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Yoghi Citra Pratama: Macroeconomic Variable and Its Influence  59

 
MACROECONOMIC VARIABLE AND ITS INFLUENCE ON 

PERFORMANCE OF INDONESIAN ISLAMIC BANKING 

Yoghi Citra Pratama1 

 
Abstract. Macroeconomic Variables and Its Influence on Performance of 
Indonesian Islamic Banking. The purpose of this research is to analyze the 
macroeconomics variables that affect to the performance of Islamic banks in 
Indonesia. Methods used in this research is the Vector Auto regressive (VAR) / Vector 
Error correction model (VECM) to see the effect of the shock and the long-term 
effect on the performance of Islamic Banking. The results show that based on the 
analysis of IRF, the performance of Islamic banking having short-term shocks to 
fluctuations in macroeconomics variables but stable in the long term, and based on 
the variance decomposition, shocks of macro variables only gives little effect on the 
performance of Islamic banking.

Keywords: Performance, Islamic banking, VAR, Macroeconomic variable

Abstraksi. Pengaruh Variabel Makroekonomi Terhadap Kinerja 
Perbankan Syariah di Indonesia. Tujuan dari penelitian ini adalah untuk 
menganalisis pengaruh variabel makro ekonomi terhadap kinerja bank syariah 
di Indonesia. Metode yang digunakan dalam penelitian ini adalah Vector Auto 
Regresive (VAR)/Vector error correction model (VECM) untuk melihat efek 
dari shock dan efek jangka panjang terhadap kinerja Perbankan Syariah. Hasil 
penelitian menunjukkan bahwa berdasarkan analisis IRF, kinerja perbankan 
syariah memiliki guncangan jangka pendek terhadap fluktuasi variabel 
makroekonomi tapi stabil dalam jangka panjang, dan berdasarkan dekomposisi 
varians, guncangan variabel makro hanya memberikan sedikit efek pada kinerja 
perbankan syariah. 

Kata Kunci: Kinerja, perbankan Islam, VAR, Variabel makroekonomi

First draft: September, 15th 2014, Revision: November, 30th 2014, Accepted: December, 16th  
2014

1 Syarif Hidayatullah State Islamic University. Jl. Ir. H. Juanda No. 95, Ciputat, South 
Tangerang, Banten, Indonesia.

Email: yoghi@uinjkt.ac.id



Al-Iqtishad: Vol. VII No. 1, Januari 2015 60

Introduction 

Globalization and integration of the financial sector in the world economy 
led to the depedency among countries in the world. Globalization means more 
corelation among countries especially in connection to world trade and financial 
market either directly or indirectly, this is proved by the global financial crisis that 
occurred in 2008, where the financial crisis that began in the United States has 
effected to the other countries in the world.The 2008 global financial crisis that 
started in the U.S. in late 2007 has given a wide array of impacts to the operating 
and financial performance of many banks all over the world . As a result, many 
banks across the world reported financial loss on their financial reportdue to 
their connections with subprime mortgage in the U.S. or were simply affected by 
economic recession in theirown countries. 

The impact of the crisis have even forced around 123 banks in the U.S. to file 
for bankruptcy in theyear, including American giant bank Lehman Brother that was 
never been expected to fail (Hidayat and Abduh, 2012). Indonesia is also get the 
impact of global crisis, that  can be seen from a number of macroeconomic indicators  
in Indonesia. The impact of the crisis also approached the financial and banking 
system in Indonesia, it can be seen from the financial ratios of banks that had a 
significant correction, including the banking system which uses a sharia based

The development of Islamic banks in Indonesia is growing  faster when the 
government is fully committed in 1998 by issuing Law No. 10 in 1998 to enhance 
the previous Act, Act 7 of 1992, which provides institutional and operational 
developments of Islamic banking in a comprehensive manner. With this legislation,  
dual banking system has been implemented, in which the conventional banks and 
Islamic banks recognized and both are regulated and supervised by Bank Indonesia. 
When business unit has enacted Law No. 21 2008 on the Islamic Banking on July 
16, 2008, then as a follow-up mandate of the Act referred to, some new policies 
must be drawn up and some of the provisions that have been issued by Bank 
Indonesia should be adjusted to remain focused on six aspects, including adherence 
to Islamic principles, compliance with prudential aspects, the development of 
operating efficiency and competitiveness, and system stability benefits to the 
economy, improving the competence and professionalism of human resources, as 
well as the optimization of social functioning of Islamic banks in facilitating the 
voluntary sector / social with people’s economic empowerment efforts. (LPPS Bank 
Indonesia, 2008). 

