Dynamic Panel Approaches - Munich Personal RePEc Archive

M PRA
Munich Personal RePEc Archive
Socioeconomic Development and Its
Effect on Performance of Islamic Banks:
Dynamic Panel Approaches
M. Ashraful Ferdous Chowdhury and M. Mahmudul Haque
and Syed Othman Alhabshi and Abul Mansur M. Masih
INCEIF, Malaysia and Shahjalal University of Science and
Technology, Sylhet, Bangladesh, INCEIF, Malaysia, INCEIF,
Malaysia, INCEIF, Malaysia
26 May 2016
Online at https://mpra.ub.uni-muenchen.de/71888/
MPRA Paper No. 71888, posted 9 June 2016 20:08 UTC
Chapter 14
Socioeconomic Development and Its Effect
on Performance of Islamic Banks: Dynamic
Panel Approaches
Mohammad Ashraful Ferdous Chowdhury, Md. Mahmudul Haque,
Syed Othman Alhabshi, and Abul Mansur Mohammed Masih
Abstract ,VODPLFEDQNVDUHKLJKO\LQFRUSRUDWHGZLWKVRFLDOLVVXHVEHFDXVHRIWKHLU
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test these gaps, this chapter attempts to investigate the socioeconomic factors along
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Quantile regression. The dataset used in this study involves 55 full-fledged Islamic
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statistically negative to cost-to-income ratio. It is also suggested that the relationVKLSEHWZHHQULVNDQGUHWXUQLVKHWHURJHQHRXVRUGLVVLPLODUDFURVVGLIIHUHQWTXDQtiles. Findings of the study tend to unravel that the socioeconomic factors especially
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Keywords 52$‡6RFLRHFRQRPLFIDFWRUV‡&UHGLWULVN‡'\QDPLF*00‡4XDQWLOH
regression
14.1 Introduction
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M.A.F. Chowdhury (*)
INCEIF and Shahjalal University of Science and Technology, Sylhet, Bangladesh
e-mail: [email protected]
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INCEIF, Lorong Universiti A, Kuala Lumpur 59100, Malaysia
© Springer International Publishing Switzerland 2016
M. Zulkhibri et al. (eds.), Macroprudential Regulation and Policy for the
Islamic Financial Industry, DOI 10.1007/978-3-319-30445-8_14
229
230
M.A.F. Chowdhury et al.
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negative, or curvilinear (Nwude 20127KHUREXVWJURZWKLQÀQDQFLQJDQGLQYHVWment activities across most jurisdictions in various real sectors has helped Islamic
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In any economy, socioeconomic freedom is a major dimension, which will affect
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setting which reflects socioeconomic freedom fluctuating widely across countries,
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investment opportunities. Socioeconomic freedom particularly easing the regulaWRU\IUDPHZRUNKHOSVLQWHUQDWLRQDOLQYHVWRUVSHQHWUDWHLQWRGRPHVWLFPDUNHWV,WLV
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rule of law, good enforcement of contracts, protection of individual and investment
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to economic progress.
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14
Socioeconomic Development and Its Effect on Performance of Islamic Banks…
231
the developed and developing countries are mostly focused on the conventional
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14.2 Literature Review
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studies rather than rigorous statistical estimations (El‐*DPDODQG,QDQRJOX2005).
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et al. 2013). While Sala-i-Martin et al. (2013) consider the effects of economic freedom on inequality, and consider income convergence aggregate productive effiFLHQF\,QGH[HVRIHFRQRPLFIUHHGRPKDYHDOVREHHQXVHGDVH[SODQDWRU\YDULDEOHV
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given level of creditors or shareholders protection. In contrast, Fries and Taci (2005)
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14
Socioeconomic Development and Its Effect on Performance of Islamic Banks…
233
While most of the research has highlighted the growth of the Islamic financial
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potential and growth of the industry. To that effect, there is a strong demand to put the
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14.3 Data and Methodology
14.3.1 Data Collection
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14.3.2 Methodology
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and dynamic models are applied.
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14.3.3 Static Models (Fixed and Random Effects)
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data, the used model consists nFURVVVHFWLRQDOXQLWVGHQRWHGE\n = 1, NREVHUYHG
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model:
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where YLVUHWXUQRQDVVHWV52$&,5LVFRVWWRLQFRPHUDWLR/7$LVQDWXUDOORJ
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error term.
