ANALYSIS OF ISLAMIC BANKING STABILITY IN INDONESIA USING ISLAMIC BANKING STABILITY INDEX
Jakarta, August 6th, 2015
Analysis of Islamic
Banking Stability
In Indonesia
Using
Islamic Banking
Stability Index
COMPOSITION OF ASSETS AMONG
FINANCIAL INSTITUTIONS
PER DECEMBER 2014
Source: Financial Services Authority (2015)
Two causes of financial instability,
including in the banking sector, Mc
Farlane (1999), as follows:
• Excessive Credit Growth
• Asset Price Explosion
The Development of Islamic Banking in
Indonesia the Last Seven Years
• Islamic Banking Assets in 2008 amounted to 49
billion dollars with five Islamic Banks (BUS).
• Total Assets of Islamic Banking in May 2014
reached 244 trillion with the number 11 Islamic
Banks (BUS).
Thus, In a period of 6 years, the development of
Islamic banking assets increased by 500%
Some Basic Principles That Lead To
Increased Stability In the Islamic Bank
( Tiby and Gras, 2015 )
•
•
•
•
•
Risk Sharing
Materiality
There Is No Exploitation
No Interest (Riba)
There Is No Involvement In Activities That
Violate Religious Rules
MACRO-MICRO ECONOMIC POLICY
FRAMEWORK
Source: Adapted from Shoenmaker (2010)
The Data
• The paper uses quantitative time series by using parametric
approach.
• The study employs the Islamic Banking Stability Index (ISPS)
as a Dependent Variable.
• The Indipendend Variable:
–
–
–
–
M2/Reserve Ratio
Inflation
Real Effective Exchange Rate
Growth of Credit
The Data of four variables are recorded in monthly basis on the website
of Bank Indonesia (BI) and the Financial Services Authority (FSA) for
10th years, since March 2004 until June 2014.
Research Methodology
• Logic Model
• VAR (Vector Autoregressive) Methodology
Some advantages are possessed by VAR model
according to Firdaus (2011) compared to the other
models are:
– The model is relatively simple
– The VAR model can be estimated using Ordinary Least Square
method (OLS) were performed on each of the equations in the
model separately
– The Forecasting results are better than the results of other
simultaneous equation models
– The model is non theory
The Scheme Assesment of
VAR/VECM Process
Source: Chen and Wu, (2000)
•
•
•
•
Green
Yellow
Orange
Red
: NORMAL
: ALERT
: EXTRA ALERT
: CRISIS
: ISPS < -6.98
: -6.98 < ISPS < - 6.93
: -6.93 < ISPS < - 6.75
: -6.75 < ISPS < - 6.06
THE MOVEMENT OF
ISLAMIC BANKING
STABILITY INDEX
IN INDONESIA
The Movement of ISPS per January 2013June 2014
Parameter
Parameter
Indeks Stabilitas Perbankan Syariah
Januari - Maret 2013
-7.114904842 -7.463852721 -7.437069621
April-Juni 2013
-7.452678457 -7.603879062 -7.638989118
Juli - September 2013
-7.655574833 -7.611203571 -7.63024006
Oktober - Desember 2013 -7.63221074 -7.593985112 -7.612335546
Januari - Maret 2014
-8.170105438 -8.126364096 -7.897280057
April-Juni 2014
-7.887363562 -7.864828644 -7.829720474
The movement of the ISPS parameters are in the
green range, which means are at Normal Levels.
