Environmental Kuznets Curve Hypothesis Research Articles

Economic Growth and Environmental Sustainability in Developing Economies

This study examines the impact of economic growth and foreign direct investment (FDI) on environmental degradation in 76 developing economies between 1991 and 2022, using various panel data models. Firstly, the environmental Kuznets curve hypothesis is supported, indicating that, as the economy expands, cleaner technologies and practices are adopted, resulting in lower carbon emissions. Secondly, FDI and carbon emissions are positively related, suggesting that investment type and regulatory frameworks must be considered carefully. This analysis underlines the impact of abundant natural resources on emissions and stresses the significance of diversification strategies and the transition to cleaner technologies. Thirdly, further analysis involving interaction effects indicates that environmental degradation increases when high economic growth, abundant resources, and substantial FDI occur simultaneously. These findings highlight the importance of devising context-specific strategies and policies to balance economic growth and environmental sustainability in developing economies.

The vulnerability to climate change in Africa: Does industrial development matter?

AbstractIn a context marked by an upsurge in the scale of climate change and its consequences in Africa, this article explores ways to increase the resilience of African economies. It aims to analyze the effect of industrialization on the continent's vulnerability to climate change (VCC). The sample used for this purpose consists of 41 African countries from 2010 to 2021. A dynamic panel model is estimated using the system generalized method of moments. Results show that industrialization reduces the VCC in African countries. It reduces their sensitivity to climate change while increasing their adaptive capacity. Furthermore, results show that industrialization is more likely to reduce the VCC in sectors such as ecosystems, habitat, health, and infrastructures whereas it increases vulnerability to climate change in the food and water sectors. The results, however, reject the environmental Kuznets curve hypothesis between industrialization and VCC. These results are robust to the change in industrialization measures. Therefore, African countries would benefit from pursuing their industrial development through greater use of renewable energy. This can help them to sustainably reduce their VCC. In addition, they need to implement specific measures to adapt to climate change in the food and water sectors.

Quantifying Environmental Degradation through Renewable Energy, Financial Development and Economic Sustainability: Insights from Panel Quantile Regression Analysis

The degradation of the environment is a global concern that needs serious attention, including the environmental Kuznets curve (EKC) hypothesis. This article examines the effects of renewable energy, financial development and economic sustainability on the environmental quality of newly industrialized countries (NICs) from 1998 to 2021 in light of the increasing severity of environmental problems associated with industrialization. This study utilized different panel cointegration estimation techniques and panel quantile regression (PQR) estimates to obtain robust findings by examining the variance of each quantile. The results of the cointegration tests confirm the long-run relationship among the variables. Nevertheless, the outcomes from the PQR unveiled that renewable energy negatively and significantly influences CO2 emissions in NICs, namely in the lower and middle quantiles (20th–50th). Financial development showed heterogeneity in the results of all the quantiles. It results in an increase in CO2 emissions from the 70th to 90th quantiles in NICs. The EKC hypothesis is relevant to these findings as this study presents the economic sustainability index, which postulates that when NICs achieve sustainability, they give greater importance to environmental preservation and sustainability. This shift is characterized by reduced emissions throughout all quantiles, ranging from the 10th to the 90th. Economic sustainability corresponds to the falling part of the U-shaped curve of the EKC, wherein sustainability gets priority, resulting in reduced CO2 emissions. Analogous results have been confirmed by comparing heterogeneous panel estimators; nonetheless, there was a significant variation in the intensity of their parameters. Moreover, the robustness analysis through quantile slope equality and symmetric quantiles tests proved legitimate results. The study’s findings offer policymakers with valuable policy recommendations. JEL Codes: C1, F36, F43, O44, Q56

Airlines’ Corporate Growth and Environmental Conservation: Evidence from Global Carriers and Forwarders

This study explores how global airlines can achieve growth and environmental conservation using transport, financial performance, and carbon dioxide (CO₂) emissions data before, during, and after the COVID-19 pandemic from 2019 to 2022 with manually collected data for 38 leading international airlines. First, the regression analyses identify a clear range of turning points that airlines should consider in terms of Scopes 1 and 2 CO₂ emissions per employee and cargo ton-kilometers per employee (cargo ton-kilometers (CTK)/EMP) considering the environmental Kuznets Curve (EKC) hypothesis. Second, the deciding factors, including fundamental efforts by the airlines themselves, result from the interaction of three points, which have been encouraged and promoted in the airline industry in recent years. (1) Tighter emissions controls for air transport, (2) investors’ emphasis on environment, society, and governance (ESG), and (3) assessments and guidelines from ratings agencies and economic and environmental organizations. Third, increasing CTK/EMP to verified thresholds and taking an ESG-oriented approach can contribute to airlines’ combined achievement of growth and environmental conservation and related data will expand academic and policy-related research.