14.3.4 Dynamic GMM Models
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*00+DQVHQ).
Arellano and Bover (1995) and Blundell and Bond (2000) augment the differHQFH*00PRGHOE\GHYHORSLQJWKHV\VWHP*00HVWLPDWRUZKLFKLQFOXGHVODJJHG
OHYHOVDVZHOODVODJJHGGLIIHUHQFHV7KHV\VWHP*00HVWLPDWRUDVVXPHVWKDWÀUVW
GLIIHUHQFHV RI LQVWUXPHQWDO YDULDEOHV DUH XQFRUUHODWHG ZLWK WKH À[HG HIIHFWV ,W
DOORZV WKH LQWURGXFWLRQ RI PRUH LQVWUXPHQWV DQG FDQ VXEVWDQWLDOO\ LPSURYH HIÀFLHQF\ 5RRGPDQ DPRQJ RWKHUV DUJXHV WKDW ERWK GLIIHUHQFH DQG V\VWHP
*00HVWLPDWRUVDUHVXLWDEOHIRUVLWXDWLRQVZLWK´VPDOO7ODUJH1µSDQHOVLQGHSHQGHQWYDULDEOHVWKDWDUHQRWVWULFWO\H[RJHQRXVÀ[HGLQGLYLGXDOHIIHFWVKHWHURVNHGDVWLFLW\ DQG DXWRFRUUHODWLRQ DPRQJ LQ WKLV VWXG\ LQGLYLGXDO EDQNV +RZHYHU WKH
GLIIHUHQFH *00 HVWLPDWRUV FDQ EH VXEMHFW WR VHULRXV ÀQLWH VDPSOH ELDVHV LI WKH
14
Socioeconomic Development and Its Effect on Performance of Islamic Banks…
235
LQVWUXPHQWVXVHGKDYHQHDUXQLWURRWSURSHUWLHV8VHRIWKHV\VWHP*00UHVXOWVLQ
QRWDEO\ VPDOOHU ÀQLWH VDPSOH ELDV DQG PXFK JUHDWHU SUHFLVLRQ ZKHQ HVWLPDWLQJ
autoregressive parameters using persistent series (Bond 2002). In addition, The
*00 V\VWHP FRQWUROV IRU XQREVHUYHG KHWHURJHQHLW\ DQG IRU SHUVLVWHQFH RI WKH
GHSHQGHQWYDULDEOH7KHIROORZLQJIRUPXODIRU*00SURSRVHGE\$WKDQDVRJORX
et al. () is used to conduct the empirical analysis:
j =1
m =1
j
m
II t = C + d II i , t -1 + å b j X j it + å b j X m it + e it
where IItLVWKHSUREDELOLW\RIEDQNi at time t where i = 1 … N, t = 1, C is the Constant
Term. II i ,t -1 LVWKHODJYDOXHRIGHSHQGHQWYDULDEOHXitLVWKHH[SODQDWRU\YDULDEOHV
and εitWKHGLVWXUEDQFHWHUPZLWKvitWKHXQREVHUYHGEDQNVSHFLÀFHIIHFWDQGuit the
idiosyncratic error. This is a one-way component regression model, where vet ~ IIN
(0, σv2) and independent of uit ~ (0, σu2). The XitLVJURXSHGLQWREDQNVSHFLÀFXjit and
PDFURHFRQRPLFYDULDEOHXmit.
