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ISLAMIC AND CONVENTIONAL FINANCIAL INCLUSION-GREEN GDP NEXUS: CASE OF OIC COUNTRIES

Presenter:

Yakubu Benedicta Hawa

Authors:

Asst. Prof. Dr. Zakaria Lacheheb

Asst. Prof. Dr. Husna Bt Jamaluddin

Asst. Prof. Dr. Sharifah Nabilah binti Syed Salleh

Asst. Prof. Dr. Dolhadi Bin Zainudin

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INTRODUCTION

LITERATURE REVIEW

METHODOLOGY

RESULTS AND DISCUSSION

SUMMARY

POLICY IMPLICATIONS

OUTLINE

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INTRODUCTION�

Financial inclusion is a critical and integral part of economic growth and has become a burning issue in recent years.

According to the World Bank (2018), "financial inclusion" is described as "persons and enterprises having access to a sort of financial goods and services that satisfy their financial requirements in an accountable, easy, inexpensive, and long-term way.“

Payment, credit, transaction, saving, insurance, and remittance flow are examples of such products and services.

According to Sarma & Pais (2011) and Park & Mercado (2015) calculated financial inclusion index by combining three-dimension factors: ATMs, bank branches, borrowers, depositors and domestics credit to GDP ratio.

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INTRODUCTION�

Economic growth is crucial to economic development (Perera & Lee, 2013), but it also affects the environmental quality (Arouri et al., 2012; Kasman & Duman, 2015).

Growth target increases carbon dioxide (CO2) emissions, affecting environmental sustainability (Arouri et al., 2012; Muhammad, 2019).

The figure illustrates that most air-polluted countries are developing countries and OIC member states

Figure ‎1. World’s Most Polluted Countries (PM2.5 air pollution)

Source: World Bank (2022).

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INTRODUCTION

GREEN GDP

The green gross domestic product (green GDP) is an indicator of economic growth with the environmental consequences of that growth factored into a country's conventional GDP.

Green GDP monetizes the loss of biodiversity and accounts for costs caused by climate change.

The Green Gross Domestic Product, or Green GDP for short, is an indicator of economic growth with environmental factors taken into consideration along with the standard GDP of a country.

Natural capital is poorly represented in GDP. Resources are not adequately considered as economic assets (Admin, 2022; Wikimedia Foundation, 2023).

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RESEARCH PROBLEM

There are several issues related to OIC countries and green GDP topic. First, OIC countries are the most polluted countries as stated by the world air report. The report shows that the top 10 polluted countries are mostly OIC countries.

The existing literature predominantly focuses on CO2 emissions and scarce attention paid to green GDP as a combination of economic and environmental outcome.

Finance-growth link is still inconclusive and further research that combines finance, institutional quality on the two in one factor of growth-environment (green GDP) would significantly contribute to the nexus.

Financial inclusion is argued to mitigate environmental degradation (Renzhi & Baek, 2020; Umar, Mirza, et al., 2021), whereas Islamic financial inclusion and its environment effects is rarely investigated.

This paper focuses on a critical issue related to OIC countries and their environmental impact. countries, like Afghanistan, Bangladesh, Bahrain, and Kuwait, are often among the most polluted in the world, according to the World Air Report.

The issue is that financial inclusion, which involves providing access to financial services to a broader population, can potentially lead to increased emissions and decreased environmental quality.

While previous research has explored how financial inclusion affects specific aspects of 'green GDP,' such as carbon emissions, there's a noticeable gap in understanding the broader connection between financial inclusion and green GDP, which is a vital indicator of the economy's environmental impact.

In essence, it’s still uncertain about the connection between financial inclusion and growth in these countries and how it impacts the environment. This thesis will bridge this gap by examining the relationship between financial inclusion, economic growth, and environmental sustainability in OIC countries. By combining the factors of finance and institutional quality, we seek to shed light on how these countries can achieve economic growth while also taking steps to protect the environment."

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RESEARCH OBJECTIVES

The primary objective of this study is to investigate the impact of Islamic and conventional financial inclusion such as bank branches and the number of ATMs on green GDP in OIC countries

This paper focuses on a critical issue related to OIC countries and their environmental impact. countries, like Afghanistan, Bangladesh, Bahrain, and Kuwait, are often among the most polluted in the world, according to the World Air Report.