An Empirical Investigation of GDP, Industrialization, Population, Renewable Energy and CO2 Emission in Bangladesh: Bridging EKC-STIRPAT Models

This research paper explores the presence of the Environmental Kuznets Curve (EKC) in Bangladesh, delving into the intricate relationships among GDP, industrialization, renewable energy utilization, and CO2 emissions. Utilizing the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, our investigation spans the 1992 to 2021 timeframe, offering a comprehensive analysis of the interplay between these crucial factors in the context of Bangladesh's environmental sustainability. In this study, the F-bound test is utilized to establish the cointegration relationship among variables. And the short-run and long-run elasticity of explanatory variables is investigated by employing the Autoregressive Distributed Lag (ARDL) approach. This research also employed a pairwise granger causality test to explore the direction of causality between them. Empirical results prove the existence of a cointegration relationship among CO2 emission, GDP per capita, a quadratic form of GDP per capita, renewable energy, industrialization, and population. The findings provide strong support for the presence of the EKC in the case of Bangladesh. Besides that, significant inverse relationship was also obtained between CO2 emission and renewable energy consumption. Additionally, the study found the detrimental long-term effects of industrialization on the environment. The EKC hypothesis argues that Bangladesh can accomplish sustainable economic development. To attain the goal country should adopt appropriate government policies and ensure their implication. This study strongly advocates using sustainable energy sources and implementing regulations on pollutant industries.

Another look at energy consumption and environmental sustainability target through the lens of the load capacity factor: Accessing evidence from MINT economies

AbstractThe relationship between energy utilization and the environment is crucial in an era of environmental concerns by global economies and rising energy consumption. Emerging economies such as Mexico, Indonesia, Nigeria, and Turkey (hereafter, MINT) face complex trade‐offs between economic growth and environmental sustainability. Strengthening this study are the UN Sustainable Development Goals prepositions on access to clean and alternative energy, decent economic growth, responsible production and consumption and climate action (UN‐SDGs‐7, 8, 12, and 13). The present study examines the environmental Kuznets curve (EKC) hypothesis for MINT economies within the framework of the load capacity factor (LCF). The article leverages panel econometrics to operationalize the relationship between study variables. Empirical findings show that the present study fails to confirm the presence of EKC. Thus, it implies that the MINT economies are at their first stage of accelerated economic growth which might result in an augmented ecological footprint and exert pressure on natural resources, as indicated by the observed negative outcome. Furthermore, there is a positive and significant relationship between renewable energy consumption (RENENG) and LCF. It implies that a 1% increase in RENENG leads to an increase in LCF of 0.70%. These outcomes indicate that the level of RENENG in MINT economies is not sufficient to mitigate climate change issues. Thus, from a policy perspective, there is a need for change in the MINT nations' energy portfolio mix, such as the need to switch from conventional energy sources (fossil fuels) to renewable energy sources, including solar, wind, photovoltaic and hydropower, which usually have a smaller negative impact on the environment. Furthermore, there is a need for investment in new and green energy technologies in the countries investigated to arrive at a clean and better ecosystem as desired. More insight is outlined in the concluding section.

Unraveling the Environmental Consequences of Trade Openness in South Africa: A Novel Approach Using ARDL Modeling

Abstract Free trade and environmental sustainability are currently top economic and environmental research priorities. While numerous theories connect trade openness with environmental quality, empirical evidence often fails to support these claims. Using data spanning from 1980 to 2020, our study examines the effect of trade openness on CO2 emissions in South Africa. By employing a novel ARDL modeling framework, our analysis confirms the presence of the Environmental Kuznets Curve (EKC) hypothesis in South Africa. Our findings reveal that while GDP square enhances environmental quality, trade openness and economic growth have a degrading effect over time. Additionally, the study identifies that energy consumption, FDI, and value-added activities all contribute to environmental degradation. Findings also highlights the influence of institutional quality on the environment, demonstrating that political stability and control of corruption lead to increased CO2 emissions, while the rule of law reduces CO2 emissions. The research suggested that the potential of green economies should be leveraged in developing renewable energy, sustainable development, the recycling industry, and green financing sectors. A shift in economic activity in this direction will thus foster long-term economic growth and sustainable development.

