A Dynamic Panel Data Analysis for Islamic Finance and Economic Growth
Tarek Sadraoui^{1, *}, Hanen Hleli^{2}
^{1}Departmentof Quantitative Methods, Higher Institute of society Administration, Gafsa, Tunisa
^{2}Departmentof Quantitative Methods, Economics and Management Faculty of Sousse, Sousse, Tunisia
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To cite this article:
Tarek Sadraoui, Hanen Hleli. A Dynamic Panel Data Analysis for Islamic Finance and Economic Growth. International Journal of Economics, Finance and Management Sciences. Special Issue: Islamic Finance System and Economic Growth: Theory and Empirical Studies. Vol. 3, No. 5-2, 2015, pp.1-6. doi: 10.11648/j.ijefm.s.2015030502.11
Abstract: This paper examines the dynamic interactions between Islamic Finance and economic growth by employing panel data econometrics, the Cointegration test and Unit root tests to see whether the financial system influences growth and growth transforms the operation of the financials system in the long-run. We use panel data of total Islamic bank financing and real GDP per capita, fixed investment, and other variables to represent real economic sectors. We found that in the short-run only fixed investment that granger cause Islamic bank where as in the long-run, there is evidence of a bidirectional relationship between Islamic Finance and fixed investment and there is evidence to support demand following hypothesis of GDP and Islamic Finance, where increase in GDP causes Islamic banking.
Keywords: Islamic Finance, Economic Growth, Causality, Panel Data Econometric
1. Introduction
Islamic law (Sharia) has been proven theoretically and empirically since the dawn of Islam. This Islamic law plays an important role in the lives of Muslims in economic, social, political and strengthening of the state and its internal and external relationships... it is characterized by validation in every time and place.
In Islamic law (Sharia), justice and in justice prevail melted, and free do prevail and the fade servitude. Assaid Ben Amer Kissra "We came out people from the worship of people to worship the Lord of mankind and Go religions to the justice of Islam, and think to a minimum capacity of this world and the hereafter.
In reality, the Muslim day after day does not want to apply the Sharia. And require the separation between religion and state as does the western world when they separated religion- of all things whatever political, economic, social... they for go to ne great thing that the separation between religion and the state in the West is right that their religion is corrupted and will be destroyed their social, economic...
The beginnings of Islamic finance dating back to 1940 marks the birth of the first Islamic bank in Malaysia and Egypt. However the true emergence of Islamic finance is only in the 1970s this emergence led to the emergence of Islamic banking in Pakistan in 1979 and Iranin 1983. How development is concentrated in the countries of the Middle East and Asia the southeast.
In return, the development of Islamic finance in the world is at the beginning of 2008 or the financial and economic crisis has shown the flaws in the practice of international financial system in the real state sector. Consequently, the crisis led to financial imbalances, economic and bankruptcy of large institutions in the world among the American economy.
Indeed, Islamic finance is a concept that still arouses wide controversy, and because she was al way striated as an ideological angle.
This paper is organized as follows: the next section describes the literature on Islamic finance and economic growth. In particular, we analyze clues under which Islamic finance makes economic growth more profitable. Indeed, this paper challenges our problem and is a general synthesis for the purpose of the relationship between Islamic finance and economic development.
The purpose of the third section gives results between Islamic finance and economic growth. The final sections hap of the empirical validation test based on the static panel data.
2. Literatures on Islamic Finance and Economic Growth
In the theoretical literature the increase of wealth and finance are perfectly compatible with the Islamic vision in the world provided that the importance economic growth meets the standards of Islamic ethics. Despite the importance of this research studies on the relationship between Islamic finance and economic growth are scarce.
Indeed, in remarks today of great importance in the Islamic financial sector in the Muslim world and also non-Muslim, however, that the Islamic financial sector is crucial for meeting the economic needs and economic growth.
Indeed, a study by Ridha Saadallah in 2013 in his paper "Islamic Finance and Development" shows that Islamic finance allows financial traders of their projects. It presents two planes on which Islamic finance promotes economic development. In the foreground, Islamic finance profit of participatory finance where that leads to finance sustainable projects source of investment to economic growth.
Indeed, on a second plane, Ridha Saadallah noted that Islamic finance does not exist only for Muslims; it offers advantages for investors for projects in which the coexistence of conventional finance and Islamic finance allows economic development from the contribution of reaching importance of resource allocation efficiency.
In concludes that Ridha Saadalla in their article to mount the relationship between Islamic finance and economic development based on the benefits of the principles of Islamic finance.
