CO₂ emissions in G20 economies: A dynamic panel analysis of economic and energy-sector drivers

The problem of climate change, which causes various negativities in the global sense, is one of the important research topics. It is necessary to determine the factors affecting carbon dioxide (CO2) emissions, which are the main determinants of climate change, and to take measures for this. In this study, based on the hypothesis that economic growth, energy usage, trade openness, and foreign direct investment affect CO2 emissions, it was aimed to examine the effects of economic growth, energy usage, trade openness, and foreign direct investment on CO2 emissions for G8 countries using annual data for the period 1990-2018. For this purpose, first, a literature review was done in the study. Then, cross-section dependency and heterogeneity tests were performed as empirical analyses. Afterward, unit root tests, cointegration analyses, and causality analyses were performed in the study. Finally, in the study, short-term parameters and long-term parameters were estimated to capture possible dynamic relationships between variables. The Westerlund Error Correction Model (ECM) panel test for cointegration showed that there is a cointegration relationship between these variables for both the entire panel and the cross-section units. The results of the Augmented Mean Group (AMG) estimator method showed that (i) economic growth has no effect on CO2 emissions in 7 of 8 countries, (ii) energy usage increases CO2 emissions in 4 of the countries studied but decreases it in one of them, and (iii) foreign direct investments and trade openness do not affect CO2 emissions in 4 countries but positively affects in 2 countries and negatively in 2 countries. According to the results obtained from the Pooled Mean Group (PMG) analysis, while economic growth, energy usage, and trade openness affect CO2 emissions in the long run, economic growth, energy use, and trade openness affect CO2 emissions in the short run too. According to Dumitrescu-Hurlin panel causality results, it was seen that there is no causal relationship between CO2 emissions, economic growth, and energy use. While there is a unidirectional causality from CO2 emissions to foreign direct investments, it was determined that there is a bidirectional causality between trade openness and CO2 emissions. When the results were examined in general, it was understood that the variables of economic growth, trade openness, foreign direct investment, and energy usage are effective on CO2 emissions in the G8 countries. It would be beneficial for countries to include the objectives of making production with clean production technologies, ensuring efficient use of energy, and expanding the use of renewable energies among their main targets.

Impact of heat and electricity consumption on energy intensity: A panel data analysis

In the modern era, CO2 emissions is a popular and significant study topic. Environmental sustainability is adversely affected by CO2 emissions, which have become the main cause of climate change. Using panel data analysis, this study investigated the connections between CO2 emissions and economic development, capital accumulation, and the use of renewable energy. Long-term connections between variables were examined using the Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) estimators, taking into account heterogeneity and cross-sectional dependence. Additionally, the Dumitrescu–Hurlin Panel Granger Causality Test was used to assess dynamic interactions between variables. Although CH4 emissions increase CO2 emissions, the effects of economic growth and capital accumulation are not statistically significant, as determined using the AMG and CCEMG. Although the use of renewable energy was shown to have the potential to lower CO2 emissions, this impact was not statistically significant. The results of the dynamic panel demonstrate that CO2 emissions increase with capital accumulation. Although methane (CH4) emissions significantly impact CO2 emissions, economic growth, capital accumulation, and renewable energy use do not show statistically significant effects, highlighting the varying influences of these factors across nations. The findings of this study emphasize the need to integrate environmental regulations into capital investment strategies and adopt country-specific policies to effectively reduce CO2 emissions. They also underscore the need to customize green legislation to the specific conditions of each nation while simultaneously advocating for further expenditures in clean energy and the formulation of policies to supplant fossil fuels.

In this study, we examine the long-run effect of environmental-related technological innovation, institutional quality, trade openness, energy consumption, and economic growth on CO2 emissions in APEC countries from 2004 to 2018. Firstly, panel unit root tests were used to explore the stationarity of each data series. The panel unit root test findings showed that all data series are stationary at the first difference. Second, the Westerlund panel cointegration test was used to deal with heterogeneity and cross-sectional dependence. Thirdly, the empirical findings from the augmented mean group (AMG) and common correlated effects mean group (CCEMG) estimators indicate that environmental-related technological innovation and institutional quality destructively affect CO2 emissions. In contrast, trade openness, energy consumption, and economic growth positively impact CO2 emissions. While causality analysis refers to the unidirectional causality runs from trade openness, energy consumption to CO2 emission and bidirectional causality relationships are between technological innovation, institutional quality, GDP, CO2 emission. Based on the findings, we proposed that APEC countries should raise investment in environmental-related technological innovation and improve the quality of the institutional environment to achieve sustainable development targets.

In this study, the effect of real exchange rate on bilateral trade balance between Turkey and its 25 main trade partners is investigated for the period of 1996-2015 with heterogeneous panel data techniques. Trade balance model is estimated by using Mean Group (MG) estimator, which allows parameter heterogeneity, Common Correlated Effects Mean Group (CCEMG), and Augmented Mean Group (AMG) estimators, which both allow cross-section dependency and heterogeneity. Results indicate that the real exchange rate elasticity of the trade balance ranges between -0.40 and -0.45 and Marshall-Lerner (ML) condition is valid for Turkey. According to the results, the foreign income elasticity of trade balance ranges between 1.54 and 2.84, while for domestic income elasticity, it is found between -0.75 and -1.38. Country-specific results show that ML condition is valid for the USA, Belgium, Spain, Switzerland, Romania, and Russia at the bilateral level according to both CCEMG and AMG estimators.