The impact of aggregated and disaggregated fisheries production and licensed fishermen on fishing grounds footprint: A time series analysis

This study has examined the factors of fishing grounds footprint in Malaysia during 1961–2018, which has been used as the indicator of environmental degradation. The main contribution of this paper is that we have considered the role of aggregated and disaggregated fisheries production on pollution in the fishing industry. Another contribution of this study is that the environmental impact of activities of licensed fishermen has been examined. The results suggest that the total fisheries production and its components- capture fisheries production and aquaculture production generate an increase in fishing grounds footprint in Malaysia. The results suggest that an increase in total licensed fishermen facilitate an increase in fishing grounds footprint. There is mixed evidence on the impact of local fishermen on fishing footprint. The results indicate that an increase in foreign fishermen facilitate an increase in fishing grounds footprint. The results suggest mixed evidence for Environmental Kuznets Curve (EKC) hypothesis.

Impact of human capital and natural resources on environmental quality in South Asia

AbstractThis study examines the importance of human capital and natural resources on environmental quality in South Asia by using panel data that ranges from 1975 to 2021. Advanced cointegration approaches establish the long-term linkages between human capital, natural resources, economic growth, economic growth squared, urban population, industrial value added, and ecological footprint. To explore the long and short-run association among these variables, this study applied the panel autoregressive distributed lags (ARDL) model. The outcome designates that human capital has a negative and significant alliance with environmental quality, whereas economic growth and economic growth square affect environmental quality positively and negatively, confirming the existence of the environmental Kuznets curve (EKC) hypothesis. Urban population growth and natural resources have significant negative associations with environmental pollution, whereas industrial value added increases the pollution levels in South Asia. Lastly, the outcome of the interaction between human capital and natural resource rent on the ecological footprint has a significant positive effect. This study recommends that South Asian nations improve their human capital to promote industrial modernization, expansion of green technology, and energy-efficient habits. Utilizing natural resources also helps South Asian nations maintain a clean ecosystem. Additionally, South Asian nations ought to vigilantly track the negative consequences of industrialization on the atmosphere. Thus, ecological sustainability requires human capital and natural resources.

Natural resources as a double-edged sword towards ecological quality: Can environmental regulations and green human capital rectify the adverse impacts?

Natural resources are the backbone of any economy and the bedrock of ecological health. However, the relentless exploitation of these resources has given rise to ecological degradation. This threatens ecosystem stability, presenting the urgent need to balance natural resource utilization with ecological integrity. Environmental regulations and green human capital are pivotal in striking this balance and progressing towards the Sustainable Development Goals (SDGs). Therefore, this study explores how natural resources impact ecological quality in Ghana from 1990 to 2019 within the environmental Kuznets curve (EKC) framework, considering the role of environmental regulations and green human capital. The study employs the novel dynamic ARDL simulation method, presenting insights that diverge from patterns noted in previous studies. The study's findings reveal that natural resources intensify ecological quality in the short term but degrade ecological quality over the long term. Environmental regulation reduces ecological harm, while green human capital negatively impacts ecological quality. Environmental regulation and green human capital undesirably and beneficially impact how natural resources relate to ecological quality, with the undesirable effects occurring in the short term and the beneficial effects emerging over the long term. Further, a U-shaped relationship is observed between economic growth and ecological pollution in the short term, which transforms into an inverted U-shaped relationship in the long term, thus validating the EKC hypothesis in Ghana. The study concludes by recommending the implementation and enforcement of environmental regulations as a pathway toward achieving ecological quality and SDGs, particularly SDG 13, SDG 12, and SDG 7.