Another paper of Hamdi Khalfaoui in 2010 "Islam and economic development" Guiso the present study, Sapienza and Zingales show that Muslims are"anti-market". They believe that Islamic finance is negatively one conomic growth.
On the other hand, the studies Siddiqi (2009) and Hassan (2009) show that Islamic finance can establish financial stability and economic wealth from their principles distinguished from conventional finance.
3. Results of Islamic Finance and Economic Growth
This work mainly aims to demonstrate that Islamic finance, including the prohibition of Riba, can improve economic growth in the MENA countries and Malaysia. The main factors that promote improved economic growth rate (GDP15% compared to conventional). Empirical validation test: an analysis by the static panel model
The purpose of this analysis is to examine in a static panel equation structure the role of Islamic finance in economic growth in MENA countries and Malaysia. First, the analysis focused on the impact of private sector credit factor of Islamic banking-according to other factors-on GDP. The primary objective is to show the effect of private sector credit of Islamic banking on GDP compared to the credit of private conventional banking sector.
3.1. Empirical Review
Empirical studies on the relationship between Islamic finance and economic growth are scarce as theoretical studies. In this section we present some works hows the important role played by Islamic banks compared to conventional banks.
3.1.1. Studies on Financial Stability
An empirical study takes on the role of banks in financial stability; this study includes a sample of 77397 Islamic banks and conventional banks from 19 countries in the Middle East, North and South East Asia Africa during a period from 1993 to 2004.
This work seeks z-score for each country to calculate a measure of financial stability and to compare for Islamic banks and conventional banks.
Indeed, the research results show that in terms of z-score is no significant difference between Islamic banks and conventional banks. This finding suggests that there is no effect dominates the link between Islamic banks and financial stability. However, the study shows that the estimate for small banks gives z-scores of Islamic banking superior to conventional small banks. But at the same time, large conventional banks would benefit from greater financial stability. Indeed, the size of Islamic banks defines the relationship between the banking sector and financial stability.
3.1.2. Studies on the Efficient Islamic Banking
This study seeks to find the impact of development of Islamic banks on the efficiency of conventional banks. Indeed, the change in bank efficiency can influence economic development.
Infact, two studies examine the efficiency of Islamic banks. Begin working Sraïri (2010) during the period 1999 to 2007 includes a sample of 23 Islamic banks and 78 conventional banks of the Persian Gulf countries. In return analysis geography studied by Abdul-Majid Battisti and Saal (2010) for a period from 1996 to 2002 in a sample of 23 Islamic banks and 88 conventional banks from 10 countries in the Middle East and South Asia.
Both studies found that the efficiency of Islamic banks is lower than conventional banks.
In other words, a study by Baele, Farooq and Ongena (2010) on the difference between Islamic and conventional loans. This analysis includes Pakistan business loans for a period from 2006 to 2008 based on data of the Central Bank of Pakistan or loans 150000. In this study the majority of loans are conventional and Islamic loans are only 5% Murabaha and Ijarakind of total loans.
The findings arise that Islamic banks default rate benefit weaker. This result can be explained by the greater costs of Islamic banks than conventional banks.
3.1.3. Islamic Banks Bring him to the Competition
Generally, banking competition contributes to a positive effect on economic growth. Indeed, several studies including Petersen and Rajan (1995) studied the importance of competition in economic development. In contrast, studies by Beck, Demirguc - Kunt and Levine (2004) and Weill Hainz and God lewski (2012) rise as banking competition from the reduced interest rate allows has a significant effect on the access to finance. Then finding the existence of Islamic banks that accesses banking competition can influence economic growth.
3.1.4. Funding for Islamic Banks Contribute to Growth
Empirical studies analyzes the role of finance Islamic banks on economic growth are scarce. Indeed, there may be mentioned figures allows favoring Islamic banks in the country. Khalaf (2008) provides interesting figures between 15% and 25% of the market share of Islamic banks in the Gulf countries. By cons according to The UK city, 18.9 billion estimate of the assets of Islamic banks in 2010 the United Kingdom.
An estimate analyzes the relationship between the total development banks, as measured by GDP and Islamic banking development, as measured by GDP. Conducted during the 2000-2005 period includes a sample of all Islamic banks worldwide. This analysis shows that the Islamic banking development is more important.
Iqbal, Munawar et al. (1998), analyzes the performance of Islamic banks; they based their studies on a sample of the top 10 banks in the world, the 10 leading banks in Asia, the 10 largest banks in the Middle East and end 10 first Islamic banks. They result from the industrial sector performance in Islamic banks are higher in a purely Islamic environment.
