MONETARY POLICY SHOCKS AND ISLAMIC
BANKS’ DEPOSITS IN A DUAL BANKING SYSTEM:
A COMPARATIVE ANALYSIS BETWEEN
MALAYSIA BAHRAIN
Rosylin
Mohd Yusof
Associate
Professor
Kulliyyah
of Economics and Management Sciences
International
Islamic University Malaysia
53100
Gombak, Kuala Lumpur
Mohammed
Al Wosabi
Assistant
Professor
College
of Business and Administration, University
of Bahrain
M.
Shabri Abdul Majid
Assistant
Professor
Kulliyyah
of Economics and Management Sciences
International
Islamic University Malaysia
53100
Gombak, Kuala Lumpur
ABSTRACT
The objective of the paper is to empirically explore
the dynamic inter-relationships between deposits of Islamic banks with monetary
policy variables in Bahrain Malaysia Malaysia Bahrain
Keywords:
monetary policy; Islamic and conventional banks; auto-regressive distributed
lag (ARDL) model; vector error-correction model (VECM); multi-variate causality
1.
INTRODUCTION
Studies supporting the merits of an interest-free monetary and banking
system have been extensive. In general,
these studies propose that the relative monetary stability accorded by an
interest-free monetary system is due to its asset-linked nature as compared to
the interest-based system which is subjected to the fluctuations in the
interest rate levels. A monetary system
which is relying on interest-free assets eliminates the element of
speculation. Due to this, it is proposed
to be more predictable and has reliable link to the policy objectives, thus can
be effectively controlled by the monetary authority. Consequently, there is a general
belief that the Islamic banking system is somewhat shielded from the risks
associated with interest rate fluctuations and is more stable compared to the
conventional banking system. Khan (1985)
further suggests that the Islamic financial market is able to weather economic
and financial crisis better. In line with this, current research efforts in
this area are mainly focused towards developing and evaluating the demand for
Islamic monetary instruments and demonstrating the validity and effectiveness
of these instruments for monetary policy purposes.
In the last
decade, the empirical literature in the area of Islamic banking has been
focused on product and development as well as the viability of Islamic banking
in the current financial intermediation process. We find that there is a lack of research
interest in the area of monetary policy from the Islamic perspective in
general, and monetary transmission mechanism, in particular. With the increasing role that the Islamic
banks are playing in both Malaysian and Bahrain Malaysia Bahrain
In the finance literature, interest
rate risk can be broadly defined as the impact of interest rate changes on a
bank's profitability, cash flows as well as net worth (Batcha, 2007). Financial
intermediaries such as commercial banks (both Islamic and conventional) are inherently
exposed to interest rate risk particularly due to the fact that they have
little control over the deposit structure of the banks. An increase in interest
rate signals a higher cost of funds and banks may have to pay higher interest
rates to attract new deposits. This may be made worse if the bank is an Islamic
bank because there is always possibility of depositors (both non muslims and
perhaps Muslims) switching accounts or withdrawing funds.
The role of a financial intermediaries such
as banks emanates from the balance sheet items; both assets and liabilities.
Money channel highlights the importance of banks in generating liabilities such
as deposits. Banks create money through the deposits and other placement
earnings from customers, banks and other financial institutions. For instance,
a contraction in money supply, reduces the banks' reserves due to reserve
requirements. This in turn, reduces the banks' ability to increase deposits. As
a result, fewer deposits are placed by the banks customers (Ford et. al, 2003).
Ramlogan (2004) asserts that in the money channel there are two classes of
assets; money and all other assets. A reduction in the level of reserves
prompts a fall in the in the level of deposits. Therefore if money demand is
related to interest, an open market interest rates need to rise to restore
equilibrium.
Although theoretically, Islamic banks and
conventional banks in a dual banking system are governed by different
philosophical foundations, it is inevitable that these two systems may interact
given that they operate in a common macroeconomic environment. For instance,
although the Islamic banks operate within the interest-free framework, the
macroeconomic environment in a dual banking system exposes them to problem
associated with interest rate risks faced by conventional banks. This paper
therefore seeks to investigate the proposition that Islamic banks are not
susceptible to interest rate changes given that its asset-linked nature as
compared to their conventional counterparts.
