and

LOGSIZE were found not to have any signi-

cant relationship with all three protability

measures. These ndings are not in line with

ndings of Haron (1996b). In most cases mar-

ket share and size of bank have direct positive

relationship with revenues. This study found

that interest rate (INT) is only positively sig-

nicant with ATCR.

CPI was found to have a positive signicant re-

lationship with all protability measures, con-

rming to the ndings of Bourke (1989) and

Molyneux and Thorton (1992). The study also

found a positive relationship between money

supply and TITA and BITA. This nding con-

rmed to the work of Haron (1996b) and con-

cludes that growth in the economy as proxies

by money supply is shared by Islamic banks.

Since all the protability measures and their

corresponding explanatory variables exhibit

cointegrating relationships, VECM were esti-



14/18



Table 7: Cointegration results for external variables

*, ** and *** denotes signicant at 1%, 5% and 10% level

mated to model short-run dynamics. The size of the error-correction term (ECT) measures thespeed at which protability measures adjust to the change in equilibrium conditions. Results

from the VECM tests are reported in Table 8 and 9.

Table 8: Error-correction models for internal variables

Table 9: Error-correction models for external variables


15/18

The results in Table 8 reveal that the ECT isnegative and statistically signicant for all prof-itability measures in the case of internal vari-ables. This implies that TITA, BITA and ATCRare adjusting to any deviations in the long runequilibrium relationship. In other words, neg-ative deviations are rectied by increases inprotability. The coefcients of ECT, however,are found to be small in magnitude. The nd-ings demonstrate a slow adjustment processtowards a change in the equilibrium condi-tions. However, it can be observed from Table8 that Islamic banks protability as measuredby BITA adjusts in the short-run in responseto a reduction in the funds in prot-sharingnancing activities.

For the external determinants, the correspond-ing error correction terms for all protabilitymeasures are highly signicant and have thecorrect negative sign as shown in Table 9. Alikeresults from the previous table, the protabil-ity measures were also found to have a slowspeed of adjustment towards long-run equi-librium. However, contemporaneous change in

ination rate and money supply signicantlyinuence changes in BITA and ATCR.

Conclusion

This study employed cointegration approach inmeasuring the relationship between determi-nants variables and protability measures ofIslamic banks. Since this is the rst attemptto investigate such relationship using advancetime-series technique, we believe the ndings

of this study could be used to compare previ-ous ndings of similar studies. This study could

serve as impetus for future works related toIslamic banking literature.

One of the important ndings from this studyis that some of the determinants have signi-cant inuence on protability. Factors such asliquidity, deposit items, assets structure, ina-tion and money supply must be closely moni-tored by banks managers. This is because allof these items are statistically signicant whichimplies that any changes in the variables willhave a long term impact on protability. How

-

ever, with regards to net prot, variables thathave signicant inuence are funds depositedin the investment account, ination and mon-ey supply.

Finally, this study also measures the speedof adjustment process towards the long-runequilibrium. Although the above mentionedvariables were found to have a long run rela-tionship with protability, Islamic banks prot-ability as measured by TITA, BITA and ATCRadjust slowly in the short-run to deviations inthe cointegrating relationship. In other words,protability of Islamic banks does not respondspeedily to changes in the explanatory vari-ables in the short-run. One of the possiblereasons that can be linked to the insignicantshort-term relationship is that the operationsof Islamic banks are based on Shariah prin-ciples.

REFERENCES

Ahmad, Ausaf (1987), Development and Prob-lems of Islamic Banks, Jeddah (Saudi Arabia,IRTI, Islamic Development Bank.

Ahmad, Ziauddin (1983), Comments onVolker Nienhaus: Protability of Islamic banksCompeting with Interest Banks. Journal ofResearch in Islamic Economics, Vol. 1, No 1(Summer), 66-68.

Ahmad, Ziauddin (1994), Islamic Banking:State of The Art. Islamic Economic Studies,Vol 2 No 1, December, 1-33.

Al-Baraka Islamic Investment Bank of Bah-rain, Annual Report, various issues, Manama(Bahrain).

Bahrain Islamic Bank, Annual Report, variousissues, Manama (Bahrain).

Bank Islam Malaysia Berhad, Annual Report,

various issues, Kuala Lumpur (Malaysia).



16/18


17/18

sis of the Relative Protability of CommercialBanks, Journal of Finance, 23, 167-176.

Haslem, John A., (1969), A Statistical Estima-tion of Commercial Bank Protability, Journalof Business, 42, 22-35.

Hassan, Naim A., (1993), Measurement of Fi-nancial Performance of Islamic Banks vis-a-visWestern-Type Commercial Banks: Some Con-ceptual Differences, A paper presented at anInternational Conference on Islamic Banking,Sydney, November.

Heggested, Arnold A. (1977), Market Struc-ture, Risk, and Protability in CommercialBanking. Journal of Finance, 32 (September),1207-16.

Heggested, Arnold A. (1979), Market Struc-ture, Competition, and Performance in Finan-cial Industries: A Survey of Banking Studies.In Issues in Financial Regulation, Franklin R.Edwards (ed), New York, USA, McGraw-Hill,449-90.

