Common Correlated Effects Mean Group Research Articles

Evaluating the Influences of Health Expenditure, Energy Consumption, and Environmental Pollution on Life Expectancy in Asia

This study examines the effects of health expenditure, energy consumption, CO2 emissions, population size, and income on health outcomes in 46 Asian nations between 1997 and 2019. Cross-sectional dependence (CSD) and slope heterogeneity (SH) tests are utilized due to the close linkages between Asian nations as a result of commerce, tourism, religion, and international agreements. The research uses unit root and cointegration tests of the second generation after validating CSD and SH issues. Due to the results of the CSD and SH tests, it is clear that conventional methods of estimation are inappropriate, so a new panel method, the inter autoregressive distributive lag (CS-ARDL) model, is used instead. In addition to CS-ARDL, the study's results were checked with a common correlated effects mean group (CCEMG) method and an augmented mean group (AMG) method. According to the CS-ARDL study, higher rates of energy use and healthcare spending lead to better health outcomes for Asian countries over the long run. CO2 emissions are shown to be harmful to human health, according to the study. The influence of a population's size on health outcomes is shown to be negative in the CS-ARDL and CCEMG, but favorable in the AMG. Only the AMG coefficient is significant. In most instances, the results of the AMG and CCEMG corroborate the results of the CS-ARDL. Among all the factors influencing life expectancy in Asian countries, healthcare spending is the most influential. Hence, to improve health outcomes, Asian countries need to take the required actions to boost health spending, energy consumption, and long-term economic growth. To achieve the best possible health outcomes, Asian countries should also reduce their CO2 emissions.

Modelling Sustainable Non-Renewable and Renewable Energy Based on the EKC Hypothesis for Africa’s Ten Most Popular Tourist Destinations

The main purpose of this study was to examine how tourism, GDP, renewable energy, and fossil fuels cause environmental damage. This study examined ten African countries between 1997 and 2021 to test the environmental Kuznets curve (EKC) theory. Egypt, South Africa, Kenya, Morocco, Tanzania, Tunisia, Mauritius, Ghana, Uganda, and Nigeria are the ten African countries with the most tourists. In this paper, the augmented mean group (AMG), mean group (MG), and common correlated effects mean group (CCEMG) models were used to deal with slope heterogeneity (SH), cross-sectional dependence (CSD), and a mix of first-differenced and level stationary variables. Though the inverted U-shaped exists, the findings are significant only for MG. The impact of renewable energy is favorable for the environment and significant for the AMG estimator. Inversely, impact of tourist arrivals and fossil fuels are detrimental for environment and significant. Based on the findings for each country, the tourism-based EKC theory only works for Kenya, Egypt, and Tanzania. The research found that using more renewable energy minimizes CO2 emissions more effectively in almost all countries except Morocco and Ghana. Ghana, Kenya, and Uganda’s CO2 emissions increase when more tourists come from other countries. For the sake of both tourism and the environment, the government must reconsider its tourism policies and implement ones that include renewable energy. The findings of this study assist in the transition to clean energy, aiding in sustainable tourism growth. As a result, selected countries should develop a new tourism plan that focuses on renewable energy sources and protects the environment.

Unleashing the influence of natural resources, sustainable energy and human capital on consumption-based carbon emissions in G-7 Countries

The nexus of natural resources and cleaner energy with carbon emissions or ecological footprint has been explored extensively; however, consumption-based carbon emissions (CBCE) are adjusted for natural resources, sustainable energy, and human capital have not been studied, though environmental deterioration primarily emanated from anthropogenic activities. Consequently, this research investigates the linkages between natural resources, sustainable energy, human capital, and CBCE in G-7 economies from 1976 to 2020 using a battery of advanced econometric statistical models. The empirical outcomes of this article, through the cross-sectional autoregressive distributive lag (CS-ARDL) model, estimate the short- and long-run findings, which explain that natural resources, cleaner energy and human capital preserve whereas urbanization exacerbates the environmental quality. More so, imports have a positive whilst exports bear a negative connection with CBCE in advanced countries. The results of the study are further validated by employing the Augmented Mean Group (AMG) and Common correlated Effects Mean Group (CCEMG) to obtain robust outcomes. In the end, policies that can improve sustainable development through key variables are discussed to provide inclusive recommendations for stakeholders to meet the carbon neutrality targets.