Based on BI data in June 2012, the number of Islamic banks were established 
11 the number of bank offices in 1780, and the number of conventional banks that 
have Islamic business units are 24and the number of bank offices 521. Coupled 



Yoghi Citra Pratama: Macroeconomic Variable and Its Influence  61

with rural Islamic banks amounted to 158, the number of office 398. development 
of Islamic banking assets also increased rapidly and above the average of national 
banks. 

Graph 1. The development of Islamic Banking Assets

Source: Bank Indonesia 

From the graph above can be shown that the development of Islamic banking 
assets increased significantly from 50 million in 2008  to 150 trillion in 2011 even 
growth of Islamic banking assets has fluctuated, although still above the average 
national banks, Islamic banks grow to over 30 % since the year 2008 and reached its 
peak in 2010, which reached 70%. This illustrates that Islamic finance industry has 
great potential and is not overly affected by the global financial crisis. 

Years 2008 to 2009 was a challenging year for the financial system, both 
domestically and globally because in that year the world was hit by the global 
financial crisis. The crisis that began with subprime mortgage in the United States 
has disrupted the stabilization of the global financial system, the effect is even to 
countries in Southeast Asia, including Indonesia. Many international and domestic 
financial institutions have liquidity problems because they are involved too deeply 
in financial derivatives sector. In addition, the global crisis has also hampered the 
Indonesian macroeconomic system. Where economic growth declined from 6.3% 
at the end of 2007 to 6.1% in late 2008 and in 2009 was estimated according to 
Bank Indonesia’s economic growth will also be corrected to 4.3%. Inflation reached 
its highest level of the 12.07% in September 2008, which since 2007 has always 
been below the range of 10% . Rupiah exchange rate also depreciated against the 
dollar, to ever reach 12,150 rupiah per dollar in November 2008. 



Al-Iqtishad: Vol. VII No. 1, Januari 2015 62

The global financial crisis also makes BI as monetary authorities create policies 
like lowering the interest rate (BI Rate) by 300 basis points since November 2008 
to encourage the growth of the real sector. The judging from the characteristics of 
Islamic banking if interest rates rise, it will suppress the growth of Islamic banking 
deposits, which in turn will impact on the level of profitability, and vice versa if 
the interest rates tend to fall in deposits of Islamic banks will increase. Currently 
September 2009 Bank Indonesia interest rate has dropped to 6.5% from its highest 
point of 9.5% in November 2008. 

The crisis that occurred in 2008 is an implication of the loss of the monetary 
sector linkages with the real sector. Monetary sector has grown so fast through 
derivative products, cross-country over the edge. The development of the monetary 
sector so quickly is not matched by the real sector, resulting in an economic bubble. 
Money becomes a tool commodity is traded with other debt securities, as a result of 
speculative motives. 

The global financial crisis in 2008 tends to slow the pace of economic 
growth in many countries and lead contraction of macroeconomic indicators. It is 
expected to have minimal impact on the national Islamic banking industry. There 
are several reasons why it believed the effect of the global financial crisis in 2008 
was not significant to the national Islamic banking industry. First, the concept of 
sharia-based real sector and based on an underlying asset in the transaction, requires 
that the monetary sector developed by the real sector. Islamic banking financing 
portfolio exposure is almost 100% channeled in the form of business financing 
in productive sectors (real sector), where the concentration of the business sector 
financing of Islamic banking is the domestic business sectors that are not directly 
related to foreign trade (LPPS Bank Indonesia, 2012). 

