AL-ARBAH: Journal of Islamic Finance and Banking Vol.
8 No.
, 235-262.
DOI: 10.
21580/al-arbah.
E-ISSN: 2716-2575.
P-ISSN: 2716-3946
The Impact of Islamic Finance Development on Economic Performance: A Driscoll-Kraay Panel Analysis of 30 Countries Eko Gondo Saputro1 1 Universitas Terbuka.
Indonesia ekogondosaputro@gmail.
Abstract Purpose - This study investigates the relationship between Islamic finance development and economic performance in 30 countries during the period 2014 to 2023.
Method - This study employs a panel regression approach, utilizing DriscollKraay standard errors to address cross-sectional dependence, heteroskedasticity, and autocorrelation.
Economic performance is proxied by real GDP at constant prices, while Islamic finance development is measured using the Islamic Finance Country Index (IFCI).
Additionally.
FDI net inflows, unemployment rate, and the HDI serve as control variables.
Result - The findings reveal a significant positive link between Islamic Finance development (IFCI) and economic performance in both models.
HDI has a strong positive effect in both models, while the unemployment rate affects only model 2 negatively.
FDI is not significant in either model.
Implication - This study suggests stronger institutional and regulatory support for Islamic finance development.
Clear policy, strong governance, and readiness help to maximize Islamic finance development's positive impact on economic performance.
Originality - This study extends the literature by employing the Islamic Finance Country Index (IFCI) as a comprehensive indicator of Islamic finance development across countries.
Furthermore, it provides novel crosscountry evidence on the relationship between Islamic finance development and economic performance in 30 countries.
Keywords:
Economic Performance.
Islamic Finance Development.
Islamic Finance Country Index (IFCI).
Panel Regression Model.
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Received 4 March 2026 Revised 11 March 2026 17 April 2026 Accepted 22 April 2026 Eko Gondo Saputro Introduction Islamic finance is one of the fastest-growing sectors in the global financial From a market size of US$200 billion in 2003, the sector grew to approximately US$1.
8 trillion by 2014, and this growth is also considered to have opened valuable opportunities to fill the development financing gap
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(Islamic Development Bank, 2.
According to Sheng & Singh .
, the rapid growth in Islamic finance is not due to increased income among the Muslim population, but instead to the increasingly robust Islamic financial infrastructure.
For instance, the existence of the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) as the major Islamic financial institution responsible for issuing standards focused on financial accounting standards, as well as the Islamic Financial Services Board (IFSB), as an institution that provides guidance and technical notes to Islamic financial regulators, along with other regulatory standards, to improve the stability and health of the system (Hassan et al.
Furthermore, the emergence of leading research centers such as the International Center for Research in Islamic Economics and the Islamic Research and Training Institute (IRTI) in Jeddah has played an essential role in bringing Islamic economics, banking, and finance from a niche segment to the mainstream (Islahi, 2.
Thus, the presence of sufficient Islamic financial infrastructure and collaboration between organizations can promote a more competitive, resilient, and stable Islamic financial industry.
Driven by rapid development in the Islamic finance sector, global Islamic financial assets grew by 12% annually, with total assets estimated to increase from US$5.
5 trillion in 2024 to US$7.
5 trillion in 2028 (Standard Chartered.
Along with the growing global potential of Islamic finance, research activity in this field remains concentrated in a limited number of countries.
Although the sector continues to expand, a substantial gap persists between market growth and academic research output.
Recent data from ICD & LSEG .
reveal a pronounced imbalance in research contributions, with leading countries producing nearly 4,000 publications, while other significant AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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The Impact of Islamic Finance Development A contributors publish only 130 to 350.
This concentration underscores limited international participation in academic discourse.
Additionally.
Nathie et al.
corroborate this stagnation, noting that publication growth in Islamic finance consistently lags behind that of the conventional finance sector.
Despite the significant global potential of Islamic finance, a pronounced disparity persists between market expansion and the volume of scholarly Recent data from ICD & LSEG .
indicate a substantial imbalance in research output, with the leading country producing nearly 4,000 publications, while other major contributors generate only 130 to 350.