The rest of this paper is
organized as follows: the next section provides some theoretical underpinnings
and literature review. Section 3 highlights an overview of the banking systems
both in Malaysia Bahrain
III. LITERATURE REVIEW
Empirical assessment on the merits of
the interest-free banking system has been initiated by Darrat (1988) who showed
that the banking system in Tunisia Iran Iran
Kaleem (2000),
Samad and Hassan (2000) and Samad (1999) are among the many studies which
provide empirical supports on the stability of the Islamic monetary instruments
in a dual banking system in Malaysia
Despite the
numerous studies supporting the superiority of the interest-free banking system
over the interest-based system, further research on more detailed aspects of
the relationships between the interest-free banking and various aspects of
financial risks reveal some concerns. Baldwin (2002) finds that there is a general lack of
awareness in adopting the best risk management practices in the Islamic
countries due to an erroneous belief that an Islamic bank, by virtue of its
interest-free nature, is not subjected to the interest rate fluctuations. Rosly (1999) finds that Islamic banks in Malaysia Malaysia
An examination of the impacts of the
conventional money market rates on the Islamic financial instruments in Malaysia Malaysia
III. ISLAMIC
BANKING SYSTEM IN MALAYSIA BAHRAIN
ISLAMIC
BANKING IN MALAYSIA
Islamic banking
industry in Malaysia Malaysia Malaysia
Despite the impressive growth, the share
of Islamic banking of the total financing extended by the banking system is
still small. Of the total deposits
mobilised by the banking system in 2006, Islamic banks contributed about 12.4
percent, a small improvement from 5 percent recorded in 2000. Likewise, Islamic banks contribute only 13.3
percent of total financing extended by the banking system.
The Islamic banking industry continues
to grow supported by the conducive environment provided by the BNM. To accelerate development of the industry and
create positive competitive pressure to take advantage of positive spill-over
effects, BNM grants banking licence to full-fledge domestic and foreign Islamic
banks, particularly from the middle-east to operate in the country. By the end of 2006 and early 2007, several
full-fledged Islamic banks commence operations resulting in eleven full-fledge Islamic banks in Malaysia
The encouraging growth of the Islamic
banking industry in Malaysia Malaysia Malaysia Malaysia
ISLAMIC
BANKING IN BAHRAIN
The Bahraini Islamic banking system is
enjoying a robust and dynamic growth in a favourable financial environment in
the last few years. Bahrain
Currently, the conventional banking system
comprises of 19 retail banks, 69 wholesale banks, 2 specialised banks and 36
representative offices of overseas bank. The Islamic banking system on the
other hand, comprises of 6 retail banks and 18 wholesale banks offering a
diversified shariah- compliant products and services. The banking system in Bahrain Bahrain
The significant role of the banking
industry in the emergence of Bahrain
Backed by the escalating fuel prices and a
corresponding increase in liquidity within the GCC region, the Islamic banking
and finance industry in Bahrain
Against the backdrop of this
burgeoning growth of the two global leaders in Islamic banking and finance
industry, Malaysia Bahrain
3. DATA AND EMPIRICAL
FRAMEWORK
3.1 The Model
Ramlogan (2004) asserts that in the money channel
there are two classes of assets; money and all other assets. A reduction in the
level of reserves prompts a fall in the in the level of deposits. Therefore if
money demand is related to interest, an open market interest rates need to rise
to restore equilibrium. Consistent with the money channel theory as proposed by
Keynes(1936), empirical model can therefore be represented as follows:
IB Depositst = δ0 + f1ONRt + j2GDPt + g3REERt + μ4M2t + €t
(1.0)
The overnight rate (henceforth denoted as ONR) is used
as the monetary policy indicator for Malaysia Bahrain Bahrain Malaysia Malaysia Bahrain
The GDP represent the growth
of an economy and therefore may be regarded as determinant of deposits in the
banking system. An increase in GDP is expected to have a positive effect on the
Islamic banking deposits. For Malaysia Bahrain
A higher exchange
rate on the other hand results in higher imports prices and inturn, increases domestic prices.
Accordingly, a higher exchange rate reduces exports prices and thus leading to
a higher demand for exports. (Kia and Darrat, 2007). As a result, the higher
demand for resources creates a pressure on domestic prices and hence reduces
deposits in Islamic banks.