14.3.5 Quantile Regression (QR) Model
7KLVVWXG\HPSOR\VD45PRGHOLQZKLFKWKHSDUDPHWHURIH[SODQDWRU\YDULDEOHV
FDQEHH[SUHVVHGDVDPRQRWRQHIXQFWLRQRIDVLQJOHVFDODUUDQGRPYDULDEOH7KH
PRGHOFDSWXUHVV\VWHPDWLFLQÁXHQFHVRIFRQGLWLRQLQJYDULDEOHVRQORFDWLRQVFDOH
DQGVKDSHRIWKHFRQGLWLRQDOGLVWULEXWLRQRIWKHUHVSRQVH7KHPRGHOLVWKXVVLJQLÀFDQWO\H[WHQGHGZLWKDFRQVWDQWFRHIÀFLHQWLQZKLFKWKHHIIHFWVRIFRQGLWLRQLQJDUH
confined to a location shift. Furthermore, this study reveals that traditional optimi]DWLRQWHFKQLTXHVLQFOXGLQJ2/6DQG/$'GLVUHJDUGGLIIHUHQWEHKDYLRUVLQWKHWDLO
UHJLRQVRIEDQNSURÀWDELOLW\GLVWULEXWLRQVDQGWKHULVN²UHWXUQUHODWLRQVKLSVLQEDQNV
FKDQJHLQWKHWDLOUHJLRQV)ROORZLQJWKLVOLQHRIWKRXJKWD45WHFKQLTXHGHYHORSHG
E\.RHQNHUDQG%DVVHWWLVXVHGLQWKLVVWXG\WRH[DPLQHWKHG\QDPLFUHODWLRQVKLSEHWZHHQWKHULVNDQGEDQNSURÀWDELOLW\SHUIRUPDQFH
Assuming that the θWKTXDQWLOHRIWKHFRQGLWLRQDOGLVWULEXWLRQRIWKHH[SODLQHG
YDULDEOHLVOLQHDULQx where Quant XiWKHFRQGLWLRQDO45PRGHOFDQEHH[SUHVVHG
as follows:
Yi = x ’i × bq + uq i
Quantq ( yi | xi ) = inf { y : Fi ( y | x )q } = x ’i × bq
Quantq ( uq i | xi ) = 0
where Quantθ (yi│xi) represents the θ the conditional quantile of yi on the regressor
vector xiβθLVWKHXQNQRZQYHFWRURISDUDPHWHUVWREHHVWLPDWHGIRUGLIIHUHQWYDOXHV
of θLQuθiLVWKHHUURUWHUPDVVXPHGWREHFRQWLQXRXVO\GLIIHUHQWLDEOHFGI
(cumulative density function) of F i(y│x)θ and a density function F i(y│x)θ.
M.A.F. Chowdhury et al.
The value Fi(y│x)θ GHQRWHV WKH FRQGLWLRQDO GLVWULEXWLRQ RI y conditional on x.
9DU\LQJWKHYDOXHRIuIURPWRUHYHDOVWKHHQWLUHGLVWULEXWLRQRIy conditional on
x. The estimator for uLVREWDLQHGIURP
i :u >= 0
min
åq
x
uq +
i :u <= 0
n
=
å
å 1-q
x
uq i
n
q x yi - x ’i × bq +
i : yi - x ’i . b >= 0
å (1 - q )
x
| yi - x ’i × bq
i : yi - x ’i . b <= 0
14.4 Results and Discussion
14.4.1 Descriptive Study
7RDQDO\]HWKHUHVXOWRIWKHVWXG\ÀUVWLWLVXVHIXOWRFRPPHQWRQVRPHSUHOLPLQDU\
IHDWXUHVRIRXUGDWD7DEOHVKRZVGHVFULSWLYHVWDWLVWLFVIRUWKHSURÀWDELOLW\52$
DQGWKHEDQNVSHFLÀFDQGPDFURHFRQRPLFYDULDEOHVXVHGLQRXUPRGHO,QDYHUDJH
WKHUHWXUQRQDYHUDJHDVVHWRI,VODPLFEDQNVXVHGLQWKLVVWXG\LV7KHPHDQ
RIDOORWKHULQGHSHQGHQWYDULDEOHVDUHDOVRSRVLWLYHH[FHSW3ROLWLFDOVWDELOLW\
7KHPHDQRIFRVWWRLQFRPHUDWLRLVWKHODUJHVWDQGYDULHVJUHDWO\DFURVV
EDQNV PD[ DQG PLQ 7KH VWDQGDUG GHYLDWLRQ LV KLJKHVW LQ WKH
LQWKHFRVWWRLQFRPHUDWLR7KH&,5DQGVL]H/RJ7$RIWKHVDPSOHGEDQN
LQ*&&UHJLRQLVDQGUHVSHFWLYHO\7KHYDULDEOH//5*/ZKLFKLVWKH
SUR[\IRUFUHGLWULVNLV)URPWKHULVNSHUVSHFWLYHLHVWDQGDUGGHYLDWLRQWKH
KLJKHVWYDOXHOLHVLQWKH&,5YDULDEOHIROORZHGE\//5*/DQG52$E\DQG
UHVSHFWLYHO\)URPWKHVRFLRHFRQRPLFSHUVSHFWLYHRYHUWKHDYHUDJHPHDQRI
WKH32/6LVQHJDWLYHPHDQLQJWKDWWKHSROLWLFDOVWDELOLW\RIWKHVDPSOHGFRXQWULHVLV
less than the standard level.