This concentration of research output indicates limited international participation in academic discourse.
Furthermore.
Nathie et al.
corroborate this stagnation, observing that the publication growth rate in conventional finance consistently exceeds that of Islamic finance.
Regardless, several studies examining Islamic finance practices in specific countries and across countries have begun to emerge.
For instance, in selected countries, studies by Ledhem & Mekidiche .
and Kazak & Okka .
examine the relationship between Islamic finance and economic growth in Turkey and Malaysia.
In addition.
Din et al.
examined the impact of Islamic finance and its depth using evidence from 12 OIC member countries, whereas Khan et al.
examined Islamic finance across 19 developed and developing countries.
However, only a limited number of studies have used comprehensive measures to assess the overall development of Islamic finance across countries, such as the Islamic Finance Country Index (IFCI).
According to the GIFR .
, through this index, countries that adopt Islamic finance will be classified as insignificant (IFCI O .
, marginal .
< IFCI O .
, moderate .
< IFCI O .
, significant .
< IFCI O .
, or exceptional (IFCI > .
, reflecting different levels of Islamic finance development.
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Eko Gondo Saputro Figure 1.
IFCI Classification Across 30 Countries .
AL-ARBAH | 238 Source: Cambridge Global Islamic Finance Report Figure 1 presents an overview of IFCI classifications in 30 countries, ranging from insignificant to exceptional, during the period 2021-2023.
The distribution of these categories also shows diversity in Islamic financial development across countries.
Although several countries remain concentrated in the insignificant and marginal classifications, most are in the moderate and significant categories.
In general, countries show an upward trend in their IFCI scores over time, moving in a positive direction.
For instance, some countries that were initially classified as insignificant have changed to marginal, while countries previously classified as significant have also changed to exceptional.
Likewise, countries that are already in the exceptional classification are continuing to maintain their performance and Islamic financial ecosystem, allowing them to remain consistently in that category.
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The Impact of Islamic Finance Development A These results indicate that the financial industry in each country continues to grow and strengthen.
Existing literature on the relationship between Islamic finance and economic performance often relies on single indicators, such as Islamic AL-ARBAH | 239 banking financing and sukuk, which do not adequately capture the complexity of the Islamic financial ecosystem.
This study addresses this gap by utilizing the Islamic Finance Country Index (IFCI), which provides a comprehensive assessment of Islamic finance sector development through eight variables: the number of Islamic banks, the number of Islamic financial institutions (IBF.
, the Sharia supervisory regime, total Islamic financial assets, the Muslim population, sukuk instruments, education and culture, and Islamic regulations and law.
The primary objective of this study is to examine the relationship between the development of Islamic finance and economic performance across Panel data from 30 countries, covering the period from 2014 to 2023, are analyzed.
These countries represent a broad spectrum of IFCI classifications, ranging from insignificant Islamic finance development (IFCI < .
to exceptional development (IFCI > .
This study contributes to the literature by capturing cross-country variations at different stages of Islamic finance development, thereby providing a more comprehensive empirical analysis than previous research.
Incorporating the multidimensional aspects of the IFCI, the study offers new insights for policymakers aiming to understand the role of the Islamic financial ecosystem in promoting sustainable economic performance.
Literature Review Determinants of Economic Performance The relationship between foreign direct investment (FDI) and economic performance remains a subject of extensive empirical debate across diverse economic contexts.
Nayak & Sahoo .
demonstrate that FDI inflows significantly enhance economic performance in India, as measured by GDP per AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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Eko Gondo Saputro In a cross-country analysis.
Sijabat .
identifies both short-term and long-term positive effects of FDI on economic performance, measured by constant GDP, across ten ASEAN countries.
However, the relationship between FDI and economic performance is not inherently automatic.
Chizema .
argues that a countryAos ability to convert capital inflows into substantial AL-ARBAH | 240 economic output depends on its absorptive capacity, particularly the quality of its institutions and human resources.