3.1. Data
Due to unavailability of data for comparative
analysis, we employ data that are most appropriate to represent each objective
and macroeconomic variable. The data description is summarised in the table
below
Table
1: Data Description and Sources
|
Variable
|
Description
|
Measurement
|
Source
|
|
ID (
|
Islamic banks'
Deposits in
|
Total deposits
in the Islamic banking system.
|
BNM
|
|
ID (
|
Islamic
Deposits in
|
Domestic
Liabilities of Islamic banks to private non-banks
|
CCB
|
|
M2
|
Real
broad-Money Supply
|
Money Supply M2
(
Money + Quasi
money (
|
IFS
|
|
ONR
|
Interest Rate
|
Overnight
policy Rate (
Money market
interbank rate (
|
IFS
|
|
IPI
|
GDP
|
Industrial
Production Index (
Refined
Petroleum production (
|
IFS
|
|
REER
|
Real Effective
Exchange Rate
|
The weighted
average of the Malaysian /
|
IFS
|
3.2. Empirical Framework
A battery of time series techniques are used to
empirically explore the dynamic interrelationships between the Islamic banks' deposits
in Bahrain Malaysia
3.2.1. ARDL Bound Testing
Approach
To examine the relationship between
deposits of the Islamic banking system and the monetary policy variables, this
study employs the newly proposed ARDL bound testing approach to cointegration
(see Pesaran et al., 2001). It
involves estimating the conditional error correction version of the ARDL model.
The choice of ARDL approach in this study is based on consideration of
cointegration analysis are unbiased and efficient given the fact that, firstly,
it can be applied to a small sample size study (Pesaran et al., 2001) and therefore conducting bounds testing will be
appropriate for the present study. Secondly, it estimates the short- and
long-run components of the model simultaneously, removing problems associated
with omitted variables and autocorrelation and, thirdly, the ARDL method can
distinguish between dependent and independent variables (Narayan, 2004).
Ideally, for the purpose of this study, we
need to incorporate all the variables in the modelling, but a VAR model can be
poorly estimated in a finite sample, as the addition of a variable will quickly
exhaust the degree of freedom. Following Gertler and Gilchrist (1993, 1994), we
estimated a series of separate VAR models including M2, IPI, and REER, policy
variable (ONR), and the Islamic banks' deposits. Thus, our models contain only
five variables.
The ARDL models for the conventional and
Islamic bank balance sheet items used in this study can be written as follow:
Islamic
Deposits: Bahrain
BIDt
= δ0 + f1ONRt + j2IPIt + g3REERt + μ4M2t + €t (1.1)
Islamic
Deposits: Malaysia
MIDt = δ0 + f1ONRt + j2IPIt + g3REERt + μ4M2t + υt (1.2)
The error correction version of ARDL framework
pertaining to the variables in the Equations (1.1) through (1.4) can be
reproduced as follows:
For Islamic
Deposits: Bahrain
(2.1)
For Islamic
Deposits: Malaysia
(2.2)
In the above equation, the terms with the
summation signs represent the error correction dynamic, while the second part
(term with λs) correspond to
the long-run relationship. The null of no cointegration in the long-run
relationship is defined by H0:
λ1 ≠ λ2 ≠ λ3
≠ λ4 ≠ λ5 = 0 is tested against the alternative of H0: λ1 ≠
λ2 ≠ λ3 ≠ λ4 ≠ λ5 ≠ 0, by the means of familiar F-test. However,
the asymptotic distribution of this F-statistic is non-standard irrespective of
whether the variables are I(0) or I(1). Pesaran et al. (1996) have tabulated
two sets of appropriate critical values. One set assumes all variables are I(1)
and another assumes that they are all I(0). This provides a bound covering all possible
classifications of the variables into I(1) and I(0) or even
fractionally integrated. If the
F-statistic lies above the upper bound level, the null hypothesis is rejected,
which indicates the existence of cointegration. However, if the F-statistic falls below the
bound level, the null cannot be rejected, showing that no cointegration exist. If, however, it falls within the band, the
result is inconclusive. Finally, in order to determine the optimal lag-length
incorporated into the model and select the ARDL model to be estimated, the
study employs the Akaike Information Criteria (AIC).
3.2.2. VECM Framework
To examine the short- and long-run dynamic relationships
among the variables, the study employs the vector error correction model (VECM)
framework. The VECM regresses the changes in the both dependent and independent
variables on lagged deviations. The
multivariate causality test based on VECM can therefore be formulated as
follows:
Zt
= d + 
iZt-1 +
…….+ kZt-k
+ PZt-k
+ εt (3)
where Zt is an
n x 1 vector of variables and d is an n x 1 vector of constant,
respectively. In our case, Zt
= (CD/CL/ID/IL, ONR, IPI, RER, INF). G is an n
x n matrix (coefficients of the short run dynamics), P = ab′ where a is an n x 1 column vector (the matrix of
loadings) represents the speed of short run adjustment to disequilibrium and b′ is an 1 x n cointegrating row vector (the
matrix of cointegrating vectors) indicates the matrix of long run coefficients
such that Zt converge in their long run equilibrium. Finally,
εt
is an n x 1 vector of white noise
error term and k is the order of
autoregression.