THE PROBABILITY MAGNITUDE OF ISLAMIC BANKING
INSTABILITY IN
VARIOUS THRESHOLD LEVELS IN 2004-2014
(YEARLY BASIS)
Year
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
PKK
-0.0377
0.03295
-0.0287
0.02885
-0.0999
0.0961
0.00226
-0.0061
0.00457
-0.003
-0.0093
PGK
1.677
4.80093
0.89575
1.21101
1.22504
-0.1635
0.82214
-0.1613
0.93952
1.76902
-0.147
PPK
0.31396
0.86723
-0.2505
1.18474
-2.5352
2.91464
0.6306
0.02869
0.23337
-0.1796
0.39647
PLK
-0.3564
0.50411
-0.1953
0.64013
-1.5135
1.49951
0.2704
-0.0885
0.12223
-0.0489
0.01606
Description:
PKK = Probability of Crisis by
Kaminsky’s Threshold,
PGK = Probability of Crisis by
Garcia’s Threshold,
PPK = Probability of Crisis by
Park’s Threshold,
PLK = Probability of Crisis by
Lestano’s Threshold
Respone Functions of ISPS Againts Some
Selected Macroeconomics Indicators
Pressure
1,4
1,2
1
0,8
0,6
0,4
0,2
0
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
-0,2
-0,4
-0,6
-0,8
ISPS
M2RES
IFL
GRED
REER
Variance Decomposition of Some Selected
Macroeconomic Indicators
4,5
4
3,5
3
2,5
2
1,5
1
0,5
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
M2RES
15
IFL
16
17
GRED
18
REER
19
20
21
22
23
24
25
26
27
28
29
30
Magnitude and Some Selected Macroeconomic
Indicators Based On IRF and VDC Test
IRF
4
8
12
16
20
24
28
30
ISPS
0.9334
1.08326
1.11573
1.13034
1.14202
1.15297
1.16347
1.16857
M2RES
0.14122
0.13864
0.11016
0.07539
0.03807
-0.0006
-0.0398
-0.0595
IFL
-0.0333
-0.0741
-0.109
-0.1412
-0.1711
-0.199
-0.225
-0.2373
GRED
0.05819
0.0485
0.02559
0.00116
-0.0229
-0.0461
-0.0685
-0.0793
REER VDC ISPS M2RES IFL GRED REER
-0.0769 4 99.2544 0.01261 0.37153 0.20902 0.15245
-0.1628 8 98.6431 0.07041 0.53147 0.21043 0.54464
-0.2474 12 98.0228 0.16928 0.63591 0.23126 0.94075
-0.3291 16 97.449 0.28929 0.72113 0.25265 1.28791
-0.4074 20 96.9282 0.42212 0.79361 0.27134 1.58478
-0.4821 24 96.458 0.56222 0.85551 0.28722 1.83702
-0.5531 28 96.0355 0.70505 0.90826 0.30063 2.05061
-0.5871 30 95.841 0.77631 0.93159 0.30651 2.14463
Strengthening Microprudensial Policy
to Improve Stability of Islamic Banking
According Beikos (1997) and Errico and Farahbaskh
(1998), Islamic banks have higher levels of financial risk
than the conventional bank:
– Most of the investment bank in the form of Islamic profit sharing
financing (PLS) scheme, the income of banks, which are
generally sourced from PLS, has a relatively high variance
– The Islamic banks bore substantial liquidity risk due to a large
number of assets in the form of non-liquid assets
– The Islamic bank is predominantly exposed to the risk of
exchange rate because they are prohibited by Sharia to hedge
its position
Three Things or Steps to Reduce /
Prevent Risks Arising from
Intermediation Activities
1) Application of Integrated Banking Model
2) Polling of Fund Concept
3) Allocation of Fund Concept
Five Hypotheses According Irfing
Fisher
• The money growth is source of inflation
• Money supply is exogenous in nature
• The money demand is a stable function of nominal
income and interest rate
• Injecting money into economy is not able to affect the
output in the long run
• The real of interest rate is merely influenced by nonmonetary factor, such as productivity of capital and time
preference
Instruments of Macroprudential
Policy
• Strengthening the resilience of capital and preventing
excessive leverage
• Managing intermediation and controlling credit risk, liquidity
risk, foreign exchange risk and interest rate risk, as well as
other risks which could potentially become systemic
• Limiting exposure concentration
• Strengthening the resilience of the financial infrastructure
• Improving the efficiency of the financial system and financial
access
In the future, Instruments of Macroprudential
Policy should be directed towards
• Instruments which affecting MV (instruments on the
financial sector, like current instruments)
• Instruments which affecting PT (instruments on the
real sector)
• Instruments which include conventional and Islamic
macroprudentials.