In the absence of these fundamental conditions, the benefits of FDI are limited and may even become detrimental.
Nevertheless, based on the theoretical perspective that FDI contributes to capital accumulation and increased output, this study maintains a positive expectation regarding this primary relationship.
H1: Foreign Direct Investment (FDI) has a positive and significant effect on economic The unemployment rate of a country signals not only poor economic performance but also suboptimal resource utilization and an economy operating below its full capacity (Siddiqa, 2.
As a result, the unemployment rate is frequently regarded as a barometer of economic performance, reflecting labor-market conditions that guide policymakers in addressing underlying social and structural challenges (Vintu & Denis, 2.
Ngubane et al.
offer a critical perspective on this relationship, highlighting its asymmetric nature and demonstrating that unemployment is more responsive to negative than to positive shocks in economic performance.
In line with the theoretical perspective that elevated unemployment rates negatively impact economic performance by reducing economic output.
Mohamud et al.
found that a one-unit increase in the unemployment rate is associated with a significant decline in Somalia's GDP.
Therefore, high unemployment rates constitute a structural impediment that directly constrains economic performance.
H2: The unemployment rate has a negative and significant effect on economic performance.
A high Human Development Index (HDI) score reflects advancements in human capital, which are critical for increasing productivity and attracting investment within an economy.
Healthier, better-educated populations with AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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The Impact of Islamic Finance Development A higher living standards are more likely to contribute to value creation across diverse economic sectors (Ramadhan & Satria, 2.
Puttitanun & Lerskullawat .
argue that, in low-income countries, improvements in human development may not be sufficient to generate measurable growth
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In contrast, in middle-income countries, higher levels of health, education, and living standards allow human development to support economic performance more effectively.
Therefore, this study hypothesizes that the HDI has a positive and significant impact on a countryAos economic H3: The Human Development Index (HDI) has a positive and significant effect on economic performance.
Islamic Finance Development and Economic Performance Islamic finance provides a framework in which financial returns are directly connected to real economic activities through risk-sharing and asset collateralization principles.
This approach incentivizes investors and depositors to allocate resources toward productive sectors, including entrepreneurship, infrastructure, and trade, rather than seeking passive income from guaranteed returns (IsDB Institute, 2.
Additionally.
Kurniawan et al.
observe that the appeal of Islamic finance encompasses both the commercial sector, such as Islamic banking and capital markets, and the social sector, including zakat, infaq, sadaqah, and waqf.
Consequently.
Islamic finance seeks to generate impact at multiple scales, positioning developments in this sector as a crucial and promising component of the global economy.
However, the potential for Islamic finance development differs across Naz & Gulzar .
demonstrate that a positive correlation between Islamic finance and real GDP emerges only in the long term, while the short-term relationship is negative.
Law & Ridhwan .
further explain that negative shocks to Islamic financial stability exert a greater influence on long-term economic performance than positive shocks.
They emphasize that AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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Eko Gondo Saputro macroprudential policies and effective oversight of Islamic financial stability can enhance a countryAos economic performance.
The Islamic Finance Country Index (IFCI) is the oldest index for ranking countries in Islamic banking and finance.
The countries included in the index AL-ARBAH | 242 represent a diverse sample, encompassing various taxonomic categories and levels of Sharia compliance (Foglie et al.
, 2.
The IFCI is specifically designed to monitor industry growth and provide a direct assessment of the state of Islamic banking and finance in each country (Prasetyo et al.
, 2.
Prandi & Colecchia .
assert that the IFCI is a reliable metric for tracking Islamic Banking and Finance (IBF) growth, as it is derived from a factor analysis tailored to quantitatively measure sector development.
They further state that the index monitors IBF sector growth globally, offers broad geographical coverage, and maintains measurement accuracy through periodic methodological updates.
As a result, the IFCI effectively captures the tangible presence of Islamic finance in specific jurisdictions, rather than offering only approximate estimates.
Numerous researchers have examined the impact of Islamic finance on economic performance at both national and cross-national levels.
Rofik et al.
report that, despite its relatively small market share.
