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Article

The Dynamic Relationship between Carbon Emissions, Financial Development, and Renewable Energy: A Study of the N-5 Asian Countries

by
Xu Xu
1,
Wensheng Dai
2,
Tufail Muhammad
1 and
Tao Zhang
2,*
1
School of Economics, Beijing Technology and Business University, Beijing 100048, China
2
Financial School, China Financial Policy Research Center, International Monetary Institute, Renmin University of China, Beijing 100872, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(18), 13888; https://doi.org/10.3390/su151813888
Submission received: 2 August 2023 / Revised: 29 August 2023 / Accepted: 14 September 2023 / Published: 19 September 2023
Browse Figure
Review Reports Versions Notes

Abstract

:
As a critical component of primary production and consumption activities worldwide, renewable energy is a necessary source of economic development and social prosperity. The main emphasis of the current research is to investigate how five Asian countries are leveraging financial resources and renewable energy to address carbon emissions and achieve Sustainable Development Goals. It explores the relationship between the environmental impacts of financial development and renewable energy under external moderation. To address this aim, a secondary quantitative research method was used, considering the period from 2010 to 2020. For data analysis, a cross-sectional dependence test, second-generation unit root test, co-integration, and CS-ARDL model were used. The research findings revealed that renewable energy induces a short-term influence on CO2 emissions. In contrast, renewable energy and financial development, when moderated by institutional quality and globalisation, have posed long-term influences on CO2 emissions. Our empirical research offers fresh insights to policymakers and governments, aiding in the development policies that safeguard environmental quality while simultaneously achieving sustainable economic objectives. This study suggests the significance of enacting adequate policies for endorsing the usage of renewable energy and the minimisation of CO2 emissions for sustainable development.