Hasan and Dridi (2010) estimates the correlation between Islamic banks and conventional banks for the period 2007-2008, they show that the growth rate of assets of Islamic banks is growing three times faster than conventional banks.
A study by Ben Hanan Rhouma shows that Islamic financial assets to achieve 812 billion euro’s at the end of 2012 it has improved compared to 2010 by 33% (according to are port released Tuesday, November 22 by the consultancy firm Ernst and Young). This study shows that the Middle East and North Africa (MENA) can reach the assets in 2015 of 990 billion against $416 billion in 2010, so in these countries economic growth should be particularly strong.
3.2. Model Presentation
Generally, the goal of researchers is not financial gain but to establish a principle of priority.
As part of our study we consider a function of log-linear Gobb-Douglas next production:
=+ln(+ln(+ln(
+ln(+ln(+ln(
i=1,....,N and t=1,....T
ε_{it}: Stochastic Term
i: Number of countries
t: Periods
Y_{it }Or GDP: Represents the real logarithm per capita for the country (i) of the year (t);
IIC: Represents the log of initial income per capita (constant 2000 US$);
CPSSIB: Represents the logarithm of private sector credit by the Islamic bank;
CPSCB: Represents the private sector credit logarithm by conventional bank;
INF: means the logarithm inflation, consumer prices (annual %);
TO: Represents (IMP+EXP) (% of GDP);
GC: Represents final consumption expenditure of general government as % of GDP;
The basic model considered in our empirical validation study is drawn from the literature on Islamic finance and economic growth.
We notice that GDP / head taken by countries depend on the initial income, private sector credit, inflation, open rates and expenditures of the final consumption.
We try to reflect the individual structure of the variables.
3.3. Studies Descriptive Statistics
We begin our study with the presentation of various descriptive statistics and specification tests or homogeneity test on our sample.
Therefore these are shown as follows in Table 1 below.
Variables | Mean | Std. Dev | Minimum | Maximum |
Log PIB | 1.190 | 1.58 | -7.233 | 6.356 |
Log Inf+1 | 1.654 | 1.767 | -3.846 | 15.745 |
Log GC | 2.64 | 1.717 | -8.660 | 14.177 |
Log CPSIB | 4.283 | 2.189 | -9.797 | 14.927 |
Log CPSCB | 3.800 | 0.793 | 1.073 | 4.905 |
Log IIC | 3.051 | 0.062 | 2.860 | 3.149 |
Log TO | 6.221 | 1.28 | 1.12 | 6.913 |
The results in Table 1 show that the average economic growth rate of the sample over the period studied is (1.190) % per year in the 15 countries; the average minimum value of the growth rate is (7233%); while the maximum is (6.356%). Regarding financial development indicators, the minimum values for the private sector credit Islamic Bank (9797%) and records the maximum (14,927%). To the credit of the private conventional banking sector, the minimum values of (1.073%) and maximum values (4.905%).
The lowest level of inflation is recorded (3846%) and the highest level is recorded (15,745%).
The higher initial income (3.149%) and the lowest (2.860%). The highest level in final consumption expenditure of general government is recorded (8660%) and the lowest is recorded. For the TO the lowest level is recorded (1.12%) and the highest level is recorded (6913%).
3.4. Correlation Matrix
Table 2 empirically studied the correlation between the variables, two conclusions deserve to be made; First, we note a low correlation, which is negative between GDP and private sector credit of Islamic banking (-0221) and private sector credit from the conventional banking (-0009). There was also a weak correlation, which is positive between private sector credit of Islamic banking and private sector credit from conventional bank (0019). As for inflation is, it is positively correlated with GDP (0.07).
Log PIB | Log INF+1 | Log GC | Log CPSIB | Log CPSCB | Log IIC | LogTO | |
Log PIB | 1.0000 | ||||||
Log INF+1 | 0.07 | 1.0000 | |||||
Log GC | -0.088 | 0.162 | 1.0000 | ||||
Log CPSIB | -0.221 | 0.125 | -0.085 | 1.0000 | |||
Log CPSCB | -0.009 | -0.097 | -0.016 | 0.019 | 1.0000 | ||
Log IIC | 0.050 | -0.10 | -0.015 | 0.04 | -0.33 | 1.0000 | |
Log TO | 0.018 | -0.007 | 0.02 | -0.027 | 0.006 | 0.38 | 1.0000 |
3.5. Specification Test of Homogeneity
The estimated model coefficients located if it is made by stata 11 software because this software is efficient in the context of studies based on panel data. It provides estimates of which three kinds of fixed effects models (individual), random effects (temporal) and Hausman test (common effects). The Hausman test allows choosing if the fixed effect model or random effect.