While the quality of Islamic banking financing is still relatively well preserved, 
as seen from the ratio of the NPF industry several years this is still maintained at an 
average rate of 3%. And sector financing is minimal from the financing of foreign 
trade enterprises. This means that the national Islamic banking financing are still 
dominant in the domestic market. It is because Islamic banking financing capacity 
is relatively limited. Secondly, the nature guided by the principles of sharia, Islamic 
banking is not allowed to use products based on interest and speculation. Here are 
the indicators of financial ratios that show the performance of Islamic banking in 
2007-2012.

From the table 1, we see that in general the global financial crisis has not 
significantly affect the performance of the national Islamic banking, if in view of 
the growth of financing (loans) of banks or Financing to Deposit Ratio (FDR) is 
still high with an increasing trend since 2005 to reach 103 , 65% in 2008, with 



Yoghi Citra Pratama: Macroeconomic Variable and Its Influence  63

the level of financing (credit) problematic or Non Performing Financing (NPF) is 
still kept below 5% and experienced a decreasing trend from 2007 to reach 2.22% 
by 2012. This means that Islamic banking still function properly as intermediary, 
by channeling financing to the real sector. In addition, Islamic banking has a great 
durability against the global crisis with the NPF rate remains below 5%.

 Table 1. Performance Indicators of Islamic Banking

Ratio 2007 2008 2009 2010 2011 2012

CAR 10. 67% 12. 81% 10. 77% 16. 25% 16. 63% 14. 13%

ROA 2. 07% 1. 42% 1. 48% 1. 67% 1. 79% 2. 14%
ROE 40. 38% 38. 79% 26. 09% 17. 58% 15. 73% 24. 06%
NPF 4. 05% 1. 42% 4. 01% 3. 02% 2. 52% 2. 22%

FDR 99. 76% 103. 65% 89. 70% 89. 67% 88. 94% 100. 00%

BOPO 76. 54% 81. 75% 84. 39% 80. 54% 78. 41% 74. 75%

Source: Bank Indonesia

Based on CAR, Islamic Banking a good performance in capital adequacy ratio. 
It is about  8% in 2011 and the highest rate reaches 16.63%.  Thus, the bank should 
obtain a profit from lending activities (FDR), which continues to increase with the 
level of non performing financing (NPF), which tends to decrease.  However, in the 
profitability ratio, ie the indicator Return on Assets (ROA) and Return on Equity 
(ROE) in 2008, ROA is decreasing into 1.42% compared to 2007 ;2.07%. Same 
as ROE indicator, it’s the highest point was 40.38% in 2007, and decreased into 
15.73% in 2011. Then it began to increase up to 24.06% in 2012.Based on the 
above data, the authors are interested to find out  the influence of external factors 
such as macro-economic variables which are contracted due to the impact of the 
global financial crisis to the performance of Islamic banking. Based on the exposure 
above, the authors formulate the following research questions. 

How does the performance of Islamic banking  which are proxy by FDR, 
CAR, NPF and ROA in the face of a global crisis that is shown by contracted the 
macroeconomic variables such as SBI interest rate, exchange rate and inflation rate 
from year 2007- 2012? 

Literature Review

Macroeconomic conditions have an important role in the performance of 
banking. Kunt (2000) describes the factors that determine the occurrence of banking 
crises that can affect the performance of banking including  macroeconomic factors, 



Al-Iqtishad: Vol. VII No. 1, Januari 2015 64

financial, and institutional. Since the early 1980s, macroeconomic problems became  
systemic problems in the banking sector that has happened in most countries. 
Vulnerable banking crisis occurs in a weak macroeconomic conditions. Low GDP 
may increase the risk in banking sector. Vulnerability to shocks on aggregate output 
is not always a sign that the banking system is not efficient, because the role of banks 
as financial intermediaries are risk taking. Increased risk in the banking sector is also 
caused by high levels of inflation. So that the tightening of monetary policy is used 
to create stability in the banking sector

Second is the financial factor. High real interest is not only caused by stability 
policy of inflation, but also by others like financial liberalization.  The degree of 
financial liberalization significantly affect the likelihood of a banking crisis even 
though real interest rates can be controlled. The third is the institutional factor. 
This factor will focus on internal activities within banking. The existence of deposit 
insurance schemes tend to increase the likelihood of systemic problems in banking. 
When on one side of the deposit insurance may reduce any panic in the banking 
sector, but on the other hand the existence of deposit insurance may lead to moral 
hazard. Therefore, reduce acts of moral hazard in the implementation of the deposit 
insurance is a top priority in the banking system. 