1. Introduction

It is noticeable that worldwide temperatures are increasing, and climate change is accelerating. Climate change and the matter of global warming have secured substantial emphasis from researchers, scholars, and policymakers across the world, including developing Asian economies, due to their catastrophic consequences. The yielding economic growth observed within several developing countries has resulted in lifting investment prospects and thereby higher demand for energy; the degradation of the environment has been subsequently exacerbated by these factors [1,2]. However, Asian countries are contemporarily making active investments in green projects to transition their energy sources towards sustainable and renewable alternatives, intending to meet the increased demand for energy and address environmental issues at the same time [3]. This shift towards green energy not only addresses environmental concerns but also forms the foundation for achieving sustainable development goals. The green energy transition intends to substitute higher carbon fossil fuels with lower carbon clean energy [4]. However, the transition towards green energy remains a major challenge for Asian developing nations. This encompasses energy poverty, limited government support, large upfront costs, regulatory restrictions, and other barriers [5]. This has resulted in making investments within green projects to minimise dependence upon fossil fuels to be an intricate and discouraging task for developing countries. Irrespective of the challenges, developing Asian nations, including India, identify the significance of adopting advanced technologies and making green investments to attain Sustainable Development Goals (SDGs), as underscored within the sustainability progress report regarding SDGs [6,7].
The concept of globalisation refers to the process of interactions between businesses, governments, and other entrepreneurs globally for economic gain. Generally, economic growth within developing countries is made at the expense of environmental degradation, resulting in increasing importance for making augmented investments in green projects and exploring alternative energy solutions [8]. Evidently, the Belt and Road Initiative (BRI), carried out by the Chinese economy, poses a substantial bearing on this discussion. The BRI has emphasised sustainable development, infrastructure connectivity, and climate vulnerability. It has also highlighted the requirement of building a green BRI by improving infrastructure connectivity, facilitating green investments, transitioning towards renewable energy, and enhancing governance to attain the SDGs of 2030 [9,10].
Figure 1 shows Percentage of Greenhouse Gas (GHG) Emission. Table 1 provides data on global annual greenhouse gas emissions, measured in CO2 equivalents, from various continents for the years 2010 to 2020. Table 1 shows the historical trend of greenhouse gas emissions for each continent over the years. It shows how emissions have changed from year to year for each continent, as well as how emissions from different continents compare to each other. These data are crucial for understanding the contributions of various regions to global greenhouse gas emissions and assessing their impact on climate change. In summary, the emissions trends observed in Table 1 can be linked to the economic growth and development patterns of each continent. Rapidly developing economies such as those in Asia might show consistent emission increases due to industrialisation, while more established economies in Europe might exhibit declining emissions due to a focus on sustainability. Fluctuations in emissions on certain continents could be due to a combination of economic, policy, and environmental factors [11].
Considering this, the economic growth of developing Asian countries significantly depends upon financial development since strong financial systems deliver lower cost loans to households and industries and thus promote energy demand, resulting in increased environmental issues [12]. The shift to renewable energy is crucial for addressing environmental problems, and this transition comes with various policy considerations, such as insufficient government backing, the requirement for more initial investments in new projects, challenges in financial systems, resource distribution, and evolving technological capacities [13].
Developing Asian countries are among the fastest growing regions when considering the share of carbon emissions and energy consumption; thereby, the countries deliver a stimulating context to analyse these dynamics [14]. These developing nations pose distinct levels of globalisation, institutional quality, and financial development; thus, they provide an exclusive opportunity to discover how these factors interrelate and contribute to the association amongst carbon emissions and renewable energy adoption. Therefore, research focuses on contributing to the prevailing literature by analysing the intricate associations amongst carbon emissions, financial developments, and renewable energy, along with a precise emphasis on developing Asian nations. Asian countries confront environmental challenges because of higher fossil fuel consumption and the phase of conventional industrialisation. The consumption of fossil fuels contributes nearly 75% to Asia’s energy [15]. In addition, the region accounts for more than 50% of the total fossil fuel consumption at the interventional level. The adoption of renewable energy plays an imperative part in mitigating GHG emissions and endorsing sustainable development [16].
Financial development serves as a catalyst for technological advancements, as well as renewable energy investments [17]. The favourable regulatory frameworks, highly developed financial markets and access to finance play a pivotal role in attracting substantial investments and fostering the implementation of green energy solutions. Nevertheless, the level of financial development, along with its influence on renewable energy, could differ across distinct contexts and nations. Asian countries could opt for innovative financial strategies developed by the IPEEC or OECD to improve renewable or green projects [18]. These findings underscore the importance of financial innovation in constructing a sustainable environment through increasing investments in renewable energy. In addition, globalisation has turned out to be a defining characteristic of the contemporary era, which shapes environmental, social, and economic exchanges amongst nations. More precisely, globalisation enables the exchange of investments, technology, and investments that could pose positive or negative influences upon the adoption of renewable energy and alleviation of carbon emissions [19]. The extent of globalisation, including technological spillovers, trade openness, and Foreign Direct Investment (FDI), could impact the effectiveness of renewable energy technologies for minimising carbon emissions.
Furthermore, institutional quality, including policy effectiveness, regulations, and governance, significantly influences the link between carbon emissions, renewable energy, and financial development by fostering green investments and efficient renewable energy policies [20]. Policy intervention plays an imperative role in curtailing the volatility of environmental change instigated by globalisation and shocks of financial investments. The major intent of this research is to suggest policy interventions for developing Asian nations. The research query is stated as follows:
Research Question:
Does the adoption of renewable energy solutions and financial investment provoke improvements in the environmental quality of developing Asian nations?
The empirical research is prearranged as follows: Section 2 contains critically reviewed past-related literature and theoretical background. Section 3 covers the utilised econometric techniques and data sources, while Section 4 presents the empirical findings and corresponding discussions. Finally, Section 5 comprises conclusions, research limitations, and policy recommendations.

2. Literature Review

The relevant literature is discussed in the section below in order to compare and discuss the existing literature.