Table 14.2 'HVFULSWLYHVWDWLVWLFV
Mean
Median
0D[
Min.
6WG'HY
6NHZQHVV
Kurtosis
2EV
52$
ï
3.39320
ï
220
&,5
10.5000
220
LTA
1.55505
ï
220
//5*/
3.55500
100.000
0.00000
220
&25
ï
220
32/6
ï
ï
ï
ï
220
IF
90.000
0.0000
220
35
50.000
90.000
10.000
220
Notes7KHGHSHQGHQWYDULDEOH52$LVFDOFXODWHGDVQHWSURÀWGLYLGHGE\WRWDODVVHWV&,5³WKH
FRVWWRLQFRPHUDWLRLVXVHGDVDSUR[\IRURSHUDWLQJHIÀFLHQF\//5*/LVDPHDVXUHRIFUHGLWULVN
FDOFXODWHGDVWKHUDWLRRIWRWDOORDQORVVSURYLVLRQVE\*URVVORDQ/2*7$LVDSUR[\PHDVXUHRI
VL]HFDOFXODWHGDVDQDWXUDOORJDULWKPRIWRWDOEDQNDVVHWV32/PHDVXUHVWKHSROLWLFDOVWDELOLW\,)
LQGLFDWHVWKH,QYHVWPHQWIUHHGRPDQG35UHIHUVWKH3URSHUW\ULJKWV
14
Socioeconomic Development and Its Effect on Performance of Islamic Banks…
14.4.2 Correlation Matrix
$FFRUGLQJWR7DEOHWKHORDQORVVSURYLVLRQWRJURVVUHYHQXHVVHHPVWREHQHJDWLYHO\FRUUHODWHGZLWKWKHSURÀWDELOLW\PHDVXUHLQGLFDWLQJWKDWZKHQWKHORDQORVV
SURYLVLRQV LQFUHDVH SURÀWDELOLW\ PRYHV WR WKH RSSRVLWH GLUHFWLRQ E\ ï $V
H[SHFWHG FRVWWRLQFRPH UDWLR RYHUKHDG H[SHQVHV LV QHJDWLYHO\ FRUUHODWHG ZLWK
SURÀWDELOLW\ZLWKDFRUUHODWLRQRIï&RQWLQXLQJWRWKHFRUUHODWLRQVRIEHWZHHQ
WRWDODVVHWVDQG52$LVSRVLWLYHO\FRUUHODWHGZLWKE\2QWKHRWKHUKDQG
VRFLRHFRQRPLFYDULDEOHVVXFKDV&RUUXSWLRQSROLWLFDOVWDELOLW\LQYHVWPHQWIUHHGRP
DQGSURSHUW\ULJKWVDUHQHJDWLYHO\UHODWHGWR52$$ZLWKïïï
DQGïUHVSHFWLYHO\)LQDOO\VLQFHWKHUHLVQRYDOXHPRUHWKDQZHFDQ
VD\WKDWWKHUHVKRXOGQRWEHDQ\PXOWLFROOLQHDULW\
14.4.3 Empirical Findings
Before estimating the static and dynamic model in panel techniques, this study
H[DPLQHVWKHSDQHOXQLWURRWWHVWDQGSDQHOFRLQWHJUDWLRQWHVW,WKDVEHHQIRXQGWKDW
GDWDDUHQRQVWDWLRQDU\DWWKHOHYHOIRUPDQGLWEHFRPHVVWDWLRQDU\DIWHUXVLQJÀUVW
OHJ,WLVDOVRIRXQGWKDWUHODWLRQVKLSVDPRQJYDULDEOHVDUHQRWVSXULRXV
6LQFHWKHSUREDELOLW\RI&KLVTXDUHYDOXHRI+DXVPDQWHVWZLWK3YDOXH
WKLVFKDSWHUZLOOJLYHPRUHIRFXVRQUDQGRPHIIHFW+HUH7DEOH provides
the estimation results of the random effect model. We can see that although variDEOHVOLNHFRUUXSWLRQDQGSURSHUW\ULJKWVDUHLQVLJQLÀFDQWQRZH[KLELWPRUHLQWXLWLYHO\SODXVLEOHSRVLWLYHGLUHFWLRQRILQÁXHQFH(YHQWKRXJKWKHRYHUDOO3URWHFWLQJ