The affect macroeconomic research on the performance of banks and other 
financial institution have been carried out in the world today. Bank of England 
(2003) in the research used the method of estimating and calculating (VAR) 
found its banking system losses in the face of macroeconomic variable shocks. The 
Reserve Bank of Australia also collects all of his resources to calculate and identify 
the relationship between bank profitability and bank resilience to contraction of 
macroeconomic variables in Australia (see Gizycki, 2001). Athanasoglu and Delis 
(2005) also studied the effects of fluctuations in macroeconomic variables to the 
profitability of Islamic banking in Greece, the results show that the inflation as a 
significant positive affect on the profitability of banks which are proxy by return on 
equity (ROE) and return on assets (ROA). 

In the context of macro economic management, Clair (2004) in his research 
in Singapore found that on average two-thirds of the bank’s performance is closely 
linked to the performance of macroeconomic variables. Islamic banking has 
different characteristics from conventional bank, but Islamic banking transactions 
which based on real sector also can not be separated from economic conditions. In 
some empirical studies, there are not direct correlation between changes in bank’s 
performances and the business cycle. Both income and expenditure are likely to be 
pro-cycle where the outcome for profit depends significantly on the banks’ expense 
policy and their credit risk profile. The relationship between risk and return depend 



Yoghi Citra Pratama: Macroeconomic Variable and Its Influence  65

on how banks price for risk and the lags between taking on risk and the crystalisation 
of the risk into realised profit or losses. When GDP increases, banks may earn higher 
returns by taking on greater risk, which boosts profits. However, if a bank suffered 
a loss, it subsequently beyond what it had provisioned, so the losses will reduce its 
profitability (Clair, 2004).

The research about the impact  of macroeconomic condition to Islamic 
banking performance have been also carried out in the world today. Hassan and 
Dridi (2010) compare the performance of Islamic banks (IBs) and conventional 
banks (CBs) since the recent global crisis by looking at the impact of the crisis on 
profitability, credit asset growth, and external ratings in a group of countries where 
the two types of banks have significant market share. The study suggests that IBs 
have been affected differently than CBs. Those factors related to IBs‘business model 
helped limit the adverse impacton profitability in 2008, while weaknesses in risk 
management practices in some IBs led to a larger decline in profitability in 2009 
compared to CBs. IBs’ credit and asset growth better than CBs in the year 2008–09.  
This contributes the financial and economic stability. Therefore, the external rating 
agencies‘re-assessment of IBs‘risk was generally more favorable. 

Noor and Ahmad (2011) studied the efficiency of the 78 Islamic banks in 
25 countries in 1992–2009. The Fixed Effect Model used to examine the impact 
of operating expenses to assets, equity, high income countries and non performing 
loans to total loans on profit efficiency.  They found that the operating expenses 
to to the high equity of assets and high income countries, have a positive and 
significant effect onfinancial performance of Islamic banks. Asma, Fadi and Noor 
(2011) examined the determinants of profitability of Islamic banks in Malaysia. 
Number of Islamic banks in specifics variables had been used capital adequacy, and 
management of expenses credit risk, liquidity, Log total assets. They found that only 
the bank’s size has a positive significant impact on profitability of Malaysian Islamic 
banks. While the other variables have no impact on Islamic’s banks profitability. 
Bashir (2003) investigated the determinants of profitability for 14 Islamic Banks 
from 8 Middle Eastern Countries. He found that total equity to total assets, loans 
to total assets and overhead (salaries, wages, and investment cost) have a positive and 
significant impact on profitability measured by (ROA), (ROE) and basic earning 
power. Gross domestic product growth has a positive and significant impact on 
Islamic banks profitability (Mustafa and Ali, 2013).