2.1. Association amongst Carbon Emissions and Financial Development

Several research studies have analysed the association between financial development and CO2 emissions [21,22]. The empirical literature has yielded diverse and multifaceted research outcomes regarding the association amongst the CO2 emissions and financial development. This is mainly because of the diversified data sets, time periods, employed econometric methodologies within distinct research studies. A few researchers contended that financial development, demonstrated by the efficiency and profundity of financial markets, endorses industrialisation and economic growth. This subsequently brings about increased energy consumption and, accordingly, increased carbon emissions [23,24,25]. In accordance with these research studies, strong financial systems tend to promote investment within energy-intensive industries, bringing about an increase in carbon-intensive production and showed that a linear, significant, and positive association exists amongst the financial development and carbon (CO2) emissions. This relationship suggests that the consistent increase in financial development results in increasing the CO2 emissions, without reaching a tipping point [26]. It revealed that both the financial development and consumption of energy have contributed to increasing CO2 emissions and thereby instigated environmental degradation. A significant and positive association between financial development and CO2 emissions was identified in both developed and developing economies, underscoring the requirement of context-specific analysis [27].
The Environmental Kuznets Curve (EKC) has suggested a U-shaped and inverted association between income and environmental degradation [28]. The hypothesis recommended that with the increase in income and financial development, countries primarily endure increased carbon (CO2) emissions. Nevertheless, when a country attains a specified level of income, both economic growth and financial development enable the implementation of renewable energy and cleaner technologies, resulting in minimised CO2 emissions [29,30]. Analysed the EKC hypothesis within the case of Pakistan, in which financial development exhibited a significant and positive influence on the CO2 emissions up to a specified income level. Subsequently, the impact of financial development became negatively related with CO2 emissions [31,32].
Furthermore, another school of thought suggests that financial development and globalisation have resulted in enhanced overall environmental quality. This is due to the fact that globalisation contributes to increasing financial investments and facilitating financial operations via trade [33]. Analysed how globalisation and trade have opened up prospects for developing nations to import novel and advanced technologies from developed ones. This has enhanced the inclusive energy efficiency of developing nations and minimised CO2 emissions. Accordingly, it is inferred from the above literature that there is a direct association between financial development, globalisation, and CO2 emissions. Nevertheless, there exists only one research study that has analysed the moderating effect of globalisation upon renewable energy consumption, financial development, and CO2 emissions, particularly within the content of G20 nations [34]. In addition, none of the research has focused on the moderating impact of institutional quality and globalisation upon CO2 emissions, consumption of renewable energy, and financial development within the developing nations of Asia. Owing to this, the present research intends to overcome this prevailing research gap.

2.2. Energy Consumption and CO2 Emissions

Energy is important for increasing overall economic growth and development since it is employed for producing products and services [34]. Developing nations have been endeavouring to deal with the concerns of environmental sustainability, which necessitates particular treatment [35]. It is found that there exists a long-run causality within the variables, including urbanisation, renewable energy utilisation, financial development, and CO2 emissions. In these countries, the high energy demand is attributed to several factors, such as economic competitiveness, manufacturing advancements, advancements, enhanced lifestyles, and population increase. In order to fulfill the need for energy, developing nations rely on the redundant burning of fossil fuels that release CO2 emissions into the air considerably and instigate a negative influence on the environment. Developing countries are characterised as the fastest growing regions, thereby they have higher demand for energy, which raises concerns about environmental quality [14]. Ref. [18] showed that an increase in energy consumption and GDP has significantly resulted in lifting CO2 emissions in G-20 nations. They conducted a study examining the interplay between urbanisation, carbon dioxide emissions, economic growth, and renewable energy generation within the member states of the Organization of Black Sea Economic Cooperation. This study underscored the key role that renewable energy plays in tackling climate change issues within developing economies [36]. In addition, found that the industrial sector tends to make investments in the purchase of equipment and machinery, which increases the usage of energy along with carbon (CO2) emissions. In contrast, found that renewable energy plays an imperative role in minimising CO2 emissions and consumption of non-renewable energy, which is certainly the major source that promotes CO2 emission. They precisely examined the EKC hypothesis in Pakistan, where financial development showed a significant and positive impact on the CO2 emissions up to a specified income level [32].

2.3. CO2 Emissions and Moderating Impact of Globalisation

According to [37]; globalisation and renewable energy influence emissions positively and negatively, respectively. Notably, economic complexity mitigates globalisation’s carbon emissions-boosting effect. However, the N-shaped EKC hypothesis does not hold for high emissions quantiles. The research suggests that environmental policies should consider the nuanced interactions between economic factors, globalisation, and renewable energy. Within the past literature, several economic and noneconomic determinants, such as Financial Development (FD), Human Capital (HC), Gross Domestic Product (GDP), Urbanisation (URB), Globalisation (GB), and Energy Consumption (EC), have been associated with carbon emissions [34]. Amongst these factors, globalisation has remained a crucial factor that relates to climate change since integration and global trade influence (both positively and negatively) the environment. The pioneering research stated that globalisation has been an important factor that provokes the financial sector. This is because globalisation minimises the borrowing cost that results in increased investments within distinct projects, thereby lifting economic growth. Globalisation has a direct association with economic growth and financial development. Nevertheless, for achieving a higher GDP, energy is an important factor required for the production process and instigates carbon emissions. It has been specifically found that globalisation has led to increasing energy demand in 25 developed nations, which has triggered CO2 emissions. Several research studies have shown that globalisation and financial development result in enhancing overall environmental quality. They examined the nexus of economic factors, carbon emissions, energy consumption, financial development, and globalisation within Pakistan by employing the ARDL approach. They found that globalisation, consumption of energy, and financial development hold a positive correlation with carbon emissions in both the long-run and short-run [22,27,38,39].