Islamic finance positively influences real GDP growth in Indonesia, as evidenced by its impact on consumer, investment, and working capital financing.
Similarly.
Alferez et .
find that Islamic finance exerts a positive and significant effect on economic performance, as measured by real GDP.
These findings suggest that Islamic finance can enhance economic performance through a robust financial system grounded in Sharia principles, risk-sharing mechanisms, and the prohibition of usury, thereby supporting economic development.
Accordingly, this study hypothesizes that the Islamic Finance Country Index (IFCI) significantly improves countries' economic performance.
H4: The Islamic Finance Country Index (IFCI) has a positive and significant effect on economic AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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The Impact of Islamic Finance Development A Conceptual Framework Figure 2 presents the conceptual framework of this study, which illustrates the direct relationship between Islamic finance development and economic performance, while accounting for macroeconomic control variables.
Islamic AL-ARBAH | 243 finance development is measured by the Islamic Finance Country Index (IFCI), which serves as the primary independent variable reflecting its proposed role in supporting economic performance.
Meanwhile, economic performance variables are measured using real GDP, which is used as the dependent variable.
In addition.
Foreign Direct Investment (FDI), unemployment rates, and the Human Development Index (HDI) are used as control variables to isolate the specific contribution of Islamic finance development to economic performance.
Figure 2.
Conceptual Framework AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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Eko Gondo Saputro Methods Data and Variables This study utilizes a panel data structure and uses secondary data sources, covering 30 countries over the period 2014 to 2023.
Purposive sampling was AL-ARBAH | 244 employed to ensure a balanced dataset.
The Islamic Finance Country Index (IFCI), a dynamic index with an expanding geographic scope, increased from 42 countries in 2014 to 53 countries in 2023.
The sample was drawn from countries that consistently appeared in the IFCI rankings, representing a spectrum from insignificant (IFCI O .
to exceptional (IFCI > .
levels and possessing complete macroeconomic data for the entire observation period .
4Ae2.
Consequently, 30 countries were selected: Iran.
Saudi Arabia.
Kuwait.
Bahrain, the United Arab Emirates.
Qatar.
Oman.
Jordan.
Turkey.
Malaysia.
Brunei Darussalam.
Indonesia.
Singapore.
Thailand.
Pakistan.
Bangladesh.
Sri Lanka.
Kazakhstan.
Egypt.
Tunisia.
Algeria.
Senegal.
Nigeria.
Kenya.
Gambia, the United Kingdom.
Switzerland.
Canada, the United States, and Australia.
Furthermore, the dependent variable in this study is economic performance, measured by real GDP from the World Bank database.
Meanwhile.
Islamic finance development, measured using the Islamic Finance Country Index (IFCI) classification based on data from the Global Islamic Finance Report, is the independent variable.
Thus, this study also uses macroeconomic variables as control variables, such as Foreign Direct Investment (FDI) and unemployment rates from the World Bank database, as well as the Human Development Index (HDI) from the UNDP database.
Moreover, as shown in Table 1, definitions of the data variables and the sources for each dataset are provided.
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The Impact of Islamic Finance Development A Table 1.
Definitions of Data Variable Data Variable Code Definition Source Real GDP (Constant 2015 US$) RGDP Gross domestic product is the total income earned through the production of goods and services in an economic territory during an accounting period.
It can be measured in three ways: the expenditure approach, the income approach, or the production This indicator is expressed in constant prices, meaning the series has been adjusted to account for price changes over time.
The reference year for this adjustment is 2015.
This indicator is expressed in United States dollars.
World
Bank
Islamic
Finance Country Index
IFCI
The Islamic Finance Country Index (IFCI) is the oldest index for ranking countries on the state of Islamic banking and finance (IsBF) and its relative importance at the national and international Cambridge Global Islamic Finance Report AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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Eko Gondo Saputro FDI Nett Inflows (BoP.
Current US$) FDI Foreign direct investment refers to direct investment equity flows in the reporting economy.
It is the reinvestment of earnings, and other capital.