Investigating the environmental Kuznets curve hypothesis with urbanization, industrialization, and service sector for six South Asian Countries: Fresh evidence from Driscoll Kraay standard error

South Asia is the most polluted region in the world and is struggling to deal with the effects of growing CO2 emissions and the ecological impact it has left. The region needs to identify the variables that are most effective in reducing pollution in order to achieve long-term sustainable growth. The current study aims to investigate the environmental impacts of the current and projected urbanization rate, the service sector, and the availability of natural resources to test the environmental Kuznets-curve (EKC) theory in six South Asian countries (SAARC). With cross-sectional dependence present, this research examines panel data from 1972 to 2021 using the newly developed Driscoll Kraay Standard Error (DKSE) approach. To check the robustness of DKSE estimation, the study employs a novel Cross Sectional Autoregressive Distributive Lag (CS-ARDL) method. The results of DKSE show that GDP significantly minimizes CO2 emissions in both the short and long run. At the same time, GDP2, urbanization, and the service sector increase CO2 emissions in the South Asian region. The DKSE estimator also shows that industrialization and abundant natural resources have insignificant impacts on CO2 emissions. Inconsistent with the EKC hypothesis, the findings show that higher economic growth leads to increased environmental pollution and CO2 levels. Meanwhile, the CS-ARDL analysis found that GDP and industrialization reduce CO2 emissions, while urbanization, GDP2, and natural resource availability increase CO2 emissions. This research emphasizes the need for establishing appropriate industrialization and urbanization strategies and promoting cleaner energy adoption to reduce CO2 emissions.

Reinvestigating the EKC hypothesis: Does renewable energy in power generation reduce carbon emissions and ecological footprint?

For a developing nation such as Malaysia with a significant reliance on fossil fuels for electricity, understanding the environmental consequences of this dependency is crucial. Thus, this study utilizes the Autoregressive Distributed Lag (ARDL) method to explore the impact of electricity intensity (EINT), renewable energy in electricity generation (ERE), and gross domestic product (GDP) on Malaysia's environmental quality, from 1985 to 2020. By using carbon emissions (CO2 emissions) and ecological footprint (EF) as proxies, the study finds a significant long-run impact of these factors on environmental degradation. Notably, the study also observed an inverted U-shaped relationship between GDP and environmental degradation, validating the existence of Environmental Kuznets Curve (EKC) hypothesis. The findings also imply that while electricity intensity is associated with increased emissions, the use of renewable energy (RE) sources for electricity generation may contribute to emission reduction. But the results for both variables show reversal signs on EF. The study's adoption of the fully ordinary least square (FMOLS) method reinforces the same results, thus, justifying the cointegrating relationship between studied variables. Drawing from these outcomes, the study advocates for a comprehensive approach to renewable energy management, emphasizing both its utilization and waste in order to improve ecological footprint. Moreover, the pressing need to enact legislation on energy efficiency and conservation is crucial in ensuring decoupling and securing sustainable development in Malaysia.

Does macroprudential policy matter for corporate green innovation? The role of financing constraints and public environmental concerns

Green development ideas are gradually being incorporated into macroprudential policy frameworks, which can be of great significance for enterprises’ green development. Most studies focus on the macroeconomic impact of macroprudential policies (MPPs). However, the extent to which MPPs affect corporate green innovation (GI) at the corporate level remains unclear. Based on 12,280 firm-year records from China's A-Share Listed Companies spanning 2011–2020, combined with Environmental Kuznets Curve (EKC) hypothesis, we discover a firm tendency to promote GI under loosening MPPs, which is then curtailed after reaching a certain threshold. The impact is primarily channelled through public environmental concerns and financing constraints, as evidenced by an inverted U-shaped relationship. Additionally, MPPs are more likely to influence corporate GI in regions with high green finance development. Furthermore, we observed a consistent superiority of strategic over substantive GI, with green process innovation being the least impacted. Our results highlight the importance of rational design of MPPs not only at the macro level but also as a priority at the corporate level, as such a policy loosening and tightening will affect the GI activities of corporations.

Promoting sustainability in developing Countries: A Machine Learning-based approach to understanding the relationship between green investment and environmental degradation

The main objective of this study is to examine the impact of green investment on environmental degradation in developing countries using machine learning-based estimation combined with robustness tests of static and dynamic panel data modeling techniques. The scope of this study covers 30 developing countries for 2009–2019. This study introduces a new index of environmental degradation that uses the entropy method and includes green gas emissions and deforestation. The study addresses trade openness, the quadratic shape of economic growth, and urbanization in the context of the Environmental Kuznets Curve Hypothesis (EKC) and the Ecological Modernization Theory (EMT), in addition to green investment. This study considers the kernel-based regularized least squares (KRLS) approach, the static panel technique Driscoll & Kraay standards error method, and a dynamic panel technique system generalized moment techniques. The empirical findings from the machine learning method show that green investment significantly reduces environmental degradation with a higher coefficient resulting from the static fixed effect estimation. The study also reveals that the main hypotheses, such as EKC and EMT, are confirmed by all estimation techniques. Based on the results, the study recommends that policymakers take pragmatic steps toward green investments and increase the financing of green energy initiatives to combat environmental degradation.