Probing the environmental impacts of structural transition and demographic mobility in Africa: Does technological innovation matter?

Although available statistics reveal Africa as an insignificant contributor to the devastating global climate condition, the succeeding impacts seem to hit the region harder than others. Efforts to address the environmental issues have seen the transition from carbon-intensive to carbon-abating sectors. Hence, this study makes the first empirical attempt to probe the ecological effects of structural transition and demographic mobility amidst the presence of technological innovation, foreign direct investment, and renewable energy. The empirical evidence focuses on the five highest emitters in Africa from 1990 to 2019 using advanced estimators, including cross-sectional autoregressive distributed lag (CS-ARDL), augmented mean group (AMG), common correlated effect mean group (CCEMG), and method of moment quantile regression (MMQR). For easy tracking of emanating effects, structural transition is captured by agriculture, manufacturing, and service sectors’ value added, whereas demographic mobility vectors rural and urban population. The results reveal agriculture sector, manufacturing sector, rural population, and urban population as amplifiers of CO2 emissions. Conversely, the moderating roles of technological innovation amidst service sector, foreign direct investment, and renewable energy are confirmed. Besides, Granger causality uncovers unidirectional and bidirectional causality in the model. Promoting developments in research and development and adopting carbon tax policies are among the emanating policies on the findings.

Recent developments in green hydrogen–environmental sustainability nexus amidst energy efficiency, green finance, eco-innovation, and digitalization in top hydrogen-consuming economies

The present era is facing a dilemma relating to engaging the essentialities of energy resources to attain economic prosperity due to the ensuing environmental complications. Consequently, sectors such as transport, aviation, and refining industries are under the scrutiny of reducing their reliance on fossil fuels achievable with the promotion of hydrogen energy which is largely neglected in the environmental empirics. To this end, the environmental impacts of green hydrogen in the top seven hydrogen-consuming countries are assessed from 1995 to 2019. Moreover, the roles of green finance, environmental-related technologies, energy efficiency, and digitalization are considered in the model specified within the STIRPAT framework. Second generation estimators comprising cross-section autoregressive distributed lag, Common Correlated Effect Mean Group, Augmented Mean Group, and Method of Moment Quantile Regression are employed in evaluating the stated hypotheses. Feedbacks from the analysis uncovered that green hydrogen; green finance, environmental-related technologies, energy efficiencies, digitalization, and structural change promote environmental sustainability in the top seven hydrogen-consuming countries. Contrariwise, natural resource dependence and urbanization trigger CO2 emissions, thereby exacerbating environmental complications. Based on the findings, policy measures leading toward sustainable environment are suggested.

Role of green technology, environmental taxes, and green energy towards sustainable environment: Insights from sovereign Nordic countries by CS-ARDL approach

This study analyzes comprehensively the role of green technology, environmental taxes, and green energy toward a sustainable environment in 5 sovereign Nordic countries by also considering income and population. For this purpose, annual data of Nordic countries from 1995 to 2020 is extracted and the cross-sectional augmented autoregressive distributed lag (CS-ARDL) technique is applied to test short-run and long-run compatibilities of the indicators on carbon dioxide (CO2) emissions. Moreover, Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) approaches are applied for robustness checks. The empirical results reveal that (i) green technology, environmental taxes, and green energy have a negative association with CO2 emissions in the both short-run and long-run; (ii) income and population have a positive association between CO2 emissions in the both short-run and long-run; (iii) AMG and CCEMG approaches report similar findings with the CS-ARDL and validate the robustness in turn. Thus, the empirical results confirm the contributing role of green technology, environmental taxes, and green energy toward a sustainable environment in 5 sovereign Nordic countries. Moreover, policy implications are discussed.

Revisiting the Environmental Kuznets Curve Hypothesis in the MENA Region: The Roles of International Tourist Arrivals, Energy Consumption and Trade Openness

This paper employed advanced panel methods to examine the effects of international tourist arrivals on CO2 emissions in the Middle East and North Africa (MENA) region over the period of 1995–2018. To analyze the predictive power of tourist arrivals for CO2 emissions, the panel Granger non-causality test was employed. Employing the common correlated effects mean group estimator showed that tourist arrival reduces CO2 emissions, while energy consumption and trade openness are the main contributors of CO2 emissions. Results also showed that although first-generation estimators confirmed the Environmental Kuznets Curve (EKC) hypothesis, according to the CCE-MG estimator, an inverted U-shaped association between economic progress and CO2 emissions does not exist. Furthermore, the null hypothesis of non-Granger causality from tourist arrivals to CO2 emissions was rejected. The findings suggest taking a more sustainable approach to tourism development and energy conservation in the long run.