P-valueofHausman | 0.000 |
Model Specification | Fixed effect |
The results of Hausman tests Shown in Table 3. In fact, the probability (P value) is below the 5% threshold. Thus, one must accept the null hypothesis of the presence of fixed effects for the random effects.
First, we will choose model estimation (fixed effect model) to study the impact of private sector credit of Islamic banking on the rate of growth. Second, we will study the impact of the private sector of Islamic banking on the rate of growth in the 15 countries considered. In fact, the estimation results of the fixed effect model are shown in Table 4 below.
Coefficient | T-student | P-value | |
| 1.249 | 0.35 | 0.728 |
| 1.130 | 1.32 | 0.354 |
| -0.703 | -16.09 | 0.000 |
| -0.540 | -2.83 | 0.005 |
| 0.686 | 11.33 | 0.000 |
| 0.080 | 1.32 | 0.190 |
| -0.028 | -0.66 | 0.728 |
R2:within | 0.640 | ||
R2:between | 0.340 |
The β_{1 }parameter takes the value of 1.130 that is to say, theIICincreaseofoneunitgeneratesadecreaseinGDPinthe15 countries averaged million. Indeed the value of Student allows to accept the null hypothesis of no significance of this parameter (t=1.32<1.96) with P-value in the range of 0.354>0.05. These results can be interpreted by the fact that the IIC has no significant effect on GDP.
The β_{2 }parameter takes the value of- 0703 is to say that the credit of the private sector decreased by an Islamic bank unit generates an average GDP increase of 0.703 million dollars. Indeed, the value of the Student to reject the null hypothesis of non-significance of this parameter (t=-16.09<1.96) with a P-value in the order of 0.000<0.05. Thus, the private sector credit by Islamic bank with a significant impact on GDP.
The β_{3 }parameter takes the value of-0540 is to say that the private sector credit decrease of conventional banking a unit generates an increase in GDP by an average of 0.540 million.
However, the value of the Student to reject the null hypothesis of non-significance of β_{2 }parameter (t=-2.83<1.96) with a value of P-value to order (0.005<0.05). These results can be interpreted by the fact that the credit of the private sector by conventional bank to a significant impact on GDP.
The β_{4 }parameter takes the value of 0.686 that is to say, the increase in the INF consumer price of a unit generates an increase in GDP in the 15 countries averaged 0.686 million. Indeed the value of the Student to reject the null hypothesis of non-significance of this parameter (t=11.33>1.96) with P-value in the range of 0.000<0.05. These results can be interpreted by the fact that the INF consumer prices to a significant impact on GDP.
The parameter is 0.080 β_{5 }value is to say that the increase of one unit TO generates a decrease in GDP in the 15 countries averaged 0.080 million. Indeed, the value of Student used to accept the null hypothesis of non-significance of this parameter (t=1.32<1.96) with P-value in the range of 0.190>0.05.These results can be interpreted by the fact that the TO is not a significant effect on GDP.
The parameter is-0028 β_{6 }value that is to say, the GC decrease of one unit generates an increase in GDP in the 15 countries averaged 0.028 million. Indeed the value of Student allows to accept the null hypothesis of no significance of this parameter (t=-0.66<1.96) with P-value in the range of 0.512>0.05. These results can be interpreted by the GC is not a significant effect on GDP.
Indeed, after choosing the fixed effect model, a necessary condition to implement this type of estimate that it is essential that errors are homoskedastic and not auto-correlated. Then for validity of the within estimate or we must first make the tests of heteroscedasticity issue to correlation of errors.
3.6. Heteroscedasticity and Autocorrelation Tests
3.6.1. Heteroscedasticity Test
We conducted the test Brusch Pagen-panel data for the test of heteroscedasticity is done in four steps:
Recover residuals of regression testing is desired;
Generate residues square;
Regressing the residuals squared on the independent variables from the original regression;
Test whether the coefficients are jointly significant (test LM test).
The test results are shown in Table 5:
Model | F-statistic | P-value |
178.04 | 0.000 |
At the end of this result, since the P-value is less than 5% we conclude that the error is heteroscedastic.
3.6.2. Autocorrelation Test
For the auto-correlation we use the test Woodridge (2002) on which stata H_{0} hypothesis is the absence of auto-correlation of the first order.
The test results are shown in Table 6:
Model | F-statistic | P-value |
5.615 | 0.032 |
The result of this test shows that the P-value is less than 5%. It is therefore concluded that the error is auto-correlated. According to the study of these two tests we conclude that errors are heteroscedastic and auto-correlated. Then the within estimator is not the most suitable estimator for estimation.