Methods 

This research is a descriptive-correlational research (causal) that will explain 
the relationship of macroeconomic variables ( inflation, interest rates Certificates 



Al-Iqtishad: Vol. VII No. 1, Januari 2015 66

of Bank Indonesia, the rupiah exchange rate against the dollar) and variables of the 
performance of Islamic Banking which are proxy by CAR, NPF, FDR, and ROA, 
to know whether those variables have positive or negative influence. Descriptive 
research is an explanation of the characteristics, profile, and relevant aspects of the 
phenomenon of the research object (Nachrowi and Usman, 2007). 

The data analysis of the study is Vector Auto reggresive (VAR)/Vector Error 
Correction Model (VECM), which aims to look at short-term relationships and 
using cointegration test to see indications of the long-term relationship. Analysis of 
data will be done with the help of computer application programs such as E-views 
6. 

VECM testing can only be conducted if there are indications of a long-term 
correlation using cointegration test. The Variables are identified to be cointegrated 
when stationary at the same order. The Augmented Dickey Fuller (ADF) Test used 
to test the stasioner data. In the ADF test is done by adding (augmenting) the value 
of the lag on the dependent variable. Specifically, the ADF test follows the following 
equation: 

ΔYt = β1 + + δYt β2t-1 + Σ α ΔY t-1 + έt 
the study used data natural log (ln) of the variables, except for the variables 

that are already in the unit of percentage, that method is useful for solving the 
equation. Logs model is a model which states measure the elasticity of Y with respect 
to X,  the size of the percentage change in the percentage change in Y when X is 
known by the model Ln_Y = α + β1 + ε ln_x. 

Vector Autoregressive (VAR) is used to see the effect of macroeconomic shocks 
on the performance of the Islamic banking. While the methods of Vector Error 
Correction Model (VECM) will be used if there are diffrent stationary variables. 

Discussion 

In the first stage of data characteristics will be tested using the unit root 
test. Unit root test is necessary to determine the data according to Gujarati the 
data become stasioner if the data of the time series data sets (time series data) had 
an average (mean) and variance are constant over time, except that the value of 
covariance  between two period of time only depends on the distance or lag of two 
periods of time and does not depend on waktu.Data Exchange in this study in the 
form of natural logarithm (ln), to simplify the analysis. 

The test of stasioner is a major requirement in the cointegration test, if the 
time series data are not stationary, then the model will have problems unit root, so 
that the handle unit root test (unit root test). In this study the unit root test is done 



Yoghi Citra Pratama: Macroeconomic Variable and Its Influence  67

by using Augmented Dickey Fuller test (ADF test). Variable that has a value smaller 
than its McKinnon then these variables have stationary. Testing the unit root can 
also be determined by the value of its critical value, if the value of the ADF is larger 
than the critical value then the variable valuenya Stationary, otherwise if the ADF 
if indigo is smaller than the value of critical value (CV) 5% then the data is not 
stationary. The results of the unit root test can be seen from the following table:

 
Table  2. Augmented Dickey Fuller test (First Diffrencing)

No. Variables
 Ho = There is a stationary

Ha = StationaryADF test CV 5%
1 CAR -7.018919 -2.954021 Stationary
2 FDR -7.143259 -2.951125 Stationary
3 NPF -7.704743 -2.951125 Stationary
4 ROA -8.973787 -2.951125 Stationary
5 SBI -3.461580 -2.951125 Stationary
6 INFLATION -3.765297 -2.951125 Stationary
7 EXCHANGE -5.339399 -2.951125 Stationary
 
Results of stationarity test data showed no variables are stationary at level. 