Intelligence and its effects on environmental decline: A worldwide analysis

The research investigates the relationship between intelligence quotient (IQ) and environmental degradation, aiming to understand how cognitive abilities influence environmental outcomes across different nations and time periods. The objective is to examine the impact of intelligence quotient (IQ) on environmental indicators such as carbon emissions, ecological demand, and the Environmental Kuznets Curve (EKC), seeking insights to inform environmental policy and stewardship. The study utilizes statistical techniques including Ordinary Least Squares (OLS), Two Stage Least Squares (2SLS), and Iteratively Weighted Least Squares (IWLS) to analyze data from 147 nations over the years 2000–2017. These methods are applied to explore the relationship between IQ and environmental metrics while considering other relevant variables. The findings reveal unexpected positive associations between human intelligence quotient and carbon emissions, as well as ecological demand, challenging conventional notions of "delay discounting." Additionally, variations in the Environmental Kuznets Curve (EKC) hypothesis are identified across different pollutants, highlighting the roles of governance and international commitments in mitigating emissions. The study concludes by advocating for the adoption of a "delay discounting culture" to address environmental challenges effectively. It underscores the complex interactions between intelligence, governance, and population dynamics in shaping environmental outcomes, emphasizing the need for targeted policies to achieve sustainability objectives.

The effect of growth, deforestation, forest fires, and volcanoes on Indonesian regional air quality

As a rapidly developing country, Indonesia faces a challenge in improving air quality that is made more difficult by frequent forest fires linked to deforestation and volcanic eruptions. This paper analyses the link between development and air pollution in 30 Indonesian cities from 2002 to 2019. Air quality is measured using two novel regional air quality indicators (AQIs) for PM2.5 and PM10 estimated from weather observations and NASA satellite data on Aerosol Optical Depth (AOD). Results from an Environmental Kuznets Curve (EKC) analysis, based on a dynamic panel data model, show that forest fires and volcanic activity have significantly worsened regional air quality in Indonesia. The model also shows that the EKC hypothesis is rejected for Indonesia as cities have followed a monotonically increasing trend in air pollution with respect to economic growth. An additional 1% of economic growth increased long run pollution as measured by AQI PM2.5 and PM10 by 0.35% and 0.46%, and forest fire events by 0.11% and 0.06%. A partial Benefit-Cost Analysis (BCA) of forest fires shows that particulate matter pollution is excessive. Decreasing the frequency of forest fires by 1% would generate a net benefit of between US$17 million to 145 million. The lower estimate of the health benefits exceeds the agricultural benefits of forest fire without accounting for other non-market costs due to forest fires. Our results imply that, as Indonesia grows economically, air quality is likely to continue deteriorating. Further, regions affected by regular volcanic activity and wildfires should apply tighter emission standards to controllable point source emissions from industry and non-point source emissions such as agricultural forest fires.

Combining the role of urbanization and renewable energy in sustainable development: testing the EKC hypothesis for Africa.

The pressing necessity to curb greenhouse gas emissions due to climate change has sparked significant scientific interest in comprehending the factors behind CO2 emissions, particularly concerning environmental sustainability challenges. Nonetheless, there exists a notable gap in our understanding of how the process of urbanization interacts with the utilization of renewable energy to impact CO2 emissions. This research endeavor seeks to evaluate the complex interplay among urbanization, renewable energy, and CO2 emissions across 46 African nations spanning from 1990 to 2019. To accomplish this objective, a variety of econometric methodologies are employed, including Driscoll-Kraay standard errors, IV-GMM, and method of moments quantile regression (MMQR) panel estimations to address issues like cross-sectional dependencies, endogeneity, heterogeneity, and panel Granger causality examination. The empirical results suggest that urbanization leads to an increase in CO2 emissions, whereas the consumption of renewable energy plays a role in enhancing environmental quality by reducing CO2 emissions. A significant outcome of the study is the revelation that a combination of urbanization and renewable energy leads to a decrease in carbon emissions. Moreover, the Environmental Kuznets Curve (EKC) hypothesis is validated. Lastly, through the Dumitrescu-Hurlin panel causality test, it is uncovered that urbanization and renewable energy consumption exhibit a bidirectional relationship with CO2 emissions. To reduce dependence on fossil fuels and curb CO2 emissions, policymakers should promote renewable energy usage in urban areas.