,QYHVWRUV,QGH[UHWDLQVSRVLWLYHVLJQWKUHHRILWVVHYHQFRPSRQHQWVQRZKDYHQHJDWLYH HIIHFW 7KH QH[W FUHGLW ULVN SURFHGXUHV H[KLELW SRVLWLYH VLJQ FRQÀUPLQJ WKH
Table 14.3 &RUUHODWLRQPDWUL[
52$$
&,5
LTA
//5*/
&25
32/6
IF
35
52$$
1.0000
ï
ï
ï
ï
ï
ï
&,5
LTA
//5*/
&25
32/6
IF
35
1.0000
ï
0.2309
1.0000
ï
ï
1.0000
ï
ï
0.0211
ï
1.0000
0.3993
1.0000
0.5519
1.0000
1.0000
Notes7KHGHSHQGHQWYDULDEOH52$LVFDOFXODWHGDVQHWSURÀWGLYLGHGE\WRWDODVVHWV&,5³WKH
FRVWWRLQFRPHUDWLRLVXVHGDVDSUR[\IRURSHUDWLQJHIÀFLHQF\//5*/LVDPHDVXUHRIFUHGLWULVN
FDOFXODWHGDVWKHUDWLRRIWRWDOORDQORVVSURYLVLRQVE\*URVVORDQ/2*7$LVDSUR[\PHDVXUHRI
VL]HFDOFXODWHGDVDQDWXUDOORJDULWKPRIWRWDOEDQNDVVHWV32/PHDVXUHVWKHSROLWLFDOVWDELOLW\,)
LQGLFDWHVWKH,QYHVWPHQWIUHHGRPDQG35UHIHUVWKH3URSHUW\ULJKWV
M.A.F. Chowdhury et al.
Table 14.4 Model estimations
)L[HGHIIHFWV
²
5DQGRP
effects
1.1915
²
First step
GLIIHUHQFHG*00
Second step
GLIIHUHQFHG*00
ï
ï
ï
ï
ï
ï
ï
²
ï
ï
ï
²
ï
ï
²
χ2 3URE!χ2 $5WHVW
F
VWDW ²
ï
ï
ï
²
χ2 3URE!χ2 ²
$5WHVW
²
²
1RREVHUYDWLRQV
220
220
Z p Z p = 0.5190
220
Z p Z p 220
9DULDEOHV
Intercept
52$$³ODJRI
GHSHQGHQWYDULDEOH
LTA
//5*/
&,5
&25
32/6
35
IF
5VTXDUHG
Sagan test
F-stat/Wald-χ2
Notes7KHGHSHQGHQWYDULDEOH52$LVFDOFXODWHGDVQHWSURÀWGLYLGHGE\WRWDODVVHWV&,5³WKH
FRVWWRLQFRPHUDWLRLVXVHGDVDSUR[\IRURSHUDWLQJHIÀFLHQF\//5*/LVDPHDVXUHRIFUHGLWULVN
FDOFXODWHGDVWKHUDWLRRIWRWDOORDQORVVSURYLVLRQVE\*URVVORDQ/2*7$LVDSUR[\PHDVXUHRI
VL]HFDOFXODWHGDVDQDWXUDOORJDULWKPRIWRWDOEDQNDVVHWV32/PHDVXUHVWKHSROLWLFDOVWDELOLW\,)
LQGLFDWHV WKH ,QYHVWPHQW IUHHGRP DQG 35 UHIHUV WKH 3URSHUW\ ULJKWV 9DOXHV LQ SDUHQWKHVLV DUH t
VWDWLVWLFVDQGLQGLFDWHVLJQLÀFDQFHDWDQGOHYHOUHVSHFWLYHO\
WKHRUHWLFDOSUHGLFWLRQV)LQDOO\SROLWLFDOVWDELOLW\DQGLQYHVWPHQWIUHHGRPRIVRFLRHFRQRPLFIUHHGRPLQGLFDWRUVUHYHDOQHJDWLYHHIIHFWVRQEDQNLQJSHUIRUPDQFH
2QWKHRWKHUKDQGFRVWWRLQFRPHUDWLRLVKLJKO\QHJDWLYHO\VLJQLÀFDQWZKLFKLV
FRQÀUPHGE\WKHWKHRUHWLFDOSUHGLFWLRQ,WLVIRXQGQHJDWLYHDQGVLJQLÀFDQWLPSDFWRQ
WKHSURÀWDELOLW\RI,VODPLFEDQNVHYHQDWVLJQLÀFDQWOHYHOLQDOOWKHDERYHPRGHOV
$LQFUHDVHVLQWKHFRVWRIWKH,VODPLFEDQNPD\UHGXFH52$RI,VODPLF
EDQNV 5HIHUULQJ WR WKH LPSDFW RI FUHGLW ULVN LW LV IRXQG SRVLWLYH DQG VLJQLÀFDQW
LPSDFWRQWKHSURÀWDELOLW\RI,VODPLFEDQNVHYHQDWVLJQLÀFDQWOHYHOLQDOOWKH