A test statistic is calculated by taking
the sum of the squared F-statistics of G and
t-statistics of P. The multivariate causality test is
implemented by calculating the F-statistics (Wald-test) based on the
null-hypothesis that the set of coefficients (G) on the lagged values of independent variables are not
statically different from zero. If the null-hypothesis is not rejected, then it
can be concluded that the independent variables do not cause the dependent
variable. On the other hand, if P is significant (that is different from zero) based on
the t-statistics, then both the independent and dependent variables have a
stable relationship in the long-run.
Finally, from the Equation (3), two
channels of causation may be observed. The first channel is the standard
Granger tests, examining the joint significance of the coefficients of the
lagged independent variables. Whereas, the second channel of causation is the
adjustment of the dependent variable to the lagged deviations from the long run
equilibrium path, represented by the error correction term (ECT). If the ECT is
found to be significant, it substantiates the presence of cointegration as
established in the system earlier and at the same time, it tells us that the
dependent variable adjusts towards its long run level. From these tests, we can
reveal four patterns of causal interactions among pairs of the variables, i.e.,
(i) a unidirectional causality from a variable, say x, to another variable, say
y; (ii) a unidirectional causality from y to x; (iii) bidirectional causality;
and (iv) independent causality between x and y.
4.
EMPIRICAL RESULTS AND ANALYSIS
In estimating the short- and long-run relationships
between the monetary policy variable and the objective variables consisting of
the deposits of Islamic banks in both countries Bahrain Malaysia
Table 1: F-statistics for
Testing the Existence of a Long-run Equation
|
Lag-Length
|
|
|
||||
|
|
Deposits
|
Deposits
|
||||
|
1
|
3.0679**
|
5.131***
|
||||
|
2
|
3.2231**
|
2.6054**
|
||||
|
3
|
3.2643**
|
2.8189**
|
||||
|
4
|
3.2695**
|
3.1405**
|
||||
|
5
|
3.1723**
|
4.0748**
|
||||
|
6
|
3.4642***
|
2.7035**
|
||||
Note: *, **, and *** denotes that F-Statistics falls above the 90%, 95%
and 99% upper bound, respectively.
The computed F-statistics for each
lag-length for all the models are reported in Table 1. As reported, the test
outcome of the significance levels for the ARDL models varies with the choice
of lag-length. The computed F-statistics are significant at least at 90% level
when the order of lags ranges from 1 to 6 for the Islamic banks' deposits for
both Bahrain Malaysia Bahrain Bahrain
Table 2: The Long-run ARDL Model Estimates
|
|
|
|
|
|
Deposits
[1,0,4,0,2]
|
Deposits
[1,0,0,0,0]
|
|
C
|
-41,9680***
(-7.59701)
|
.83542 (1.1044)
|
|
ONR
|
-0.23013***
(-8.4456)
|
.0080720 (.39818)
|
|
IPI
|
-2.959
(-1.7176)
|
-.037193 (-.55697)
|
|
M2
|
4.9283***
(12.6564)
|
.74028***
(6.3055)
|
|
REER
|
2.3562***
(4.1494)
|
-.065221 (-.56918)
|
|
|
Adj-R2 = .97406
D-W= 1.6822
|
Adj-R2 = .98342
D-W = 2.2625
|
Notes: *, ** and *** denotes significantly at 10%, 5% and 1% level of
significance, respectively. Figures in
the parentheses and squared parentheses are the t-statistics values and
the selected ARDL model. D-W denotes
Durbin-Watson test for autocorrelation.