Direct investment is a category of cross-border investment in which a resident of one economy exercises control or a significant degree of influence over the management of an enterprise resident in another Ownership of 10 percent or more of the ordinary shares of voting stock is the criterion for determining whether a direct investment relationship Data are in current U.
World
Bank
Unemployme nt Rate (%) UNEMP
Unemployment refers to the share
of the labor force that is without work but available for and seeking Definitions of labor
force and unemployment differ by World
Bank
Human
Development Index
HDI
The Human Development Index (HDI) is a summary measure of average achievement across key development: a long and healthy life, knowledge, and a decent standard of living.
UNDP
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The Impact of Islamic Finance Development A Model and Estimation Based on the conceptual framework presented in Figure 2, the robustness of the results will be tested using two empirical models to separate the specific impact of Islamic finance development.
The first model estimates the basic AL-ARBAH | 247 relationship between economic performance and control variables .
ithout IFCI).
Meanwhile, the second model extends the basic specification by adding Islamic finance development .
ith IFCI) to examine the additional impact on economic performance.
Furthermore, equations .
explain the details of the empirical models used in this study.
Log_RGDPit = A0 A1IHS_FDIit A2UNEMPit A3HDI2it Auit Log_RGDPit = A0 A1IHS_FDIit A2UNEMPit A3HDI2it A4Log_IFCIit Auit .
Where Log_RGDPit refers to the natural logarithm of economic performance measured by real GDP, and Log_IFCIit refers to the natural logarithm of Islamic finance development.
IHS_FDIit indicates the inverse hyperbolic sine transformation of foreign direct investment net inflows.
UNEMPit refers to the unemployment rate, and HDI2it indicates the squared form of the Human Development Index.
Meanwhile, yu0 indicates the constant parameter, yuycu is the slope associated with each controlled and independent variable, i denotes the country, t refers to the time variable, and Auit is the error To examine the relationship between Islamic finance development and economic performance, this study uses panel data regression analysis with STATA 16.
Before determining the final model, this study also performs descriptive statistics to profile the data, conducts skewness tests as normality diagnostics, and uses Hausman tests as specification tests to select between fixed- and random-effects models in panel regression.
A series of diagnostic tests was conducted, including the Pesaran CD test for cross-sectional dependence, the Breusch-Pagan test for heteroskedasticity.
AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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Eko Gondo Saputro the Lagrange Multiplier (LM) test for autocorrelation, and the Mean Variance Inflation Factor (VIF) test for multicollinearity.
Furthermore, the Driscoll & Kray .
estimator was applied using the AoxtsccAo command in Stata, as developed by Hoechle .
, to obtain standard errors robust to heteroskedasticity, autocorrelation, and cross-sectional dependence.
This AL-ARBAH | 248 approach enhances the validity of the significance test results.
Results and Discussion Data Diagnostics The empirical analysis begins with an overview of the data through descriptive statistics.
Table 2 presents the mean, standard deviation, maximum, and minimum for the variables used in this study, covering 300 observations from 2014 to 2023.
Table 2.
Descriptive statistics Variable Obs.
Mean Std.
Dev.
Min Max RGDP (Billion US$) 1,130.
3,530.
22,100.
FDI (Billion US$) UNEMP (%) HDI (Inde.
IFCI (Inde.
Source: Data Processed by STATA .
The results exhibit that the data in this study are highly diverse, as evidenced by the distributions of the variables.
For instance, the RGDP variable exhibits a substantial standard deviation (US$3,530 billio.
, indicating significant disparities across the sample countries.
Meanwhile, although the average FDI is substantial at US$23.
7 billion, it is worth noting that the FDI variable has a negative minimum value (-US$242 billio.
, indicating that some AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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The Impact of Islamic Finance Development A countries in the sample exhibit net investment outflows that exceed inflows during the observed period.
In contrast, the average unemployment rate of 5.
81%, with a considerable variation ranging from 0.
10% to 19.
84%, reflecting varying conditions in the AL-ARBAH | 249 labor market.