Therefore variables derived in first-degree diffrencing, as listed in the table above. 
The next stage is the determination of the optimal lag. Determination of the optimal 
lag is very important because the independent variable used is nothing but a lag of 
endogenous variables. Determination of the optimal lag is done based on the value 
of Schwartz information criterion (AIC). Selection of optimal lag cointegration test 
done before, it is important to do before estimating Vector Autoregressive (VAR) 
model. Election lag length is important because it can affect the acceptance and 
rejection of the null hypothesis, resulting in biased estimates and could result in 
inaccurate predictions. 

Graph 2. Impulse Response Function On CAR

-0.5

0.0

0.5

1.0

1.5

5 10 15 20 25 30 35 40 45 50

Response of DCAR to DCAR

-0.5

0.0

0.5

1.0

1.5

5 10 15 20 25 30 35 40 45 50

Response of DCAR to DINFLASI

-0.5

0.0

0.5

1.0

1.5

5 10 15 20 25 30 35 40 45 50

Response of DCAR to DKURS

-0.5

0.0

0.5

1.0

1.5

5 10 15 20 25 30 35 40 45 50

Response of DCAR to DSBI

Response to Cholesky One S.D. Innovations

The longer the lag is used to reduce the degree of freedom and the number 
of observations, while the amount of lag that is too short will result in incorrect 



Al-Iqtishad: Vol. VII No. 1, Januari 2015 68

specification (Gujarati, 2007). The issue of the selection of lag length also increased 
with the assumption that the selection of the appropriate lag will result in residual   
(free from autocorrelation and hetroskedastisitas) (Gujarati, 2007). To define the 
optimal lag value typically used Akaike information criteria (AIC), Final Prediction 
Error (FPE), Hannan-Quinn Information Criterion (HQ) and Schwarz Information 
Criteria (SC). 

In this study the magnitude of the lag is selected based on the value of the 
smallest SC. SC calculations every lag. From the test results it is known that CAR 
models, FDR, NPF and ROA indicates optimal lag one, is evident from the value 
Schawart Information Criteria and Hannan-Quinn Information that shows the 
smallest value in lag 1.

Graph 3. Impulse Response Function On FDR

-1

0

1

2

3

1 2 3 4 5 6 7 8 9 10

Response of DFDR to DFDR

-1

0

1

2

3

1 2 3 4 5 6 7 8 9 10

Response of DFDR to DINFLASI

-1

0

1

2

3

1 2 3 4 5 6 7 8 9 10

Response of DFDR to DKURS

-1

0

1

2

3

1 2 3 4 5 6 7 8 9 10

Response of DFDR to DSBI

Response to Cholesky One S.D. Innovations

From the graph 2, it is known that the impulse respone function test results 
showed that the CAR response to inflation shock. Seen from the table above it can 
be seen that CAR responds positive to inflation shock until at 25th period, after it 
fluctuates into a negative and stable at zero in the long run in the 40th period. CAR 
response to fluctuations in the exchange rate is negative at15th period after having 
a positive movement in the short term and having stability at 35th period. Firstly 
CAR response to SBI with fluctuates and have negative relationship at eight period 
after that in the short term CAR responds positively and achieve stable movement 
began at 25th period.

Graph 4. Impulse Response Function On NPF

-.1

.0

.1

.2

.3

1 2 3 4 5 6 7 8 9 10

Response of DNPF to DNPF

-.1

.0

.1

.2

.3

1 2 3 4 5 6 7 8 9 10

Response of DNPF to DINFLASI

-.1

.0

.1

.2

.3

1 2 3 4 5 6 7 8 9 10

Response of DNPF to DKURS

-.1

.0

.1

.2

.3

1 2 3 4 5 6 7 8 9 10

Response of DNPF to DSBI

Response to Cholesky One S.D. Innovations



Yoghi Citra Pratama: Macroeconomic Variable and Its Influence  69

The graph 3, explains that FDR respond positive to movements the inflation 
in the short term until the 7th period but after that FDR had a tendency to respond 
negative to inflation. FDR suffered shocks to the exchange rate in the short-term and 
has positive response but at 2nd period until 3.5 period responded to the negative, 
then returned with a positive response at the 4th period  and tend to have stability in  
9 period. FDR’s response positive  to SBI untilat 5th period after that  FDR respond 
with negative long-term and having stable negative respond to SBI.