DERYHPRGHOV7KLVUHVXOWLPSOLHVWKDWLQFUHDVHGHFUHDVHLQWKLVFUHGLWULVNLQFUHDVH
GHFUHDVHWKHSURÀWVRI,VODPLFEDQNVRSHUDWLQJLQWKH,VODPLFEDQNLQJVHFWRU
$VDOUHDG\GLVFXVVHGWKHHVWLPDWRUVRIWKLVPRGHOVWLOOVXIIHUIURPELDVGXHWRWKH
ODFNRIG\QDPLFUHODWLRQVKLSEHWZHHQODJJHGGHSHQGHQWYDULDEOH6LQFH*00FDQ
VROYHRQO\WKH´À[HGHIIHFWµSUREOHPEXWÀ[LQJWKHSUREOHPRI´FRUUHODWLRQEHWZHHQ
WKH ODJJHG GHSHQGHQW YDULDEOH DQG WKH HUURU WHUPµ DQG ´WKH HQGRJHQHLW\ RI VRPH
H[SODQDWRU\YDULDEOHVµSUREOHPVWKLVVWXG\DSSOLHGWKHVWHSDQGVWHSGLIIHUHQFHG
*00 7KH QH[W WZR FROXPQV RI WKH WDEOH VKRZ ÀQGLQJV RI *00 HVWLPDWLRQV
14
Socioeconomic Development and Its Effect on Performance of Islamic Banks…
239
&ROXPQIRXUGHVFULEHVUHVXOWVRIGLIIHUHQFH*00HVWLPDWLRQ$OORIWKHLQGLFDWRUV
KDYHVLJQLÀFDQWH[SODQDWRU\SRZHUPRUHRYHUWKHVLJQVRIWKHHVWLPDWHVPRVWO\FRQform to its theoretical predictions almost in every case.
7KHVHUHVXOWVFRQÀUPWKHWKHVLVRISRVLWLYHLQÁXHQFHRILQVWLWXWLRQDOYDULDEOHVRQ
the financial sector. Therefore, we can infer that institutional quality, including speFLÀFEDQNGHWHUPLQDQWVDQGEURDGHUVRFLRHFRQRPLFIUHHGRPLQGLFDWRUVDUHVLJQLÀFDQWGHWHUPLQDQWVRIEDQNSHUIRUPDQFHOHYHO,WVKRXOGDOVREHPHQWLRQHGWKDWWKH
HVWLPDWRUV KDUGO\ UHPDLQ LQ WKH ERXQGDU\ EHWZHHQ 5DQGRP (IIHFWV DQG )L[HG
(IIHFWV ,Q WKH QH[W VWHS VWHS GLIIHUHQFH *00 HVWLPDWLRQV DUH XVHG IRU PRUH
DFFXUDWHUHVXOWVDQGLQIHUHQFH2YHUDOOXVLQJERWKÀUVWGLIIHUHQFHDQGVHFRQGGLIIHUHQFH*00PHWKRGVWKLVFKDSWHUÀQGVWKDWWKHYDULDEOHVH[KLELWFRUUHFWGLUHFWLRQRI
influence. The magnitudes of which are not overly sensitive to change in specificaWLRQVEHWZHHQÀUVWGLIIHUHQFHDQGVHFRQGGLIIHUHQFH*00
14.4.4 Quantile Regression
7DEOHOLVWVWKHHVWLPDWLRQUHVXOWVRIWKH45PRGHOIRUWKHLPSDFWRIWKHEDQN
VSHFLÀFYDULDEOHVDQGVRFLRHFRQRPLFYDULDEOHVRQWKH52$)RUFRPSDULVRQWKH
2/6HVWLPDWHVDUHDOVRSUHVHQWHG+HUHERWK2/6DQGWKHTXDQWLOHUHJUHVVLRQDW
WKUHHGLIIHUHQWTXDQWLOHKDYHEHHQVWXGLHG,QWHUHVWLQJO\WKHUHVXOWRI2/6YDULHVDW
different percentile especially loan-loss reserve and total assets, etc. The result indiFDWHVWKDWDVPRUHULVNVDUHWDNHQE\DEDQNPRUHPRQH\FRXOGEHPDGH+RZHYHU
WKH2/6HVWLPDWRUE\IRFXVLQJRQO\RQWKHFHQWUDOWHQGHQF\RIWKHGLVWULEXWLRQV