Moreover, the Human Development Index (HDI) exhibits a significantly smaller standard deviation .
, suggesting that human development levels are more evenly distributed among countries.
Lastly, the average IFCI value is 21.
77, which, according to GIFR .
, is classified as a moderate level because it falls within the range .
< IFCI O .
However, a significant gap exists between the minimum .
and maximum .
values, reflecting a substantial disparity in Islamic financial growth among the sampled countries.
Based on this descriptive overview, it is crucial to ensure the data is well distributed before proceeding with the analysis.
Hence, the skewness test was conducted to determine whether the variables in this study required transformation to achieve a more normal distribution.
Table 3 presents the results of the skewness test for each variable in its level, logarithmic, and square forms, where values closer to zero indicate a symmetrical data Table 3.
Skewness Test
Variable Level Form
Log Form
Square Form
RGDP
FDI
UNEMP
HDI
IFCI
Source: Data Processed by STATA .
Based on the findings, the logarithmic forms of RGDP and IFCI show values close to zero.
The results indicate that both variables need to be transformed into natural logarithms.
FDI also shows a similar pattern, with the logarithmic AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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Eko Gondo Saputro form yielding values close to zero.
however, due to negative observations, this variable will use the Inverse Hyperbolic Sine (IHS) transformation to maintain the logarithmic distribution.
UNEMP in level form is considered the best .
losest to zer.
compared to other forms, so UNEMP will not be transformed.
Lastly.
HDI shows that the square form is closest to zero, suggesting that HDI
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should be transformed into the square form.
With the variables now properly transformed to ensure data symmetries, the next step is to verify the chosen model to confirm that it has no statistical To ensure the regression model is accurate and to obtain the Best Linear Unbiased Estimator (BLUE), the study will use a Hausman test to select the most appropriate panel data regression model.
Afterwards, classical assumptions will be tested, including cross-dependence, heteroscedasticity, autocorrelation, and multicollinearity in the chosen model.
The results of these tests are presented in Table 4.
Table 4.
Summary of Diagnostic Test Results of Model 1 & Model 2
Diagnostic Test
Hausman Test
PesaranAos Test for Cross-Section Dependence Breusch-Pagan Test for Heteroskedasticity Lagrange Multiplier (LM) Test
Mean Variance Inflation Factor (VIF) for Multicollinearity Model 1
Model 2
0000***
Source: Data Processed by STATA .
Note: ***p < 0.
01, **p < 0.
05, *p<0.
The Hausman test results indicate that the p-value in Model 1 .
= 0.
and Model 2 .
= 0.
fail to reject the null hypothesis, suggesting that the Random Effects Model (REM) is the appropriate estimation approach in this AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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The Impact of Islamic Finance Development A The Random Effects Model (REM) will also serve as the final model and will be applied to models 1 and 2.
Furthermore, cross-dependence diagnostic tests using PesaranAos test showed different results for the two models.
Model 1 showed a significant test AL-ARBAH | 251 .
= 0.
, indicating the presence of cross-sectional dependence.
Meanwhile, model 2 showed no cross-sectional dependence .
= 0.
In addition, the Breusch-Pagan test indicates that only model 1 .
indicates heteroscedasticity, while model 2 .
does not.
Moreover, the Lagrange Multiplier (LM) test shows that both model 1 .
and model 2 .
indicate the presence of autocorrelation.
Given these findings, it is recommended to use the Driscoll & Kray .
estimator, as implemented with the AuxtsccAy command in STATA, in the final Random Effect Model (REM) to address heteroscedasticity, autocorrelation, and cross-sectional dependence, thereby ensuring more reliable and robust estimates.
Lastly, multicollinearity was not detected in either model, as the VIF values were low .
This result indicates that the independent variables in both models did not exhibit strong correlation, ensuring the reliability of the regression Model Interpretation Table 5 presents robustness checks for the panel data regression results in both models, providing additional validation for the final model used in this To avoid issues of cross-sectional dependence, heteroskedasticity, and autocorrelation in models 1 and 2, this study will employ the Driscoll & Kray .
estimator with the "xtscc" command in STATA as the final model Based on the findings, in model 1, only HDI has a positive and significant effect on economic performance, and this result is also consistent with model 2.