PURCHASING POWER PARITY THEORY: A CROSS-SECTIONAL DEPENDENCE PANEL DATA ANALYSIS OF SIXTEEN DEVELOPED COUNTRIES

This paper examined the purchasing power parity (PPP) theory for a group of sixteen developed countries using powerful statistical panel data methods that account for cross-sectional dependence. The paper utilized the Pesaran panel unit root test, the cointegration test of Westerlund, the Augmented Mean Group (AMG) estimator, the Common Correlated Effect Mean Group (CCEMG) estimator, and the panel data Granger non-causality test of Dumitricus and Hurlin to analyze the causal relationships among the variables involved in the study. The tests showed that the PPP theory occurs in this group of countries. Furthermore, outcomes of the long-run estimation revealed both depreciation and appreciation of the nominal exchange rates. Apart from providing important policy implications on the results obtained, this paper made another significant contribution by extending the linear AMG and CCEMG estimators into nonlinear estimators and further used them in examining the long-run PPP theory.

Evaluating the role of renewable energy and technology innovations in lowering CO2 emission: a wavelet coherence approach.

Environmental sustainability is one of the most critical issues that require efficient environmental and economic policies in modern times. Advancements in renewables and green technologies contribute significantly to sustained long-term development without affecting environmental quality. Several studies focus on the association of carbon dioxide emissions (CO2e) with economic variables. However, they ignored the impact of technological innovations and renewable energy consumption on CO2e in developed countries. Therefore, this study examines the relationship between CO2e, energy consumption, gross domestic product (GDP), renewable energy consumption, and technology innovations in G-7 countries by employing cross-sectionally augmented autoregressive distributed (CS-ARDL) lag and wavelet coherence techniques during 1990-2020. The results depict that GDP and renewable energy consumption are inversely related to CO2e. A 1% increase in CO2e will decrease GDP and renewable energy consumption by 0.459 and 0.172% in the long run and by 0.471 and 0.183% in the short run in G7 countries. Technology innovations negatively impact CO2e in the short run while positively influencing it in the long run. Considering the advancements in green technologies in different energy-dependent and manufacturing sectors is crucial for a sustainable environment in the long run. Such initiatives ensure the effective use of energy sources by limiting CO2e in the atmosphere. Moreover, the dynamic common correlated effects mean group model confirms the reliability and effectiveness of the CS-ARDL. The wavelet coherence approach revealed a causality relation between CO2e and technology innovation in Italy, Japan, the UK, and the USA during the study period.

The prominence of fossil energy resources in ecological sustainability of BRICS: The key role of institutional worth

Introduction: The relationship between fossil fuel energy resources and environmental degradation has been quantified from theoretical and empirical perspectives. However, none of these studies has considered the conditioning role played by institutions in the nexus, especially for BRICS countries. Therefore, the current study examines the moderating role of institutional quality using annual data from 1996–2018 for BRICS countries.Method: The study employs the novel cross-sectional augmented autoregressive distributed lags (CS-ARDL) estimator, robust to cross-sectional dependency and heterogeneity, for short-run and long-run estimation. Moreover, augmented mean group (AMG) and common correlated effects mean group (CCEMG) estimators are used for robustness analysis.Results: The finding reveals that fossil fuel energy resources, globalization, and growth significantly positively affect the ecological footprint, whereas the institutional quality significantly negatively effects the ecological footprint in BRICS countries. Furthermore, the interaction term of institutional quality with fossil fuel energy resources significantly negatively moderates the fossil fuel energy-EFP nexus. Finally, we performed the Dumitrescu and Hurlin (DH) panel causality analysis to determine the causality direction between the variables. Except for intuitions quality and growth, we found a unidirectional causality for explanatory variables and EFP.Discussion: The study provides novel empirical evidence and recommends the importance of institutional quality for environmental sustainability.

How can environmental degradation and income disparities influence national health: an eye bird view on China's provinces.