2.4. CO2 Emission and Moderating Impact of Institutional Quality

Numerous research studies have underscored the importance of institutional quality to ensure economic sustainability over the long-run [18,40]. The empirical findings of past-related research studies have presented mixed results regarding the influence of institutional quality upon the overall quality of the environment. A few research studies have revealed that better institutional quality, which is considered by effective policy implementation, strong regulatory frameworks, and good governance, has a significant and positive impact on improving environmental quality. They found that trade openness, energy use, and institutional quality stimulate economic growth. Particularly, there remains a significant and positive interaction between institutional quality and CO2 emission. The association suggests that impartial, as well as efficient, domestic institutions are highly imperative for lowering CO2 emissions and simultaneously enhancing economic growth [41]. Similarly, Ref. [42] found that green innovation considerably resulted in lowering the CO2 emissions. In addition, the quality of institutions has posed a negative moderating impact upon the association amongst the CO2 emissions and green innovation, in such a way that with higher institutional quality, renewable or green solutions hold a robust and substantial reduction within the CO2 emissions. However, contrary to this, Ref. [40] revealed that governance and institutions are liable for environmental degradation and sustainable development.
Institutional quality has posed a substantial and negative influence on CO2 emissions. Thus, institutional quality lowers environmental degradation when a nation poses a lower income level. Human capital plays an important role that might impact environmental quality. Human capital has been a crucial input parameter employed within production procedures for adding value [43,44]. Work experience, expertise, training, insights and knowledge, and education are encompassed within the human capital framework. Human capital, characterised by competent and highly trained employees, poses the possibility of accelerating economic growth (GDP) along with promoting advancements in environmental sustainability. Research studies have shown that human capital and financial development results in minimising CO2 emissions; nevertheless, the rise in energy consumption and GDP has led to a substantial increase in CO2 emissions [45,46]. Additionally, globalisation has instigated a positive influence upon human, as well as financial, development, thereby minimising CO2 emissions. In contrast, it revealed that ICT results in minimising the CO2 emissions by providing advanced and innovative technological solutions. However, the formation of human capital has resulted in lifting CO2 emissions since it has an indirect influence on economic growth. The research has also found that human capital has the potential to improve growth and environmental quality, as it poses absorptive capacity and can improve the efficiency of ICT tools, which can minimise CO2 emissions [47].
From the literature review, it has been determined that there remains a divergence within the influences of the selected parameters (Renewable Energy Consumption (REC), Institutional Quality (IQ), Globalisation (GB), and Financial Development (FD)) upon carbon emissions. Thus, due to the continuing discrepancy in the academic literature, the debate is still growing about the directionalities of the impact, and research has failed to possibly construct a consistent and coherent policy framework. Thus, it is important to congregate the influences of the policy instruments upon the targeted economic variable to develop a policy framework. Additionally, the convergence of the policy framework must be analogous to long-term policy objectives. Thus, in the academic literature, there remains a policy void regarding the rationalisation of policy orientation within the empirical context. Specifically, the empirical findings of this research are used to construct a Sustainable Development Goals SDG-oriented policy framework. The framework poses the potential to be employed as a standard policy framework to address the SDG objectives.

3. Methodology

3.1. Data

In the current research, the main intent of the researcher is to analyse the dynamic nexus among renewable energy, carbon emissions, financial development, and the moderating roles of institutional quality and globalisation in the context of Asian countries. However, for the purpose of this, a secondary quantitative research method has been used, and information has been derived on five Asian countries (including China, India, Japan, Malaysia, and Thailand). Regarding the source of data, information has been derived from the World Bank Indicator and Economy Website KOF while considering the period from 2010 to 2020. The primary reason for using secondary quantitative information is that it is easily accessible and requires less time for data collection [48].

3.2. Variables Description

Table 2 represents the variables, measurement for variables, and sources of variables.