Does emerging country's urbanization redefine the environmental Kuznets hypothesis for carbon emissions? A novel perspective on national and subnational differences

Emerging countries are experiencing rapid urbanization. Examining the link between economic growth and carbon emissions in developing nations as well as the effects of urbanization on this relationship at the national and subnational levels are the goals of this research. Thus, to investigate if China's economic development and carbon emissions align with the environmental Kuznets curve (EKC) hypothesis, this study adopts the FMOLS model and the fixed effects model. Furthermore, this study uses urbanization as a threshold variable and examines how the influence of economic development on carbon emissions would alter as a result of urbanization. The findings demonstrate an inverted U-shaped link between China's economic development and carbon emissions and the relationship is compatible with the EKC hypothesis. Although there is variability at the subnational level, most of the regions follow the inverted U-shaped connection. The carbon emissions inflection point in the western area is larger than the inflection points in the eastern and central regions. According to the threshold model, as urbanization rises, the increase in carbon emissions brought on by economic expansion declines. The eight economic areas of China differ in how the link between economic growth and carbon emissions change in the process of urbanization. But compared to the initial stage of urbanization, the last stage of urbanization in most countries lessens the impact of economic expansion on carbon emissions. To decrease carbon emissions, we must not only encourage the development of cleaner technologies and boost energy consumption efficiency, but also create carbon-reduction strategies that are specific to the growth characteristics of various areas.

Economic complexity, renewable energy and ecological footprint: The role of the housing market in the USA

Prior studies tested the environmental Kuznets curve hypothesis via the income channel, but few studies have used the housing market to examine this relationship; these papers are constrained due to the fact that CO2 emission was used as a measure of environmental deterioration, which only accounts for air pollution. Therefore, this study aims to bridge this gap by employing the housing market to test for the validity of the environmental Kuznets curve using ecological footprint in the case of the USA, which serves as a more comprehensive measure of ecological equality. The present work is the first study to explore the impact of the housing market on ecological footprint in the context of the USA. The study uses the novel bootstraps ARDL approach to assess the effects of the housing market, renewable energy, economic growth, and economic complexity on the ecological footprint in the case of the USA from 1980 to 2018. The outcomes revealed that the impacts of renewable energy and economic complexity on ecological footprint are positive and statistically significant. In addition, the environmental Kuznets curve theory has also been validated in the case of the USA. The empirical results also indicate that the housing market adversely influences ecological quality. Based on the study findings, this study offers several policy implications for the USA policymakers to promote ecological sustainability by formulating comprehensive economic and green energy policies. Furthermore, the study suggests that USA policymakers should promote a high level of complexity through knowledge and skills to achieve a sustainable ecosystem.

Assessment of the influence of institutions and globalization on environmental pollution for open and closed economies

AbstractAs the environmental sustainability effectiveness of various political systems is taken into consideration, it is doubtful as to whether the presumption of the overall efficiency of democracy can be sustained in global governance architecture. The effectiveness of autocracies and democracies (i.e., governance indicators are compared in the present study) with reference to strengths and weaknesses in environmental objectives. This analysis explores the effect of autocracy, democracy, as well as the trend of globalization on CO2 emissions for open and closed economies from 1990 to 2020. Crucial indicators such as economic growth, renewable energy and non-renewable energy are controlled for while examining the roles of economic expansion on the disaggregated energy consumption portfolios for both open and closed economies. The empirical analysis revealed some insightful results. First, for the open economies, with the exception of non-renewable energy which shows a positive significant impact on emissions, all variables show a negative effect on emissions. Furthermore, the closed economies result indicate that, apart from renewable energy which has a negative relationship with emissions, all the variables including the interaction terms have a positive relation with emissions. However, an inverted U-shaped environmental Kuznets curve hypothesis was validated for both economies.