Growing socio-economic disparity is a global issue that could disturb community health. Numerous case studies have examined the health influences of income disparities as well as the patterns that implicate those disparities. Therefore, this study attempts to examine the core determinants of mortality rate, which are environmental degradation, green energy, health expenditures, and technology (ICT) for the 25 provinces of China over the period of 2005-2020. This study uses a series of estimators to investigate the preferred objectives in which CS-ARDL and common correlated effect mean group (CCE-MG). Estimated results show the significant contribution of environmental deterioration and income inequality to the mortality rate. Furthermore, health expenditures, ICT, and green energy significantly reduce the mortality rate. Similarly, the moderate effect of income inequality on health expenditure, green energy, and ICT significantly reduces the mortality rate in selected provinces of China. More interestingly, the current study suggests policy implications to reduce the rising trend of mortality rate.

Renewable energy consumption and Inclusive Growth: Evidence from 20 African countries

In Africa, the need for energy is growing. When it comes to renewable energy resources in Africa zone, it is unequivocally needed. Many African countries are experiencing development therefore they are shifting to the use of renewable energy. In that view, this study aims to discover the potential impact of renewable energy consumption on inclusive growth in 20 African countries for a period covering 1997 To 2015. To tackle this estimation technique namely Pesaran’s (2007) [1] CD test, Pesaran’s (2015) [2] LM test and Breusch and Pagan’s (1980) [3] LM test, slope homogeneity test, Average Mean Group (AMG), Common Correlated Effects Mean Group (CCEMG) and pairwise granger were employed. Concentration on inclusive growth contributes greatly to the economy size and ensures employment opportunity creation for the society in a different segment, the result of the study indicates that renewable energy consumption significantly impacted inclusive growth in n the selected Africa Countries. Consequently, if countries like Africa prosper in switching to renewable energy, unbelievable gains could be captured in terms of inclusive growth.

Exploring the heterogeneous effects of technological innovations on environmental sustainability: Do structural change, environmental policy, and biofuel energy matter for G7 economies?

The global economy has realized that global warming issues should not be treated with levity. Instead, conscientious and meticulous measures must be taken to address the unwavering ravaging impacts of ecological complications of which technological innovations stand out. Despite the emphasis on technology as a viable pathway to zero emissions by the recent 26th Conference of the Parties (COP26), the feasibility of achieving the global target remains vogue from the empirical perspective. Hence, this study presents the first empirically based evidence on the heterogeneous effects of technological innovations on environmental sustainability in Group of Seven (G7) countries from 1995 to 2019. For robust policy insights, the study controls for the functional roles of structural change, environmental policy, biofuel energy, and trade openness in verifying the empirical model. The empirical evidence relies on second-generation estimators comprising cross-sectional autoregressive distributed lag (CS-ARDL), augmented mean group (AMG), common correlated effects mean group (CCEMG), and panel method of moment quantile regression (PMMQR) that are robust for the issues of slope heterogeneity and cross-sectional dependence. The main findings show that the various components of technological innovations, structural change, environmental policy, and biofuel energy support environmental sustainability by exerting statistically adverse effects on CO2 emissions. In contrast, trade openness appears as a deterrent to sustainable environment by statistically and positively impacting CO2 emissions. Besides, the findings reveal bidirectional and unidirectional causality pathways in the nexuses investigated for G7. Based on the empirical fallouts, viable policy insights that lead to achieving the net zero emissions target are formulated.

Do globalization and nuclear energy intensify the environmental costs in top nuclear energy-consuming countries?

Nuclear energy is considered an effective alternative to ensure global energy safety, and it has recently started to be promoted as a climate change mitigation solution to achieve low-carbon energy transition targets. Considering this view, this study aims to assess the environmental cost reduction by using nuclear energy efficiency and technological innovation from the prospects of the globalization process. Therefore, the relationship among carbon emissions, nuclear energy, globalization, and technological innovation was assessed in the top ten nuclear energy-consuming countries from 1990 to 2017 while controlling for economic growth and renewable energy. This study applied Common Correlated Effects Mean Group (CCEMG), Augmented Mean Group (AMG), and Dumitrescu-Hurlin causality techniques for model estimation that solves the problem of cross-sectional dependence and slope heterogeneity. The empirical results indicated that nuclear energy and technological innovation diminish environmental costs by reducing carbon emissions. However, globalization increases environmental costs by releasing more carbon emissions into the atmosphere. Moreover, bidirectional causality exists among nuclear energy, renewable energy, and carbon emissions. Consequently, the highest nuclear energy-consuming countries must utilize nuclear energy efficiency to control environmental costs and a cost-effective path to a low-carbon economy. Finally, this perspective intended to appeal to policymakers to do a better job of substantiating their decisions.