Table 14.5 Quantile regression at different percentiles
LTA
//5*/
&,5
&25
32/6
35
IF
_cons
2/6BUHV
EVH
ï
0.052
ï
ï
ï
p < 0.01
Q25_res
EVH
0.000
ï
ï
ï
ï
ï
Q50_res
EVH
0.090
ï
ï
1.519
p < 0.001
4BUHV
EVH
0.090
ï
ï
0.030
ï
2.010
Notes7KHGHSHQGHQWYDULDEOH52$LVFDOFXODWHGDVQHWSURÀWGLYLGHGE\WRWDODVVHWV&,5³WKH
FRVWWRLQFRPHUDWLRLVXVHGDVDSUR[\IRURSHUDWLQJHIÀFLHQF\//5*/LVDPHDVXUHRIFUHGLWULVN
FDOFXODWHGDVWKHUDWLRRIWRWDOORDQORVVSURYLVLRQVE\*URVVORDQ/2*7$LVDSUR[\PHDVXUHRI
VL]HFDOFXODWHGDVDQDWXUDOORJDULWKPRIWRWDOEDQNDVVHWV32/PHDVXUHVWKHSROLWLFDOVWDELOLW\,)
LQGLFDWHV WKH ,QYHVWPHQW IUHHGRP DQG 35 UHIHUV WKH 3URSHUW\ ULJKWV 9DOXHV LQ SDUHQWKHVLV DUH W
VWDWLVWLFVDQGLQGLFDWHVLJQLÀFDQFHDWDQGOHYHOUHVSHFWLYHO\
M.A.F. Chowdhury et al.
1
0
.2
.4
.6
Quantile
.8
1
0
.2
.4
.6
Quantile
.8
1
0
.2
.4
.6
Quantile
.8
1
0
.2
.4
.6
Quantile
.8
1
0
.2
.4
.6
Quantile
.8
1
0
.2
.4
.6
Quantile
.8
1
0
.2
.4
.6
Quantile
.8
1
COR
-6.00
-4.00
-2.00
0.00
2.00
4.00
POLS
-4.00-2.000.00 2.00
.8
LLRGL
-0.10 0.00 0.10 0.20
LTA
-2.00
-1.00
0.001.002.003.00
.4
.6
Quantile
IF
-0.30-0.20
-0.100.000.10
Intercept
CIR
.2
-0.06-0.04-0.020.00
0
-0.20 0.00 0.20 0.40
PR
-40.00
-20.00
0.0020.00
40.00
GRHVQRWDOORZWKHLPSDFWRIWKH//5*/RQEDQNSURÀWDELOLW\WRGLIIHUIRUPRUHOHVV
SURÀWDEOHEDQNV%\FRQWUDVWWKHTXDQWLOHYDU\LQJHVWLPDWHVRIWKH//5*/YDULDEOH
GHULYHGE\WKH45PRGHODVVKRZQLQ7DEOHUHYHDOFRQVLGHUDEOHYDULDWLRQLQ
VL]HVLJQLÀFDQFHDQGHYHQLQVLJQ,QSDUWLFXODUE\XVLQJWKHOHYHORIVLJQLÀFDQFHDVDFULWHULRQZKLOHWKH//5*/YDULDEOHLVDVVRFLDWHGZLWKDQLQVLJQLÀFDQW
FRHIÀFLHQWDWWKHFHQWUDOTXDQWLOHVIURPSHUFHQWLOHLWEHFRPHVDVLJQLÀFDQWO\
SRVLWLYH QHJDWLYH FRHIÀFLHQW DW KLJKHU ORZHU TXDQWLOH OHYHOV IURP WR ²
2QWKHRWKHUKDQGWKHEDQNVL]H/7$YDU\LQJDWGLIIHUHQWSHUFHQWLOHDVVKRZQ
LQ7DEOHUHYHDOVFRQVLGHUDEOHYDULDWLRQLQVL]HVLJQLÀFDQFHDQGHYHQLQVLJQ
,QSDUWLFXODUE\XVLQJOHYHORIVLJQLÀFDQFHDVDFULWHUDWLRQLWKDVEHHQIRXQG
that the co-efficient of LTA is statistically significant only at 25 percentile whereas
2/6IRXQGWKDW/7$KDVDSRVLWLYHLPSDFWRQWKHSHUIRUPDQFHRIWKH,VODPLFEDQNV
DWOHYHORIVLJQLÀFDQFH
6XEVHTXHQWO\ )LJXUH GHSLFWV WKH 45 HVWLPDWHV DQG WKH 2/6 HVWLPDWHV