The issue is that financial inclusion, which involves providing access to financial services to a broader population, can potentially lead to increased emissions and decreased environmental quality.

While previous research has explored how financial inclusion affects specific aspects of 'green GDP,' such as carbon emissions, there's a noticeable gap in understanding the broader connection between financial inclusion and green GDP, which is a vital indicator of the economy's environmental impact.

In essence, it’s still uncertain about the connection between financial inclusion and growth in these countries and how it impacts the environment. This thesis will bridge this gap by examining the relationship between financial inclusion, economic growth, and environmental sustainability in OIC countries. By combining the factors of finance and institutional quality, we seek to shed light on how these countries can achieve economic growth while also taking steps to protect the environment."

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LITERATURE REVIEW�

In the case of OECD countries, Hussain et al. (2021) studied the impact of financial inclusion and infrastructure on the ecological footprint.
Their results reveal that financial inclusion deteriorates environmental quality by increasing its ecological footprint, while infrastructure is found to disrupt the environmental quality of OECD countries.
Wang et al. (2018) found that national control of corruption can reduce CO2 emissions and that controlling corruption moderates the relationship between trade and carbon emissions in BRICS countries.

Kim et al.(2016) examined the link between inclusive finance and economic expansion in 55 OIC countries from 1990 to 2013. Their study found a positive connection between inclusive finance and economic growth in the context of OIC nations, emphasizing the potential for financial inclusion to contribute to economic development in these countries.
Lau, Choong, and Eng (2014) found that institutional quality inhibits CO2 emissions during economic development in Malaysia.

"In the context of OECD countries, Hussain et al. (2021) conducted a study to understand the impact of financial inclusion and infrastructure on the ecological footprint. Their results indicate that financial inclusion tends to have a negative effect on environmental quality by increasing the ecological footprint. At the same time, infrastructure development disrupts environmental quality in OECD countries.

In a separate study, Wang et al. (2018) found that a nation's control of corruption can lead to reduced CO2 emissions. Additionally, they observed that controlling corruption plays a moderating role in the relationship between trade and carbon emissions, particularly in BRICS countries.

Moving to a different context, Kim et al. (2016) conducted a study examining the relationship between inclusive finance and economic expansion in 55 countries that are members of the Organization of Islamic Cooperation (OIC) from 1990 to 2013. Their findings highlight a positive connection between inclusive finance and economic growth in OIC nations, emphasizing the potential for financial inclusion to drive economic development in these countries."

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LITERATURE REVIEW�

There is limited literature related to Islamic and green GDP, and inclusive finance in developed and emerging economies is still in the infant stage (Park & Mercado, 2015; Sulong & Bakar, 2018).

However, there are still contradictory results based on the previous literature. Some researchers have found a positive association between inclusive finance and economic expansion (Babajide et al., 2015; Sharma, 2016; Thomas et al., 2017; Lenka & Barik, 2018; Kim et al., 2018; Sethi & Acharya, 2018; and Ahmad et al., 2021).

"In the context of OECD countries, Hussain et al. (2021) conducted a study to understand the impact of financial inclusion and infrastructure on the ecological footprint. Their results indicate that financial inclusion tends to have a negative effect on environmental quality by increasing the ecological footprint. At the same time, infrastructure development disrupts environmental quality in OECD countries.

In a separate study, Wang et al. (2018) found that a nation's control of corruption can lead to reduced CO2 emissions. Additionally, they observed that controlling corruption plays a moderating role in the relationship between trade and carbon emissions, particularly in BRICS countries.

Moving to a different context, Kim et al. (2016) conducted a study examining the relationship between inclusive finance and economic expansion in 55 countries that are members of the Organization of Islamic Cooperation (OIC) from 1990 to 2013. Their findings highlight a positive connection between inclusive finance and economic growth in OIC nations, emphasizing the potential for financial inclusion to drive economic development in these countries."

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METHODOLOGY

The choice of these countries stems from data availability among developed and emerging economies. Panel Data was sourced from the World Bank, and world governance indicators (WGI) Data.

The general method of moments (GMM) is addressed, as proposed by Holtz-Eakin et al. (1988) and refined by Arellano and Bond (1991), Arellano and Bover (1995), and Blundell and Bond (1998). From 2013 to 2021, the Difference GMM (D-GMM) estimator was used for a panel of 19 OIC economies for the estimation.