3.3. Model and Specification

The study’s empirical framework is grounded in the variables of financial development (FD), renewable energy (RE), globalisation (GB), and institutional quality (IQ), which serve as explanatory variables, with carbon emissions (CO2) as the dependent variable. Previous research indicates that financial institutions play a pivotal role in funding economic activities and providing low-cost financing to households and businesses, thereby stimulating energy demand, while also contributing to environmental degradation. In this context, the study anticipates a positive correlation between FD and CO2 emissions. Conversely, the adoption of renewable or green energy sources enhances environmental quality by mitigating CO2 emissions. Building upon the existing literature [18,20,34], it is hypothesised that RE will exhibit a negative relationship with CO2 emissions. Globalisation, by facilitating trade and invigorating economic endeavours, amplifies the demand for goods and services, consequently driving energy consumption and CO2 emissions. This pattern aligns with findings from earlier investigations [27,38,39]. Three models have been estimated in the current research, which can be explained as follows:
CO2it = β0 + β1FDit + β2Git + β3IQit + β4REit + εit
Here:
CO2 = Carbon Emission, FD = Financial Development, G = Globalisation, IQ = institution Quality, RE = Renewable Energy, t = time period, i = country, ε = error term.
CO2it = β0 + β1FDit + β2Git + β3IQit + β4REit + β5FD*Git + β6RE*Git + εit
CO2it = β0 + β1FDit + β2Git + β3IQit + β4REit + β5FD*Git + β6RE*Git + β7FD*IQit + β8RE*IQit + εit

3.4. Empirical Estimation

For empirical estimations, the first cross-sectional dependence test has been utilised to analyse the dependence of variables involved in the current research. In addition to this, a second generation test has also been used to assess the stationary of the variables through using Cross-Sectional Augmented Dickey–Fuller (CADF) at both level and first difference. Hence, after evaluating the stationary and cross-section dependence, Panel Dynamic Least Squares (DOLS) has been used to evaluate the long-term relationship between variables involved in the current research. Lastly, the cross-sectional ARDL model has also been used to evaluate the long-run and short-run effects of variables on carbon emissions.