3.7. Unit Root Test
3.7.1. First Generation Tests
The presence of unit root problem is important that the above problems. Prior to the study of the relationship of Islamic finance and economic growth, we conduct a number of unit root tests. We perform tests like (Levin, Linand Chu (2002); Im, Pesaran and Shin (1997) and Hadri (2000)) are first generation tests specified by the independence between individuals, usually these tests are different each other according to the unit root character (homogeneous or not).The results of these tests are presented in the following Table3.7.
Indeed, the results in Table 7 show that the test Levin, Lin and Chu (2002) would lead us to accept the hypothesis of stationarity for all variables for the model without trend (10%) and for the model with trend (5%). Inaddition, models with trend would lead us to accept the hypothesis of stationarity (5%) Statistics Im, Pesaran and Shin. Similarly for Statistics Hadri (2000) for all variables, the assumption is H_{0}
Variables | Model specification | LLC | IPS | Hadri |
Log PIB | Model without trend | -10,254 | -5,547 | 12,863 |
(0.000) | (0.000) | (0.000) | ||
Model with trend | -13,869 | -5,701 | 6,938 | |
(0.000) | (0.000) | (0.000) | ||
Log INF+1 | Model without trend | -4,14 | -5,559 | 4,493 |
(0.000) | (0.000) | (0.000) | ||
Model with trend | -3,011 | -6,194 | 3,153 | |
-0,001 | (0.000) | (0.000) | ||
Log GC | Model without trend | -13,97 | -2,202 | 1,455 |
(0.000) | (0.013) | (0.072) | ||
Model with trend | -10,764 | -3,005 | 3,41 | |
(0.000) | (0.001) | (0.000) | ||
Log CPSIB | Model without trend | -6,849 | -1,253 | 10,361 |
(0.000) | (0.105) | (0.000) | ||
Model with trend | -1,409 | -0,79 | 2,311 | |
(0.079) | (-0,214) | (0.010) | ||
Log CPSCB | Model without trend | -2,149 | 0,883 | 15,098 |
(0.015) | (0.811) | (0.000) | ||
Model with trend | -4,107 | 0,27 | 4,596 | |
(0.000) | (0.606) | (0.000) | ||
Log IIC | Model without trend | 0,359 | -5,456 | -0,629 |
(0.640) | (0.000) | (0.735) | ||
Model with trend | -0,036 | -6,668 | -0,494 | |
(0.485) | (0.000) | (0.684) | ||
Log To | Model without trend | -0,183 | -3,808 | -1,827 |
(0.427) | (0.000) | (0.966) | ||
Model with trend | -5,606 | -5,513 | 0,716 | |
(0.000) | (0.000) | (0.236) |
3.7.2. Unit Root Test of Second Generation
Results Pesaran test are presented in Table 8. The unit root hypothesis is rejected (5%) for INF and TO variables in the model without trend and trend. Indeed, we accept the unit root hypothesis for the other variables.
Variables | Model without trend | Model with trend |
LogPIB | -1,232 | -0,5 |
(0.109) | (0.309) | |
LogINF+1 | -6,142 | -2,781 |
(0.000) | (0.003) | |
LogGC | 0,675 | -1,175 |
(0.750) | (0.120) | |
LogCPSIB | 3,913 | 5,318 |
(1.000) | (1.000) | |
LogCPSCB | 1,058 | 2,749 |
(0.855) | (0.997) | |
LogIIC | 13,804 | 11,272 |
(1.000) | (1.000) | |
LogTo | -7,207 | -6,271 |
(0.000) | (0.000) |
3.8. Results Interpretation and Conclusion
The objective of this article and to confront theoric and empirical evidence of the impact of Islamic finance on economic growth in the MENA countries and Malaysia. This field of investigation has not yet been tested. The approach of the static panel data analysis allows studying a model closer to theoretically lessons on the impact of Islamic finance on economic growth. In this study, we tried to examine the relationship between Islamic finance and economic growth in MENA countries and Malaysia. In a sample of 15 countries over the period 2000-2011, the estimation results obtained using the static panel show that the private sector credit by the Islamic bank, variable measuring Islamic finance to an effect more important that the private sector credit by conventional banking in MENA countries and Malaysia. Indeed, the importance can be explained by the interest rate that is equal to zero in Islamic banks.
The application of unit root tests through the use of tests of the first generation LLC, IPS and Hadri shows that all statistical series are stationary. With test of second generation Pesaran shows that’ statistical series are stationary except INF and TO variables.
References