Diagnostic tests:

Second-order serial correlation test
Sargan/Hansan test

Methodology

The choice of selected countries is based on data availability, which includes both developed and emerging economies. The panel data was gathered from reputable sources such as the Mendeley data, World Bank, and World Governance Indicators (WGI), spanning the period from 2013 to 2021.

For the analysis, I employed the System GMM estimator, as introduced by Blundell and Bond in 1998. This estimator is preferred for its ability to provide consistent parameter estimates and is considered more robust than other common techniques.

To ensure the reliability of the results, I conducted several diagnostic tests, including a second-order serial correlation test to check for any patterns in the data. Additionally, I used the Sargan/Hansan test to address issues related to overidentification, which may arise due to the use of multiple instruments in the analysis.

Lastly, the U test was employed to assess whether there is a U-shaped (or inverse U-shaped) relationship within the data, helping to unveil any non-linear patterns within the variables

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MODEL SPECIFICATION

This study applied three models as follows:

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METHODOLOGY�

Institutional quality is proxied by control of corruption, which is scaled with a maximum score of 0 for total corruption and a maximum score of 100 for no corruption, according to the World Governance Indicator (WGI).

Trade openness is net export as a percentage of GDP from the World Bank database.

Similarly, human capital from the World Bank is proxied by school enrollment, primarily (% gross).

Financial inclusion is proxied by ATMs and banks. The number of ATMs per 100,000 adults and bank branches are the number of bank branches per 100,000 adults. The data is collected from Islamic and conventional banks in OIC countries.

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RESULTS & DISCUSSION�

Table 1.Descriptive Statistics Table 2. Matrix of Correlations

VARIABLE	OBS	MEAN	STD.DEV.	MIN	MAX
GGDP	180	2.82e+11	2.76e+11	4.47e+09	1.24e+12
IBB	180	1492.55	4474.972	-44	21409
BB	171	12.422	7.545	1.69	38.59
IATM	126	5250.754	13775.19	16	65132
ATM	171	43.743	28.868	.71	122.04
IQ	180	43.803	24.465	.474	87.204
TO	171	74.71	43.026	4.128	191.873
HC	180	100.714	10.892	72.015	119.556

VARIABLES	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
(1) GGDP	1.000
(2) IBB	0.126	1.000
(3) BB	0.190	0.730	1.000
(4) IATM	0.186	0.968	0.727	1.000
(5) ATM	0.367	0.327	0.646	0.421	1.000
(6) IQ	-0.069	-0.340	0.077	-0.296	0.494	1.000
(7) TO	-0.228	-0.217	0.125	-0.181	0.433	0.854	1.000
(8) HC	0.264	0.241	0.263	0.260	0.316	0.211	0.190	1.000

The mean Green GDP is approximately 1.31e+11(131 billion.), with values ranging from 8.97e+08(897 million) to 1.09e+12 (1.09 trillion). These disparities highlight the diversity in economic and environmental performance within the OIC.

In comparison to variables like investment, institutional quality, and FDI, trade openness demonstrates substantial differences among OIC countries, as indicated by its 43.80% standard deviation. This suggests a wide range of trade openness levels across these nations.

The investment variable, with a standard deviation of 10.086, exhibits a maximum value of 60.058 and a minimum of -3.946. this indicates a varying degrees of investment across the OIC countries.

The correlation matrix in Table 4.2 reveals the relationships between our key variables. Our analysis of the correlation coefficients indicates that collinearity was not a significant concern. The majority of the correlation coefficients are below 0.67, suggesting that collinearity did not pose a challenge in this study. As a result, our panel data series was deemed suitable for accurate and robust estimations, and no spurious regression was identified.