4. Empirical Results and Discussion

The first cross-sectional dependence test has been used to assess the dependence of variables involved in the current research. Likely, as per [49] null hypothesis in the cross-sectional dependence test, there is no cross-sectional dependence, while the alternative hypothesis indicates that cross-sectional dependence exists. From Table 3, it can be seen that the p value in Breusch–Pagan LM and Pesaran-scaled LM is below the threshold of 0.05, while the p value in Pesaran CD is greater than 0.05. Hence, based on the above criteria, the null hypothesis is rejected, and it is concluded that there is a presence of cross-section, which might be due to neighbourhood effects. Therefore, it is essential to deploy a second-generation panel unit test to test the stationary.
In order to determine the stationary of the variables, second-generation unit root tests have also been used using the Cross-Sectional Augmented Dickey–Fuller (CADF) test at both level and first difference. Likely, as per [49], a p value in ADF testing less than 0.05 indicates that we reject the null hypothesis, and the series is stationary. However, from Table 4, it can be seen that all variables are non-stationary at this level, as the p value is greater than the threshold. However, all variables are stationary at the first difference, except for financial development and renewable energy.
In Table 5, after confirming the stationary and cross-section dependence, the cointegration test has been used to evaluate the long-term relationship. Similarly, Ref. [50] in their study, added that the null hypothesis in co-integration indicated that no cointegration exists, while that alternative hypothesis indicated that cointegration exists. However, Panel Dynamic Least Squares (DOLS) has been used for cointegration testing. It can be seen that the coefficient value for financial development is −0.05 and the sig value is 0.51 > 0.05, which implies that there is no long-term relationship (no cointegration) between financial development and carbon emissions. Similarly, there is also no cointegration between globalisation and carbon emission, as the p value is 0.616 > 0.05. In contrast, there is a positive and long-term relationship between institutional quality and carbon emissions, as the coefficient value is 2.27 and the p value is 0.02 < 0.05. Lastly, there is a negative and long-term relationship between renewable energy and carbon emissions, as the coefficient value is −0.098 and the p value is 0.0986. Thus, it can be said that there is a long-term relationship of renewable energy and institutional quality with carbon emissions.
In the above Table 6, the Cross-sectional Autoregressive Distributed Lag (ARDL) model has been employed to assess both the short-term and long-term effects on carbon emissions. In relation to Model 1, the analysis encompasses variables such as financial development, globalisation, institutional quality, and renewable energy, aiming to scrutinise their impacts over different time horizons. Noteworthy is the discovery that financial development wields a positively charged, enduring influence on carbon emissions, with a coefficient value of 0.153 and a corresponding p-value of 0.0095, which is less than the threshold of significance at 0.011. Similarly, globalisation also yields a constructive and lasting effect on carbon emissions, as evidenced by the coefficient value of 0.095, accompanied by a p-value of 0.000, which is significantly lower than 0.01, it can be seen from Table 6. Conversely, renewable energy exhibits a long-term yet adverse impact on carbon emissions, with a coefficient of −0.207 and a significant p-value of 0.000, again below 0.01. On a divergent note, institutional quality appears devoid of any substantial long-term influence on carbon emissions, given that its p value exceeds the predefined threshold.
Furthermore, upon analysing the short-term effects, it becomes apparent that only renewable energy exerts a detrimental influence on carbon emissions. In this context, financial development, globalisation, and institutional quality lack any discernible short-term impact on carbon emissions.
In Model 2, we have examined the moderating effects of globalisation to analyse both its short-term and long-term impacts on carbon emissions. However, due to issues with multicollinearity, we have excluded the individual impacts of factors such as financial development, institutional quality, and renewable energy. Regarding the interaction between financial development and globalisation, our findings indicate a positive and lasting influence on carbon emissions. This is evident from the coefficient value of 0.001, with a corresponding p value of 0.001, which is less than the significance threshold of 0.01. Similarly, the interaction between renewable energy and globalisation also demonstrates a positive and enduring effect on carbon emissions. The coefficient value for this interaction is 0.001, and the associated p-value is 0.000, again lower than the significance threshold of 0.01. Conversely, when considering short-term effects, we observe that only the interaction between renewable energy and globalisation exhibits a significant and negative impact on carbon emissions. The coefficient value is 0.004, and the corresponding p value is 0.0387, which is below the significance threshold of 0.05. These findings align with prior research, as indicated by various studies [22,39,40,44], which highlight the crucial role of globalisation in the context of climate change.
In Model 3, we explore the moderating effects of institution quality and globalisation on carbon emissions, assessing both their short-term and long-term impacts. However, in addressing multicollinearity concerns, individual influences, such as financial development, globalisation, institution quality, and renewable energy, have been omitted from Model 3. Regarding the interaction between financial development and globalisation, a noteworthy positive and enduring correlation with carbon emissions emerges. This is evidenced by a coefficient value of 0.015, with a significance level (sig) of 0.000, well below the threshold of 0.01. Similarly, the interplay of renewable energy and globalisation also exhibits a constructive and lasting effect on carbon emissions. Here, the coefficient value stands at 0.008, and the associated significance value is again 0.000 < 0.01. Further analysis reveals that the interaction between financial development and institution quality likewise contributes to a favourable and sustained impact on carbon emissions. With a coefficient value of 0.593 and a significance value of 0.000 < 0.01, this association reinforces the idea of their combined influence. Similarly, when renewable energy moderates with institutional quality, a positive and enduring effect on carbon emissions is discerned. The coefficient value, determined to be 0.193, aligns with a significance value of 0.000 < 0.01.
On the other hand, the short-term perspective shows that no variables exert a direct influence on carbon emissions. This finding underscores the complexity of the interrelationships at play. Importantly, our results resonate with prior research, as various studies, including [22,38], have emphasised the pivotal role of globalisation and institution quality in the context of climate change.

Implications of Results

The analysis includes variables such as financial development, globalisation, institutional quality, and renewable energy. The results reveal significant insights into how these factors interact with and impact carbon emissions.
The interaction between financial development and globalisation demonstrates a sustained positive influence on carbon emissions. This suggests that when these two factors combine, they might amplify their effects on emissions, possibly due to increased investment and trade-related activities. The positive interaction between renewable energy and globalisation reveals that these two factors, when combined, could lead to higher carbon emissions. This could be due to the complex dynamics between adopting renewable energy technologies and the overall economic and trade context. The interaction between financial development and institutional quality shows a significant favourable impact on carbon emissions. This might imply that strong institutions combined with financial resources could lead to better management of emissions and sustainable development. The positive interaction between renewable energy and institutional quality in terms of carbon emissions implies that these two factors, when combined, can contribute to reducing emissions. This underscores the potential effectiveness of well-functioning institutions in supporting renewable energy transitions.
This study highlights the complex relationship between various factors influencing carbon emissions. This indicates that financial development and globalisation, despite their positive impacts on economic growth, might also contribute to increased emissions. Additionally, the counterintuitive findings regarding renewable energy suggest the need for comprehensive strategies beyond its adoption to effectively mitigate emissions. The role of institutional quality appears less pronounced in the context of emissions reduction, which could be due to its indirect effects or interactions with other factors. These findings emphasise the need for holistic and integrated policies that consider the interactions between economic development, energy sources, globalisation, and institutions to effectively address climate change.