Meanwhile, model 2, which includes IFCI, shows very different Unemployment shows a negative and significant effect on economic Additionally.
Islamic finance development also has a positive and AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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Eko Gondo Saputro significant impact on economic performance.
However.
FDI is not statistically significant in both models.
Table 5.
Random Effect Model using the Driscoll-Kraay Standard Errors Model 1 (Without IFCI) AL-ARBAH | 252 Variables Coefficient .
-valu.
FDI .
n IHS .
UNEMP
HDI .
n square For.
IFCI .
n log For.
Model 2 .
ith IFCI) Hypothesis (Remark.
(Not Supporte.
(Not Supporte.
Coefficient .
-valu.
005*** .
(Supporte.
428*** .
(Supporte.
669*** .
(Supporte.
043*** .
(Supporte.
Hypothesis (Remark.
(Not Supporte.
A0 .
onstant 042*** .
428***
Prob>Chi2 Overall R2 Wald Chi Source: Data Processed by STATA .
Note: ***p < 0.
01, **p < 0.
05, *p<0.
Table 5 shows that the HDI variable in Models 1 and 2 has positive, significant effects.
Since HDI is squared, use the average HDI value .
from Table 1 to calculate the marginal impact.
In Model 1.
HDI's marginal impact is 38 .
428 x 0.
, and also in Model 2, it is 4.
669 x 0.
Thus, 01-point increase in HDI would boost economic performance by 5.
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The Impact of Islamic Finance Development A (Model .
18% (Model .
, if other factors remain constant .
eteris These results also align with Taqi et al.
and Soleman et al.
, who found a positive and significant effect of HDI on economic growth in Pakistan and Indonesia, respectively.
Furthermore, the UNEMP in Model 2 shows a negative and significant effect, indicating that a 1% increase in the unemployment rate leads to a 0.
005 x .
decrease in economic performance, assuming all other factors remain constant.
These findings are in line with Hjazeen et al.
, who found a negative relationship between unemployment rates and economic growth in Jordan, and with Oshiokpekhai & Egbejule .
, who also found an adverse long-term effect of unemployment rates on economic growth in Nigeria.
Lastly, the IFCI in Model 2 shows a positive and significant effect, indicating that a 1% increase in the index score will be associated with a 0.
043% increase in economic performance .
eteris paribu.
These findings are in line with Khan et al.
Din et al.
, and Khattak & Khan .
, who also found similar results in cross-country samples.
Additionally, these findings align with Ledhem & Mekidiche .
Kazak & Okka .
, and Sakinah et .
, who also found that Islamic finance influences economic growth, with a country-specific focus on Turkey.
Malaysia, and Indonesia.
In addition, the overall R-squared value indicates that Model 2 provides a better fit to the data and can provide a more comprehensive explanation of the relationship between Islamic finance development and economic The R-squared value in Model 2 .
is higher than that in Model 1 .
, indicating that the addition of the IFCI not only enhances the model's explanatory power but also further strengthens the relevance of Islamic finance development within the model, thereby improving the robustness of the findings.
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Eko Gondo Saputro Discussion This study contributes to the literature by examining the broader Islamic financial ecosystem rather than focusing solely on individual financial Using the Islamic Finance Country Index (IFCI), which includes AL-ARBAH | 254 factors such as the number of Islamic banks.
Sharia supervisory regimes, total Islamic financial assets.
Muslim population, sukuk instruments, education, culture, and Islamic regulations, the study provides a comprehensive and upto-date assessment of Islamic finance's impact on economic performance in 30 The development of Islamic finance has a positive impact on economic performance, indicating that the Islamic financial system, as measured by the Islamic Finance Country Index (IFCI), can facilitate economic progress through a comprehensive ecosystem.
The IFCI evaluates Islamic finance by assessing the growth of Islamic banking institutions and financial assets, such as sukuk, which enhance the availability of capital for productive sectors.