$SSDUHQWO\DVPRYLQJXSWKHEDQNSURÀWDELOLW\TXDQWLOHVOHYHOVWKH45HVWLPDWHV
YDULHVZLGHO\0RUHRYHUDFRPSDULVRQRIWKH45HVWLPDWHVZLWKWKHWUDGLWLRQDO2/6
HVWLPDWHV LQGLFDWHV WKDW WKH 2/6 HVWLPDWHV XQGHUHVWLPDWH WKH SRVLWLYH ULVN²UHWXUQ
UHODWLRQVKLS DW WKH KLJKHU TXDQWLOH OHYHOV DQG REWDLQ WKH ZURQJ FRQFOXVLRQ DW WKH
lower quantiles. Figure SUHVHQWVWKHUHJUHVVLRQOLQHVGHULYHGE\WKH45DJDLQVW
WKH2/6PHWKRGV+HUHLWFDQEHVHHQWKDWWKH//5*//7$DQG&,5YDULHVDWGLIferent percentile.
Fig. 14.1 5HJUHVVLRQOLQHV45YV2/6IRUGLIIHUHQWYDULDEOHV
14
Socioeconomic Development and Its Effect on Performance of Islamic Banks…
7KLV ÀQGLQJ UHTXLUHV VRPH H[SODQDWLRQV ,Q WKHRU\ D EDQN WDNLQJ D UHODWLYHO\
KLJKULVNLVVXSSRVHGWRHDUQKLJKSURÀWVEXWLVDOVRH[SRVHGWRFHUWDLQFRVWVWKHUHIRUHLWVSURÀWDELOLW\PLJKWEHUHGXFHG,QSDUWLFXODUEDQNUXSWF\FRVWVPD\EHUHODWLYHO\KLJKIRUDEDQNPDLQWDLQLQJKLJKHUULVNH[SRVXUH$VXEVHTXHQWLQFUHDVHLQ
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percentile. From the socioeconomic perspectives, the results are consistent in most
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14.5 Conclusion
Islamic finance is in a unique position to offer an alternative to the present interestUDWHEDVHGGHEWÀQDQFLQJUHJLPHWKDWKDVEURXJKWLQGLYLGXDODQGJOREDOHFRQRPLHV
to a series of crisis and lopsided prosperity. The core principle of Islamic finance is
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,QWKLVVWXG\LWKDVEHHQH[DPLQHGWKDWWKHOHYHORIHFRQRPLFIUHHGRPFRXOGPDWWHUVWURQJO\IRUEDQNLQJSHUIRUPDQFHDQGFUHGLWULVN7RLQYHVWLQSRWHQWLDOPDUNHW
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In contrast, there is clear evidence that showed that less government intervenWLRQSURPRWHVEDQNSHUIRUPDQFHVWDELOLW\LQD0XVOLPFRXQWU\7KLVLQIHUHQFHLV
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M.A.F. Chowdhury et al.
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together.
References
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Arellano M, Bond S (1991) Some tests of specification for panel data: Monte Carlo evidence and
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14
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