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RESULTS &DISCUSSION

Table 3. Regression Results

	Islamic FI		Conventional FI
Variables	Model (IBB)	Model (IATM)	Model (BB)	Model (ATM)
	lggdp	lggdp	lggdp	lggdp
l.LGGDP	0.344*** (0.118)	0.428*** (0.136)	0.083 (0.170)	0.220 (0.208)
LFI/LIFI	0.045*** (0.016)	0.010 (0.116)	0.185*** (0.038)	0.076 (0.160)
LIQ	-0.319*** (0.055)	-0.499*** (0.062)	-0.409*** (0.086)	-0.311*** (0.054)
LTO	0.120* (0.062)	0.195*** (0.047)	0.118* (0.070)	0.121* (0.063)
LHC	-0.468** (0.207)	-0.421* (0.223)	-0.518*** (0.195)	-0.500** (0.230)
CONS	19.618*** (3.030)	17.761*** (3.065)	26.867*** (4.362)	23.028*** (4.776)

AR(2) (p-value)	0. 768	0.713	0. 440	0. 205
J-test (p-value)	0.224	0.118	0.306	0.640
No. of Instruments	12	12	12	12
No. of Countries	19	14	18	18
No. of Observations	132	98	126	126
Time dummies	No	No	No	No

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According to the findings, there is a statistically significant positive relationship between bank branches of Islamic banks on green GDP.

However, conventional financial inclusion shows no dynamic effect using SGMM.

This study adopts only DGMM to compare the results between the conventional and the Islamic, while if using a fixed effect or random effect model could give better results but the methods will be different, and hence difficult to compare the results.

ATMs of Islamic banks were insignificant at first, then turned to positive and significant after including population and investment into the model.

Additionally, our findings reveal a positive correlation between trade openness and green GDP.

CONCLUSION

Objective One:

Objective: To assess the impact of institutions on green GDP in OIC countries.

Outcome: The research demonstrates that institutions have a positive impact on green GDP, indicating that a high quality of government and favorable policies contribute to environmental preservation while also fostering economic growth. Conversely, it is found that financial inclusion has a negative impact on green GDP due to the construction and proliferation of ATMs and bank branches, especially in rural areas, which can lead to environmental degradation.

Objective Two:

Objective: To investigate the interaction effect between institutional quality and financial inclusion on green GDP in OIC countries.

Outcome: The research suggests that the interaction between institutional quality and the presence of ATM machines and bank branches may mitigate the negative impact of financial inclusion on green GDP. In other words, strong institutions can play a role in balancing the potential environmental consequences of financial inclusion.

Objective Three:

Objective: To identify threshold levels for bank branches per 100,000 population in OIC countries and their impact on green GDP in relation to financial inclusion.

Outcome: The study's results reveal a critical threshold of 6.55 bank branches per 100,000 population in OIC countries. Below this threshold, financial inclusion has a positive impact on green GDP. However, beyond this threshold, the impact of financial inclusion turns negative. This finding highlights the importance of carefully managing the expansion of banking services to achieve a balance between economic development and environmental sustainability.

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POLICY IMPLICATIONS

This result has significant policy considerations that the government could implement to accelerate the growth of its green GDP.

To minimize environmental contamination, policy makers at the OIC countries should emphasize preserving and improving the quality of their institutions to boost and develop green GDP in their respective nations.

In addition, policymakers should establish effective government regulations to improve institution quality measurements.

The governments should also promote green investment, which consists of investment projects and processes that enable the adoption of renewable energy sources, ecologically friendly technology, etc., reducing environmental pollution.

Policy Recommendations:

Enhancing Institutional Quality:

Policy makers in OIC countries should prioritize the development of institutions that foster stability, democracy, and good regulatory quality. These factors contribute to environmental preservation and economic growth. Strengthening institutional quality will help maintain environmental quality and ensure that financial services operate at an optimal level.

Rethinking ATM and Bank Branch Expansion:

It is essential for OIC countries to reconsider the indiscriminate expansion of ATMs and bank branches, especially in light of the increasing availability of financial technology and online financial services. Instead of focusing solely on physical infrastructure, policymakers should encourage the adoption of fintech solutions, which can provide financial services more efficiently and sustainably.

Shifting Focus to Fintech:

Given the current state of financial inclusion, OIC countries should shift their focus from conventional financial inclusion efforts to fintech. Fintech solutions can bridge the gap in financial services access more effectively, particularly in remote and underserved areas. Policymakers should create an environment conducive to fintech development and adoption.

Monitoring Green GDP as a Vital Indicator:

Policymakers should recognize the importance of monitoring and promoting green GDP as a critical indicator of both environmental health and economic performance. This integrated approach provides valuable insights into the interplay between the environment and the economy. Incorporating green GDP considerations into policy decisions can help OIC countries achieve a balanced and sustainable approach to development.

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THANK YOU