Analysis of Islamic
Banking Stability
In Indonesia
Using
Islamic Banking
Stability Index
COMPOSITION OF ASSETS AMONG
FINANCIAL INSTITUTIONS
PER DECEMBER 2014
Source: Financial Services Authority (2015)
Two causes of financial instability,
including in the banking sector, Mc
Farlane (1999), as follows:
• Excessive Credit Growth
• Asset Price Explosion
The Development of Islamic Banking in
Indonesia the Last Seven Years
• Islamic Banking Assets in 2008 amounted to 49
billion dollars with five Islamic Banks (BUS).
• Total Assets of Islamic Banking in May 2014
reached 244 trillion with the number 11 Islamic
Banks (BUS).
Thus, In a period of 6 years, the development of
Islamic banking assets increased by 500%
Some Basic Principles That Lead To
Increased Stability In the Islamic Bank
( Tiby and Gras, 2015 )
•
•
•
•
•
Risk Sharing
Materiality
There Is No Exploitation
No Interest (Riba)
There Is No Involvement In Activities That
Violate Religious Rules
MACRO-MICRO ECONOMIC POLICY
FRAMEWORK
Source: Adapted from Shoenmaker (2010)
The Data
• The paper uses quantitative time series by using parametric
approach.
• The study employs the Islamic Banking Stability Index (ISPS)
as a Dependent Variable.
• The Indipendend Variable:
–
–
–
–
M2/Reserve Ratio
Inflation
Real Effective Exchange Rate
Growth of Credit
The Data of four variables are recorded in monthly basis on the website
of Bank Indonesia (BI) and the Financial Services Authority (FSA) for
10th years, since March 2004 until June 2014.
Research Methodology
• Logic Model
• VAR (Vector Autoregressive) Methodology
Some advantages are possessed by VAR model
according to Firdaus (2011) compared to the other
models are:
– The model is relatively simple
– The VAR model can be estimated using Ordinary Least Square
method (OLS) were performed on each of the equations in the
model separately
– The Forecasting results are better than the results of other
simultaneous equation models
– The model is non theory
The Scheme Assesment of
VAR/VECM Process
Source: Chen and Wu, (2000)
•
•
•
•
Green
Yellow
Orange
Red
: NORMAL
: ALERT
: EXTRA ALERT
: CRISIS
: ISPS < -6.98
: -6.98 < ISPS < - 6.93
: -6.93 < ISPS < - 6.75
: -6.75 < ISPS < - 6.06
THE MOVEMENT OF
ISLAMIC BANKING
STABILITY INDEX
IN INDONESIA
The Movement of ISPS per January 2013June 2014
Parameter
Parameter
Indeks Stabilitas Perbankan Syariah
Januari - Maret 2013
-7.114904842 -7.463852721 -7.437069621
April-Juni 2013
-7.452678457 -7.603879062 -7.638989118
Juli - September 2013
-7.655574833 -7.611203571 -7.63024006
Oktober - Desember 2013 -7.63221074 -7.593985112 -7.612335546
Januari - Maret 2014
-8.170105438 -8.126364096 -7.897280057
April-Juni 2014
-7.887363562 -7.864828644 -7.829720474
The movement of the ISPS parameters are in the
green range, which means are at Normal Levels.