5. Concluding Remarks

5.1. Conclusions

The present research found that the consumption of renewable energy has induced a negative influence on CO2 emissions and the environment, both in the long- and short-term. Therefore, there is a need to develop a policy framework that supports renewable energy initiatives. Government subsidies and backed funds could offer grants, and loans on lower interest rates to entice private sector investments in renewable energy. It argues that globalisation has a positive and long-term impact on carbon emissions. This research considers how globalisation moderates the effects of renewable energy and financial development on CO2 emissions. The findings suggest that globalised renewable energy and financial development contribute to CO2 emissions reduction. It emphasises the need for policies such as quota restrictions and tariffs to lower emissions. The role of financial development as a moderator is explored along with the importance of institution quality, which, when coupled with renewable energy and financial development, negatively affects CO2 emissions in the long term. Enhancing institution quality for emissions reduction. It suggests a policy framework involving import substitution, aiming to limit the imports of environmentally harmful technologies. This approach would promote local technology production, innovation, and job creation. Ultimately, it highlights the potential for such policies to align with Sustainable Development Goal 8, fostering sustainable and comprehensive development in Asian nations.

5.2. Implications for Sustainable Development

The research emphasises the policy framework for sustainable development in Asian nations. The inclusion of the private sector is crucial, achieved by offering such as grants, loans, and subsidies. Globalisation’s positive impact on carbon emissions is explored. Globalised renewable energy and financial development contribute to reduced CO2 emissions. Quota restrictions, tariffs, and institution quality are means to lower emissions. Financial development plays a moderating role that interacts with the quality of institutions, and the import substitution policy holds significance for fostering local technology production

5.3. Limitations and Future Considerations

The endeavour to foster GDP growth and environmental sustainability in developing Asian nations necessitates careful consideration of key assumptions and limitations. Policymakers must ensure that bureaucratic processes do not facilitate rent-seeking behaviours, particularly in supporting startup initiatives. Strengthening existing laws is vital to safeguarding public interests. Transitioning away from fossil fuels requires accompanying measures for labourer reskilling to mitigate short-term unemployment and maintain social stability. Adhering to these principles is essential for achieving enduring growth and development across Asia. The framework has also considered the moderating influences of institutional quality and globalisation. However, the comprehensiveness of the framework can be additionally analysed as the deliberated challenges are extensively dominant within several other emerging nations, facilitating research generalisability. Inclusively, the research’s policy framework could be used as a fundamental guide for other developing nations across the world.