The dynamic impact of energy productivity and economic growth on environmental sustainability in South European countries

In the wake of global warming, the world is in an ecological state of disarray. Consequently, governments across the globe are committing to achieving low temperatures with a target of 1.5 °C, of which South European countries play a key role. This study aims to examine the effects of energy productivity (EP), economic growth (GDP), and globalization (GLO) on CO2 emissions of Cyprus, Spain, Portugal, Italy, Greece, and Malta (Southern European countries). The study covers the time from 1990 to 2018. Unlike earlier studies, the current analysis considers EP a significant factor in determining CO2 emissions in Southern European countries. Southern European countries primarily represent a group of emerging economies, but it is relatively ignored in empirical environment literature. This study is the first to reveal a newly second-generation connection among EP, GDP, GLO, and CO2 emissions in the Southern European countries by using the novel method of panel cointegration of Westerlund cointegration, Pedroni cointegration, augmented mean group (AMG), common correlated effects mean group (CCEMG), and followed by Dumitrescu–Hurlin causality tests. The empirical results suggest that the variables' effects are cointegrated, and EP reduces CO2 emissions while GDP, and GLO increase CO2 emissions in the South European countries. Furthermore, findings from the Dumitrescu Hurlin panel causality test suggest that any reductions in EP would have a positive impact on the extent of carbon emissions. On the basis of these empirical findings, this study suggests that policy administrators of the South European countries should consider the energy efficiency impact among the variables in setting their environmental, growth, and energy policies.

Do renewable energy consumption and financial development contribute to environmental quality in MINT nations? Implications for sustainable development

Maintaining a balance between the well-being of the economy and the environment has become a top priority for governments globally. In the contemporary age, world economies, particularly the emerging ones like MINT nations, highlight the need for eco-friendly economic expansion. The MINT nations are thriving economically but are having difficulty reducing their Ecological footprint (EF). This paper aimed to determine if factors such as population density, renewable energy, foreign direct investment, economic growth, and financial development impact ecological footprint in the MINT countries between 1990 and 2018. The study applied ample advanced econometrics such as method of moments quantile regression (MMQR), augmented mean group (AMG) and Common Correlated Effects Mean Group (CCEMG). The overall results indicated that the variables are integrated at the first difference and are cointegrated. The AMG, CCEMG and MMQR results reveal that economic growth deteriorates ecological well-being by promoting the EF while foreign direct investment, population density and renewable energy assists in enhancing it by mitigating the EF in the MINT nations. In addition, financial development does not exert a significant effect on EF. The Dumitrescu Hurlin Panel Causality results show unidirectional causality from economic growth, financial development, population density, and renewable energy to EF. Based on these results policy recommendations are suggested.

Economic Growth, Energy Mix, and Tourism-Induced EKC Hypothesis: Evidence from Top Ten Tourist Destinations

The tourism sector makes a sizable contribution to a country’s gross domestic product, increasing employment opportunities, foreign currency earnings, and economic diversification strategies. This paper uses the Environmental Kuznets Curve (EKC) model to analyze the effects of tourism on the environment in the world’s top 10 tourist countries from 1972 to 2021. Panel cointegration and second-generation unit root tests are suggested due to the presence of cross-sectional dependence and slope heterogeneity. A cross-sectional-autoregressive-distributed lag (CS-ARDL) model is applied to evaluate the marginal influence of environmental variables other than tourism on carbon dioxide (CO2) emissions. These variables include fossil fuels, renewable energy, and nuclear energy. For the purpose of testing robustness, both the augmented mean group (AMG) and the common correlated effects mean group (CCEMG) estimators are employed. The CS-ARDL supports the EKC hypothesis in the short run and long run, but it is not significant in the short run. The existence of EKC demonstrates that rising income leads to fewer CO2 emissions. All forms of environmental degradation can be accelerated by using fossil fuels. The results of this study indicate that CO2 emissions can be reduced by using renewable energy and nuclear energy. A rise in tourism activity has a positive impact on environmental quality. The best-attended tourist spots around the globe are those that, in the long run, implement clean energy-related technology and promote ecotourism.