Heggested, Arnold A. and John J. Mingo (1976),Price, Non-prices, and Concentration in Com-mercial Banking. Journal of Money, Credit,and Banking, 8 (February), 107-17.

Heggested, Arnold A., (1977), Market Struc-ture, Risk, and Protability in CommercialBanking, Journal of Finance, 32, 1207-1216.

Hester, Donald D. and John F. Zoellner, (1966),The Relation Between Bank Portfolios andEarnings: An Econometric Analysis, Review ofEconomics and Statistics, 48, 372-386.

Homoud, Sami Hassan (1994), Progress ofIslamic Banking: The Aspirations and the Re-alities. Islamic Economic Studies, Vol 2 No 1,December, 71-80.

International Monetary Fund, InternationalFinancial Statistics, various monthly issues,Washington (USA),

Islami Bank Bangladesh Limited, Annual Re-

port, various issues, Dhaka (Bangladesh).

Islamic Development Bank (1989), StatisticalMonograph No 8, Jeddah, Saudi Arabia.

Islamic Development Bank (1994), StatisticalMonograph No 14, Jeddah, Saudi Arabia.Johansen, S., (1988), Statisitical Analysis ofCointegraiton Vectors, Journal of economicDynamics and Control, 12, 231-254.

Johansen, S. and K. Juselius (1990), MaximumLikelihood Estimation and Inference on Coin-tegration With Application to the Demand forMoney, Oxford Bulletin of Economics and Sta-

tistics, 52, 169-210.

Jordan Islamic Bank, Annual Report, variousissues, Amman (Jordan).

Khan, M. Fahim (1983), Comments on VolkerNienhaus: Protability of Islamic banks Com-peting with Interest Banks. Journal of Re-search in Islamic Economics, Vol 1, No 2 (Win-ter), 73-78.

Kuwait Finance House, Annual Report, various

issues, Safat (Kuwait).

Kwast, Mayron L., and John T. Rose (1982),Pricing, Operating Efciency, and ProtabilityAmong Large Commercial Banks. Journal ofBanking and Finance, Vol 6 No 2 (June), 233-254.

Lindley, James T., James A. Verbrugge, JamesE. McNulty, and Benton E. Gup (1992), In-vestment Policy, Financing Policy, and Perfor-mance Characteristics of De Novo Savings andLoan Associations. Journal of Banking and Fi-nance, Vol 16, 313-330.

M. Bashir, Abdel-Hameed (2003), Determi-nants of Protability in Islamic Banks: SomeEvidence from the Middle East, Islamic Eco-nomic Studies, Vol 11, No. 1, 31-60.

McCall, Alan S. and Manferd O. Peterson(1977), The Impact of De Novo Commercialbank Entry. Journal of Finance, Vol 32, No 5(December), 1587-1604.

Mirakhor, Abbas (1987), Short-term Assets



18/18

Concentration and Islamic Banking, in MohsinS. Khan and Abbas Mirakhor, eds.: TheoreticalStudies in Islamic Banking and Finance, Insti-tute for Research and Islamic Studies, Hous-ton.

Molyneux, Philip and John Thornton, (1992),Determinants of European Bank Protability:A Note, Journal of Banking and Finance, 16,1173-1178.

Mullineaux, Donald J., (1978), Economies ofScale and Organizational Efciency in Bank-

ing: A Prot-Function Approach, Journal of Fi-

nance, 33, 259-280.

Nienhaus, Volker (1983), Protability of Is-lamic banks Competing with Interest Banks.Journal of Research in Islamic Economics, Vol1, No 1 (Summer), 37-47.

Peltzman, Sam (1968), Bank Stock Pricesand the Effects of Regulation of the BankingStructure. Journal of Business, Vol 41, No 4(October), 413-430.

Revell, J.R.S.(1980), Costs and Margins inBanking: An International Survey, Paris, Or-ganization for Economic Co-operation and De-velopment.

Rhoades, Stephen A., (1980), Entry and Com-petition in Banking, Journal of Banking andFinance, Vol 4, No 2 (June), 143-150.

Short, Brock K. (1979),The Relation BetweenCommercial Bank Prot Rates and Banking

Concentration in Canada, Western Europe andJapan, Journal of Banking and Finance, 3, 209-219.

Smirlock, Michael (1985),Evidence on the(Non) Relationship Between Concentrationand Protability in Banking. Journal of Money,Credit and Banking, Vol 17, No 1(February),69-83.

Steinherr, A., and Ch. Huveneers (1994), Onthe Performance of Differently Regulated Fi-nancial Institutions: Some Empirical Evidence.

Journal of Banking and Finance, Vol 18, 271-

306.

Vernon, Jack R. (1971), Separation of Owner-ship and Control and Prot Rates, the Evidencefrom Banking: Comment. Journal of Financialand Quantitative Analysis, Vol 6 No 1 (Janu-ary), 615-625.


profitability of islamic bank

Documents