Author Contributions

Conceptualisation, X.X. and T.M.; methodology, T.M.; software, T.M.; validation, X.X., T.M. and W.D.; formal analysis, T.Z. and W.D.; investigation, T.M. and X.X.; resources, X.X.; data curation, W.D.; writing—original draft preparation, T.M.; writing—review and editing, T.M.; visualisation, W.D. and T.Z; supervision, T.Z.; funding acquisition, X.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 15 13888 g001
Figure 1. Percentage of Greenhouse Gas (GHG) Emission. Source: (https://ourworldindata.org/) (Drawn from Table 1) (accessed on 19 July 2023).
Figure 1. Percentage of Greenhouse Gas (GHG) Emission. Source: (https://ourworldindata.org/) (Drawn from Table 1) (accessed on 19 July 2023).
Sustainability 15 13888 g001
Table 1. Global Annual Greenhouse Gas Emissions in CO2 equivalents from all Sources.
Table 1. Global Annual Greenhouse Gas Emissions in CO2 equivalents from all Sources.
Continents20102011201220132014201520162017201820192020
Africa4,724,591,0004,883,026,4004,862,142,5004,771,323,0004,751,794,7004,656,470,0004,698,851,3004,742,433,3004,683,634,0004,719,213,6004,640,355,300
Asia23,501,705,00025,112,080,00025,835,897,00026,092,777,00027,001,670,00027,731,263,00027,087,560,00027,633,859,00028,251,386,00029,153,006,0002,867,336,800
Australia811,251,000826,610,200777,676,000675,925,570665,306,560650,599,200646,500,160680,855,550658,960,260623,561,300602,731,650
Europe7,467,774,0007,399,134,0007,359,351,3007,226,138,0006,950,991,0006,989,548,0007,031,311,4007,091,462,0007,084,059,6006,916,850,7006,486,574,000
North America8,417,333,0008,288,974,3008,108,574,0008,245,462,5008,380,942,3008,275,196,0008,170,190,0008,112,087,6008,320,786,0008,221,015,0007,507,261,400
South America4,153,206,8004,121,616,0004,234,718,5004,239,712,8004,161,550,3004,071,219,0003,889,702,4003,783,899,4003,658,345,5003,800,535,0003,601,995,300
Source: (https://ourworldindata.org/) (accessed on 19 July 2023).
Table 2. Data and sources.
Table 2. Data and sources.
VariablesData SourceDescription of Variables
Dependent Variable
Carbon Emission WDI, World BankCO2 emission
Independent
Variables
Financial
Development		World Development IndicatorsAccessibility to banks
Renewable EnergyWorld Development IndicatorsRenewable energy consumption
GlobalisationEconomy Website of Global Economic Barometer (KOF) Consisting of sub-indices of economic, social, and political,
Institution QualityWorld Development Indicators Comprises sub-indices, control of corruption, regulatory quality, voice and accountability, rule of law, government effectiveness absence of political stability, and terrorism
Table 3. Results of the Cross-Sectional Dependence Test.
Table 3. Results of the Cross-Sectional Dependence Test.
TestStatisticd.f.Prob.
Breusch–Pagan LM18.77906100.0432
Pesaran-scaled LM1.963055 0.0495
Pesaran CD0.022448 0.9822
Null hypothesis: No cross-section dependence in residuals.
Table 4. Second-generation Unit Root test.
Table 4. Second-generation Unit Root test.
LevelFirst Difference
Variablest-Statisticsp-Valuet-Statisticsp-Value
Carbon Emission16.85920.077519.64940.0327
Financial Development7.434330.683914.78450.1401
Globalisation 7.900390.638631.50050.0005
Institution Quality 8.570440.573322.11150.0145
Renewable Energy 13.71550.186410.82510.3713
Null Hypothesis: has Unit root and series is non-stationary.
Table 5. Co-Integration test.
Table 5. Co-Integration test.
Variable Coefficient Std. Errort-Statistic Prob.
Financial Development−0.0561590.085746−0.6549480.5152
Renewable Energy −0.0983860.058217−1.6897610.0986
Institutional Quality 2.2741711.0060592.2604840.0292
Globalisation −0.0308430.061063−0.5050750.6162
Null Hypothesis: No cointegration.
Table 6. Outcomes of CS-ARDL Estimation.
Table 6. Outcomes of CS-ARDL Estimation.
Model 1Model 2Model 3
Long Run Equation
Coefficientp ValueCoefficientp ValueCoefficientp Value
Renewable Energy −0.207 ***0.000
Financial Development0.153 ***0.095
Globalisation 0.095 ***0.000
Institution Quality 0.1150.8259
Renewable Energy *Globalisation 0.001 ***0.000−0.008 ***0.000
Financial Development * Globalisation 0.001 ***0.0110.015 ***0.000
Renewable Energy * Institutional Quality −1.92 ***0.000
Financial Development * Institutional Quality −0.593 ***0.000
Short Term Equation
Coefficientp ValueCoefficientp ValueCoefficientp Value
D (Renewable Energy) −0.339 **0.0369
D (Financial Development)−0.1690.3832
D (Globalisation) 0.0030.9298
D (Institution Quality) 1.0660.1807
D (Renewable Energy * Globalisation) −0.004 **0.0387−0.0100.147
D (Financial Development * Globalisation) −0.0010.69920.0050.3515
D (Renewable Energy * Institutional Quality) −0.4350.6345
D (Financial Development * Institutional Quality) 1.0700.3938
Note: it showed that *** significant at 1%, ** significant at 5%, * significant at 10%.
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Xu, X.; Dai, W.; Muhammad, T.; Zhang, T. The Dynamic Relationship between Carbon Emissions, Financial Development, and Renewable Energy: A Study of the N-5 Asian Countries. Sustainability 2023, 15, 13888. https://doi.org/10.3390/su151813888

AMA Style

Xu X, Dai W, Muhammad T, Zhang T. The Dynamic Relationship between Carbon Emissions, Financial Development, and Renewable Energy: A Study of the N-5 Asian Countries. Sustainability. 2023; 15(18):13888. https://doi.org/10.3390/su151813888

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Xu, Xu, Wensheng Dai, Tufail Muhammad, and Tao Zhang. 2023. "The Dynamic Relationship between Carbon Emissions, Financial Development, and Renewable Energy: A Study of the N-5 Asian Countries" Sustainability 15, no. 18: 13888. https://doi.org/10.3390/su151813888

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