Role of country risks and renewable energy consumption on environmental quality: Evidence from MINT countries

This study focuses on uncovering the effect of country risks and renewable energy consumption on environmental quality. In this context, the study examines Mexico, Indonesia, Nigeria, and Turkey (MINT) nations; takes economic growth, trade openness, and urbanization into account; includes data from 1990 to 2018; applies cross-sectional autoregressive distributed lag (CS-ARDL) as the main model while common correlated effects mean group (CCEMG) and augmented mean group (AMG) for robustness checks. The empirical results show that (i) economic growth, political risk, urbanization, and trade openness contribute to an increase in ecological footprint; (ii) economic and financial risks as well as renewable energy use have a positive influence on environmental quality; (iii) a unidirectional causality exists from economic risk, financial risk, political risk, economic growth, urbanization, and trade openness to the ecological footprint: (iv) the validity of the EKC hypothesis for the MINT economies is verified; (v) the robustness of CS-ARDL results are validated by CCEMG and AMG approaches. Based on these results, policymakers should promote a sustainable environment to lessen the ecological footprint. Additionally, governments should firmly support investments in green technology as well as economic and financial stability to boost energy efficiency and promote the adoption and usage of energy-saving products.

Panel Estimation of the Environmental Kuznets Curve for CO2 Emissions and Ecological Footprint: Environmental Sustainability in Developing Countries

Abstract Research background: The relationship between the economy and the environment is one of the most frequently encountered issues recently. Today the issue of environmental sustainability is one of the problems faced by countries. Purpose: This study, it is aimed at investigating the relationship between economic and environmental variables. Research methodology: The existence of the environmental Kuznets curve theory, in other words, the inverted U-connection between per capita carbon dioxide emissions, per capita ecological footprint, and per capita GDP in the examples of 10 developing countries is examined. We analyzed annual balanced panel data covering the period 1992–2014 for an inverted U-link between carbon dioxide emissions and ecological footprint and per capita GDP. Westerlund’s cointegration test was applied as a cointegration test. The Common Correlated Effects Mean Group (CCEMG) and Augment Mean Group (AMG) estimator methods were applied for long-term parameter estimation. The Dumitrescu and Hurlin causality test was applied to determine the causal connections. Results: As a result of the study, a positive and significant effect of electricity consumption on carbon dioxide emission was determined in the long term in the model where the ecological footprint is the dependent variable. In the environmental Kuznets curve hypothesis, an inverted U-shaped relationship was determined. That is, the results confirming the existence of the environmental Kuznets curve have been determined. Finally, bidirectional causal links between carbon emissions and economic growth, between carbon dioxide emissions and the square of economic growth, and between carbon dioxide emissions and electricity consumption; It is observed between the ecological footprint and economic growth, between the ecological footprint and the square of economic growth, and between the ecological footprint and electricity consumption. It is expected that this article will make a significant contribution to the literature with the important results obtained by using both an ecological footprint and carbon dioxide emission as dependent variables. Novelty: In this study, unlike other studies, two models were created with both CO2 emissions and the ecological footprint data as environmental variables.

The roles of energy, natural resources, agriculture and regional integration on CO2 emissions in selected countries of ASEAN: does political constraint matter?

This paper empirically examines the effects of energy, natural resources, agriculture, political constraint and regional integration on CO2 emissions in four ASEAN (Association of Southeast Asian Nations) countries of Cambodia, Malaysia, Indonesia and Thailand. We distinguish between renewable and fossil fuel energy consumption to see their individual impacts on CO2 emissions. The study employed a panel data from 1990 to 2019 derived from sources such as World Development Indicators, which were then analysed using Common-Correlated Effect Mean Group (CCEMG) and Augmented Mean Group (AMG) estimates. The findings show that renewable energy consumption has a negative impact on CO2 emissions while fossil fuel energy degrades the environment. The role of natural resources was found to be favourable for environmental quality with the impact of agriculture being found to be detrimental. For regional trade integration, its influence was not significant enough to offset CO2 emission. Furthermore, we discovered that political constraint induces CO2 emission. Based on the result, it is recommended that the selected ASEAN countries promote the use of renewable energy and clean technologies in their manufacturing processes, conserve natural resources, adopt eco-friendly political policies and intensify regional integration to accelerate the achievement of the SDGs.