Inflation give a stable respond at the beginning of the second period, after that 
NPF respond negatively to inflation shocks until the 4th period and thereafter gave 
a positive response, its mean the higher of the inflation rate will cause the greater 
the level of NPF. Exchange rate give negative effect to NPF untill third period, after 
that at the fourth period the movement of NPF as the respond of exchange rate is 
stable at posisitve respond. NPF respond positively to the shock caused by SBI until 
seventh period, after that NPF respond negativly to SBI.

Graph 5. Impulse Response Function On ROA 

-.05

.00

.05

.10

.15

.20

.25

1 2 3 4 5 6 7 8 9 10

Response of DROA to DROA

-.05

.00

.05

.10

.15

.20

.25

1 2 3 4 5 6 7 8 9 10

Response of DROA to DINFLASI

-.05

.00

.05

.10

.15

.20

.25

1 2 3 4 5 6 7 8 9 10

Response of DROA to DKURS

-.05

.00

.05

.10

.15

.20

.25

1 2 3 4 5 6 7 8 9 10

Response of DROA to DSBI

Response to Cholesky One S.D. Innovations

 

The graph above explains that the inflation gave negative shock to ROA but 
after  second period, inflation tend to brought to the zero and ROA gives a positive 
response to inflation until the seventh period.  Exchange rate Shock  give positive 
effect on ROA and tend to be stable in the eight period after that ROA tend to 
negative respond exchange rate. SBI give ROA negative response and tend stable. 

 Table 3. Variance Decomposition Model (1) CAR 

Variance Decomposition of DCAR:
 Period SE DCAR DINFLASI DKURS DSBI

 1  1.336783  100.0000  0.000000  0.000000  0.000000
 2  1.402522  96.34677  0.999679  1.290292  1.363259
 3  1.564987  77.39283  15.34615  3.777673  3.483345
 4  1.718135  65.05940  27.45176  3.795459  3.693382
 5  1.804432  59.68344  32.93968  3.840892  3.535995
 6  1.853637  56.60407  35.79475  4.219619  3.381558
 7  1.884897  54.74216  37.36704  4.613230  3.277570



Al-Iqtishad: Vol. VII No. 1, Januari 2015 70

 8  1.903068  53.70180  38.09582  4.879719  3.322669
 9  1.914722  53.05528  38.37929  5.049229  3.516196
 10  1.924163  52.56504  38.50542  5.131814  3.797723

From the result of variance decomposition on table 3, it can be seen that in 
the first period CAR is influenced by variables itself with a value of 100%, in tenth 
periodCAR is influnced by its own variables at 52.56% and other variables affecting 
the tenth period CAR is the inflation rate effect  38.50%, then the variable exchange 
rate effect of 5.13 % and SBI whose give influence of 3.79%. 

Table 4. Variance Decomposition Model (2) FDR 

 Variance Decomposition of DFDR:
 Period SE DFDR DINFLASI DKURS DSBI

 1  2.814258  100.0000  0.000000  0.000000  0.000000
 2  3.405376  84.61833  0.210797  0.092497  15.07838
 3  3.668259  82.08140  0.448766  0.314167  17.15567
 4  3.743162  80.62526  0.560337  0.556163  18.25824
 5  3.762227  80.16739  0.715868  1.040097  18.07664
 6  3.790074  79.08602  0.753053  1.856415  18.30451
 7  3.828620  77.61979  0.750023  2.422237  19.20796
 8  3.875368  76.01495  1.058916  2.624580  20.30155
 9  3.935000  74.13494  2.129524  2.577904  21.15764
 10  4.013154  71.73056  4.159672  2.495334  21.61443

From the table 4, it is known that variable FDR in the first period is influenced 
by the variable itself at 100%, then the period of ten variables FDR is affected by 
the variable itself influenced by71.73% and the second biggest variable whose gives 
influenced is SBI at 21.61%. Further, inflation gives influenceat 4.1% in the period 
of ten and Exchange rate effect of 2.49 percent in the period of ten. 