THE PROBABILITY MAGNITUDE OF ISLAMIC BANKING
INSTABILITY IN
VARIOUS THRESHOLD LEVELS IN 2004-2014
(YEARLY BASIS)
Year
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
PKK
-0.0377
0.03295
-0.0287
0.02885
-0.0999
0.0961
0.00226
-0.0061
0.00457
-0.003
-0.0093
PGK
1.677
4.80093
0.89575
1.21101
1.22504
-0.1635
0.82214
-0.1613
0.93952
1.76902
-0.147
PPK
0.31396
0.86723
-0.2505
1.18474
-2.5352
2.91464
0.6306
0.02869
0.23337
-0.1796
0.39647
PLK
-0.3564
0.50411
-0.1953
0.64013
-1.5135
1.49951
0.2704
-0.0885
0.12223
-0.0489
0.01606
Description:
PKK = Probability of Crisis by
Kaminsky’s Threshold,
PGK = Probability of Crisis by
Garcia’s Threshold,
PPK = Probability of Crisis by
Park’s Threshold,
PLK = Probability of Crisis by
Lestano’s Threshold
Respone Functions of ISPS Againts Some
Selected Macroeconomics Indicators
Pressure
1,4
1,2
1
0,8
0,6
0,4
0,2
0
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
-0,2
-0,4
-0,6
-0,8
ISPS
M2RES
IFL
GRED
REER
Variance Decomposition of Some Selected
Macroeconomic Indicators
4,5
4
3,5
3
2,5
2
1,5
1
0,5
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
M2RES
15
IFL
16
17
GRED
18
REER
19
20
21
22
23
24
25
26
27
28
29
30
Magnitude and Some Selected Macroeconomic
Indicators Based On IRF and VDC Test
IRF
4
8
12
16
20
24
28
30
ISPS
0.9334
1.08326
1.11573
1.13034
1.14202
1.15297
1.16347
1.16857
M2RES
0.14122
0.13864
0.11016
0.07539
0.03807
-0.0006
-0.0398
-0.0595
IFL
-0.0333
-0.0741
-0.109
-0.1412
-0.1711
-0.199
-0.225
-0.2373
GRED
0.05819
0.0485
0.02559
0.00116
-0.0229
-0.0461
-0.0685
-0.0793
REER VDC ISPS M2RES IFL GRED REER
-0.0769 4 99.2544 0.01261 0.37153 0.20902 0.15245
-0.1628 8 98.6431 0.07041 0.53147 0.21043 0.54464
-0.2474 12 98.0228 0.16928 0.63591 0.23126 0.94075
-0.3291 16 97.449 0.28929 0.72113 0.25265 1.28791
-0.4074 20 96.9282 0.42212 0.79361 0.27134 1.58478
-0.4821 24 96.458 0.56222 0.85551 0.28722 1.83702
-0.5531 28 96.0355 0.70505 0.90826 0.30063 2.05061
-0.5871 30 95.841 0.77631 0.93159 0.30651 2.14463
Strengthening Microprudensial Policy
to Improve Stability of Islamic Banking
According Beikos (1997) and Errico and Farahbaskh
(1998), Islamic banks have higher levels of financial risk
than the conventional bank:
– Most of the investment bank in the form of Islamic profit sharing
financing (PLS) scheme, the income of banks, which are
generally sourced from PLS, has a relatively high variance
– The Islamic banks bore substantial liquidity risk due to a large
number of assets in the form of non-liquid assets
– The Islamic bank is predominantly exposed to the risk of
exchange rate because they are prohibited by Sharia to hedge
its position
Three Things or Steps to Reduce /
Prevent Risks Arising from
Intermediation Activities
1) Application of Integrated Banking Model
2) Polling of Fund Concept
3) Allocation of Fund Concept
Five Hypotheses According Irfing
Fisher
• The money growth is source of inflation
• Money supply is exogenous in nature
• The money demand is a stable function of nominal
income and interest rate
• Injecting money into economy is not able to affect the
output in the long run
• The real of interest rate is merely influenced by nonmonetary factor, such as productivity of capital and time
preference
Instruments of Macroprudential
Policy
• Strengthening the resilience of capital and preventing
excessive leverage
• Managing intermediation and controlling credit risk, liquidity
risk, foreign exchange risk and interest rate risk, as well as
other risks which could potentially become systemic
• Limiting exposure concentration
• Strengthening the resilience of the financial infrastructure
• Improving the efficiency of the financial system and financial
access
In the future, Instruments of Macroprudential
Policy should be directed towards
• Instruments which affecting MV (instruments on the
financial sector, like current instruments)
• Instruments which affecting PT (instruments on the
real sector)
• Instruments which include conventional and Islamic
macroprudentials.