Furthermore, the index includes the Sharia supervisory system and legal framework to ensure a stable and transparent investment environment.
The IFCI also accounts for demographic, educational, and cultural factors that create conditions favorable to Islamic business and financial institutions (IBFI.
, thereby significantly influencing the real economy.
Empirical studies support this perspective.
Gani & Bahari .
demonstrated that Islamic banks in Malaysia positively influenced capital formation, investment, and capital productivity, as measured by total factor Similarly.
Kazak et al.
found that Islamic banking in Turkey, through commercial lending and fund distribution, had a positive and significant effect on the real economy, particularly manufacturing production Evidence from diverse contexts corroborates these findings, indicating that the development of Islamic finance is a key driver of real economic activity and can enhance a countryAos economic performance.
Another critical finding regarding macroeconomic control variables is the role of the human development index (HDI.
and unemployment rate in AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
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The Impact of Islamic Finance Development A impacting economic performance.
The HDI2 shows a positive and significant impact on economic performance in both model 1 .
ithout IFCI) and model 2 .
ith IFCI).
These results indicate that human development remains a key determinant of economic performance, regardless of whether a country AL-ARBAH | 255 adopts Islamic finance.
This finding aligns with Wardani & Arif .
, who show that Islamic bank financing has a positive and significant indirect effect on human development through economic growth.
In addition, the unemployment rate findings show a negative and significant result only in model 2 .
ith IFCI).
This result aligns with the findings of Yuli & Rofik .
, who identified a trade-off between economic growth and job creation in the context of Islamic finance.
Their research demonstrates that economic growth facilitated by Islamic finance does not fully support optimal job creation.
Furthermore, they found that the effectiveness of Islamic financing in reducing unemployment declines as its market share increases.
These results indicate that, although the development of Islamic finance improves economic performance, its impact is not sufficiently inclusive to optimally absorb participants in the labor market.
While this study quantitatively examines the relationship between Islamic finance and economic performance, its empirical findings also inform policy discussions, particularly given the cross-country scope.
The effectiveness of Islamic finance varies by region and depends on the preparedness of each country's regulatory framework.
For instance.
Munfariha .
observes that, despite the United Kingdom's established financial regulatory system, challenges persist in integrating Islamic financial principles into accounting standards and regulations that do not sufficiently address the unique characteristics of Sharia-compliant financial instruments and transactions.
Similarly.
Hassan et al.
identify obstacles to Islamic banking in the United States, including complex taxation and the lack of Sharia governance.
Consequently, establishing a robust governance framework for Islamic financial institutions is critical for countries seeking to maximize the potential of Islamic finance to enhance economic performance.
AL-ARBAH: Journal of Islamic Finance and Banking Ae Vol.
8 No.
Eko Gondo Saputro Conclusion This study examines the impact of Islamic finance development on economic performance across 30 selected countries using panel data.
The results indicate that Islamic finance development, as measured by the Islamic Finance Country Index (IFCI), has a positive and significant effect on economic AL-ARBAH | 256 performance, particularly on real GDP.
These findings imply that the Islamic financial system, which includes institutional expansion, financial assets, regulatory frameworks, and demographic, educational, and cultural factors, can improve economic performance in adopting countries.
These findings have several policy implications.
To maximize the impact of Islamic finance, countries should prioritize strengthening institutional and regulatory frameworks.
While these factors were not directly examined as independent variables in this study, the results indicate that policy readiness, supportive Sharia governance, and robust financial infrastructure are essential for realizing the full benefits of Islamic finance for the real economy and improving national economic performance.
This study has several limitations, primarily due to the exclusion of certain institutional and social quality variables resulting from limited data availability within the sample.
Future research should incorporate variables such as regulatory quality, social norms, and infrastructure readiness as moderating factors to address these limitations.
Additionally, employing a mixed-methods approach or conducting specific case studies may provide deeper insights into the mechanisms through which the maturity of Islamic finance influences economic performance.
References