The next step involves estimating Equations
(1.1) to (1.4) using the appropriate lag-length selection criterion based on
the Akaike Information Criterion (AIC). Based on Table 2, the results provide
evidence that the Bahrain
In the case of Bahrain Bahrain Bahrain Malaysia
In comparing the responses of the channels
of monetary policies in both Bahrain Malaysia Bahrain
Next, we move on to the multivariate
causality analysis which helps us to explore the short- and long-run dynamics
of the variables in the system. Based on
the VECM framework, we estimate the changes in both dependent and independent
variables on lagged deviations. The estimates of the error correction
representations selected by the AIC are presented in Tables 3 and 4. The long
run coefficients reported for both models involving Islamic banking deposits
for Bahrain Malaysia
Table 3: Multivariate 'VECM' Causality for the Islamic
Bank (Malaysia
|
Dependent Variables
|
Independent Variables
|
|||||||||||||||
|
ΔID
|
ΔONR
|
ΔIPI
|
ΔM2
|
ΔREER
|
ECTt-1
|
|||||||||||
|
ΔID
|
|
|
|
|
|
|
||||||||||
|
ΔONR
|
|
-
|
|
|
|
|
||||||||||
|
ΔIPI
|
|
|
-
|
|
|
|
||||||||||
|
ΔM2
|
|
|
|
|
|
|
||||||||||
|
ΔREER
|
|
|
|
|
-
|
|
||||||||||
Note: ***, ** and *
represent significance at the 1%, 5% and 10% levels, respectively. ECTt-1
is derived by normalizing the cointegrating vectors on the dependent variables
(i.e., BID and MID), producing residual r. By imposing restriction on
the coefficients of each variable and conducting Wald test, we obtain F-statistics
for each coefficient in all equations. Figures in the parentheses and squared
parentheses represent F-statistics
and probabilities for t-statistics,
respectively.
Analyzing the short-run
causalities based on the VECM framework, we find further support to our earlier
findings. Focusing on the direction of
causalities between the monetary policy variable and the bank balance sheet
items, we find that there is a significant causality running from ONR to IPI. However, the monetary policy variable is not
significant in causing Islamic banks' deposits for both Bahrain Malaysia
results also show that for Malaysia Malaysia
Table
4: Multivariate 'VECM' Causality for
the Islamic Bank (Bahrain
|
Dependent Variables
|
Independent Variables
|
|||||||||||||||
|
ΔIDB
|
ΔONR
|
ΔIPI
|
ΔM2
|
ΔREER
|
ECTt-1
|
|||||||||||
|
ΔIDB
|
--
|
|
|
|
|
|
||||||||||
|
ΔONR
|
0.304118
(0.7578)
|
-
|
|
|
|
|
||||||||||
|
ΔIPI
|
|
|
|
|
|
|
||||||||||
|
ΔM2
|
|
|
|
|
|
|
||||||||||
|
ΔREER
|
|
|
|
|
-
|
|
||||||||||
Note: ***, ** and *
represent significance at the 1%, 5% and 10% levels, respectively. ECTt-1
is derived by normalizing the cointegrating vectors on the dependent variables
(i.e., BID and MID), producing residual r. By imposing restriction on
the coefficients of each variable and conducting Wald test, we obtain F-statistics
for each coefficient in all equations. Figures in the parentheses and squared
parentheses represent F-statistics
and probabilities for t-statistics,
respectively.
Shifting to the short-run causality of
monetary policy variable and Islamic banks’ deposits for Bahrain Bahrain Bahrain Bahrain
We then proceed to examine the stability of
the long run coefficients together with the short-run dynamics. Following
Pesaran and Pesaran (1997), we apply the CUSUM test proposed by Brown et al.
(1975). The tests are employed for both models. As highlighted by
Bahmani-Oskooee and Ng (2002), the CUSUM test employs the cumulative sum of
recursive residuals based on the first set of observations and is updated
recursively and plotted against the break points. If the plot of the CUSUM
statistics is found to be within the critical bounds of 5% level, the null
hypothesis that all coefficients in the error correction models as in Equations
(2) and (3) are stable cannot be rejected. On the other hand, if the lines are
found to be crossed, the null hypothesis of coefficient constancy can therefore
be rejected at 5 percent significance level. Based on the graphical
representations for CUSUM test for all models are reported respectively as in
Figure 1, the results indicate no evidence of any significant structural instability.
Figure 1: CUSUM
and CUSUMSQ Plots
Islamic Deposits: Malaysia
Islamic Deposits: Bahrain
5.
Conclusion
In
conclusion, the study shows that the Islamic banks’ deposits in Bahrain Bahrain Malaysia Bahrain
Due to
vulnerability to interest rate changes, Islamic financial institutions in Bahrain Malaysia Malaysia Bahrain Bahrain Malaysia
As shown in this study, it could also be implied that
the variables that are relevant in the monetary policy transmission would have
to be continuously monitored due to the dynamic nature both economies. As being shown in the study, the importance
of the Islamic bank's deposits in the monetary transmission in Bahrain
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