Table 5. Variance Decomposition Model (3) NPF 

  Variance Decomposition of DNPF:
 Period SE DNPF DINFLASI DKURS DSBI

 1  0.276172  100.0000  0.000000  0.000000  0.000000
 2  0.333364  93.52451  0.002483  3.455156  3.017851
 3  0.368386  91.48392  0.423766  2.847924  5.244388
 4  0.389198  90.71460  0.379816  2.590996  6.314587
 5  0.404310  89.79314  0.731620  2.935515  6.539726
 6  0.418169  87.97660  2.022665  3.743844  6.256896
 7  0.432684  85.32802  4.008094  4.819740  5.844142



Yoghi Citra Pratama: Macroeconomic Variable and Its Influence  71

 8  0.447077  82.50230  6.047942  5.901228  5.548534
 9  0.459898  80.09056  7.595677  6.878989  5.434774

 10  0.470083  78.34647  8.463037  7.726345  5.464146

From the table 5, it can be seen that the NPF variable is influenced by the 
variable itself by 100% in the first period and the second period NPF variable is 
affected by exchange rate at 3.45% and SBI at 3.01% and then inflation gives 
influence at 0.002%. In the period of ten variables NPF influenced by variable itself 
by 78.34% and then followed by Inflation at 8.46%, then the variable exchange rate 
influnced NPF at 7.72% and then SBI gives influence to NPF at 5.46%.

Table 6. Variance Decomposition Model (4) ROA 

 Variance Decomposition of DROA:
 Period SE DROA DINFLASI DKURS DSBI

 1  0.199317  100.0000  0.000000  0.000000  0.000000
 2  0.208445  91.79469  2.538893  5.466057  0.200362
 3  0.214047  87.05893  4.309262  6.587490  2.044313
 4  0.220805  81.81397  7.030236  7.716723  3.439071
 5  0.225816  78.49478  8.614079  8.245917  4.645228
 6  0.228713  76.77743  9.181591  8.347609  5.693366
 7  0.230104  75.98051  9.143707  8.307620  6.568164
 8  0.231127  75.34009  9.147700  8.234731  7.277482
 9  0.232516  74.44299  9.549156  8.192048  7.815805

 10  0.234446  73.24785  10.34849  8.208393  8.195273

From the table 6, it is known that the variable ROA in the first period is 
influenced by the variable itself amounted to100% and then in the second period 
is affected by the exchange rate at 5.46%. Further, it’s influenced by inflation at 
2.5% and SBI gives influenced to ROA at 0.20%. In the tenth period ROA variable 
affecting itsself by73.24%, and further variable ROA influenced by inflation of 
10.34% and the exchange rate amounted to 8.2% and the last SBI gives influenced 
to ROA at 8.19%.

Conclusion 

This empirical study provides several important findings; firstly based on 
analysis of impulse response function is known that the performance of the Islamic 
banking which are proxied by CAR, FDR, NPF and ROA had short-term shocks 
to macroeconomic fluctuations due to the financial global crisis. However, the 
performance of Islamic banking showed stable tendency in the long run. Secondly, 



Al-Iqtishad: Vol. VII No. 1, Januari 2015 72

based on the test of Variance Decomposition  is known that the performance of 
Islamic banking which are proxied by CAR, FDR, NPF and ROA is affected by 
the variable itself in the first period and thereafter until the tenth period apparently 
Inflation provide second biggest influence to Islamic banking performance, it can 
be seen from its effect on CAR in the tenth period are giving out the effect of 
38.5%, and give influence 8.46% to NPF and 10.34% to ROA. Diffrent form 
others variables, the second biggest variables whose influenced FDR is SBI, whose 
gives the effect of 21.61%.

The findings lead to the empirical conclusion that performance of Islamic 
banking is affected by fluctuations in macroeconomic variables in the short term but 
has a tendency to improved and stabilized quickly, this is because Islamic banking 
in running its operations related to the real sector, therefore the development of 
Islamic banking should be encouraged as much as possible in order to encourage 
economic growth and sustainable development.

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