This is the first attempt to explore linkages among industrialization, urbanization, energy consumption, CO2 emissions, and economic growth based on estimations in simultaneous equations framework. An economic growth model is extended to incorporate industrialization as shift factor and pollutant emissions as determinant of total factor productivity. A country panel of 30 Chinese provinces/cities and three regional panels, for periods 2000-2016, are estimated employing Augmented Mean Group (AMG) estimator as well as Common Correlated Effects Mean Group (CCEMG) estimator that are robust to both cross-sectional dependence and cointegration. The empirical findings are as follows: (i) the impact of urbanization on economic growth varied from negative to neutral to positive for western-, intermediate-, and eastern-economic zone, respectively, and is known as "urbanization ladder effect," (ii) moving from western to eastern economic zone, as regions develop, industry expansion has more powerful impact on economic growth, and thus, we define it as "industry expansion effect," (iii) industrialization promotes rapid urbanization in less developed and less employment saturated regions; hence, we name it as "employment saturation effect," (iv) economic growth in more developed regions pulled the CO2 emissions downward, while pushed it upward in case of less developed regions; therefore, we call it "growth pull/push effect," and (v) in bidirectional causality between energy consumption and economic growth, the "feedback effect" of economic growth remained dominant for all four panels. Based on empirical findings, policies are suggested for Chinese economy. Further, these policies have potential to extract implications for the rest of the world.

PurposeThis paper aims to examine the impact of information and telecommunication technologies (ICT-proxied by mobile phone subscription and Internet usage) on carbon dioxide (CO2) emissions in the Organization for Economic Cooperation and Development (OECD) countries from 1990 to 2018.Design/methodology/approachThe Cross-section Autoregressive Distributed Lag (CS-ARDL) model is employed to address the potential cross-section dependence problem. Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators are used to test for robustness of results.FindingsResults reveal contrasting effects of mobile phone subscription and Internet usage on CO2 emissions. While mobile phone penetration helps mitigate CO2 emissions, Internet usage tends to increase the emissions. Findings show that renewable energy is beneficial to the environment while economic growth is harmful to the environment. The effects of financial development and trade openness seem negligible.Practical implicationsThis study offers practical implications for policymakers. As different proxies of ICT could have contradictory impact on CO2, governments should be cautious against utilizing ICT to mitigate CO2. Findings point to the benefits of renewable energy in alleviating CO2 emissions. Therefore, governments are strongly advised to implement policies facilitating renewable energy consumption.Originality/valuePrevious studies ignored the problem of cross-section dependence which could lead to biased results and cause misleading inferences. This study aims to fill this void in the literature.

Discerning the role of renewable energy and energy efficiency in finding the path to cleaner consumption and production patterns: New insights from developing economies

The impact of green technological innovation and institutional quality on CO2 emissions in African countries

PurposeThe purpose of this study is to examine how renewable energy consumption moderates the relationship between inequality and carbon dioxide (CO2) emissions for Brazil, Russia, India, China and South Africa (BRICS). The nexus between energy use and geopolitical tensions has also been explored.Design/methodology/approachThis study has used distinctive data sets from 1990 to 2018 to explore the interconnections on emission, energy use, inequality and geopolitics. To do away with the difficulties related to heterogeneity and cross-sectional dependence (CD), this paper uses recent estimation methods that are robust to panel heterogeneity and CD.FindingsThe results of the panel augmented mean group (AMG) estimation and common correlated effects mean group (CCEMG) estimation verify the environmental Kuznets curve. The findings show that a 1% rise in Gini inequality leads to a 0.24% rise in the CO2 emission (AMG) method and a 0.17% rise in emissions CCEMG (method). As far as the moderating impact of renewable energy upon Gini measure of inequality is concerned, it is −0.10 AMG and CCEMG methods of estimation, respectively. However, the moderating impact of renewable energy on the geopolitical index leads to a mitigating impact on CO2 emissions, 0.55% decline in AMG method.Originality/valueThis research makes a distinctive contribution by investigating for the first time to the best of the authors’ knowledge the main pillars of sustainable ecological development in the context of the BRICS nations.

Rapid industrialization and economic growth in South Asia have intensified concerns about environmental sustainability, particularly regarding CO₂ emissions. This study examines the impact of hydropower energy (HPE), financing for clean energy (FCE), foreign direct investment (FDI), gross fixed capital formation (GFCF), and renewable energy consumption (REC) on CO₂ emissions and broader environmental sustainability indicators in South Asian countries from 2004 to 2022. To ensure robust analysis, panel unit root tests, including Phillips and Perron (PP), augmented Dickey–Fuller (ADF), and cross-sectionally augmented lm–Pesaran–Shin (CIPS), are applied to check stationarity, while the Westerlund cointegration test is employed to assess long-run relationships. The study utilizes the common correlated effects mean group (CCEMG) estimator as the primary regression technique, with augmented mean group (AMG) and mean group (MG) estimators for robustness. The findings reveal that REC significantly reduces CO₂ emissions, indicating its role in promoting environmental sustainability. However, HPE and FDI are positively associated with CO₂ emissions, suggesting potential inefficiencies in energy production and capital investment. Meanwhile, FCE and GFCF exhibit an insignificant relationship with CO₂ emissions. These results highlight the need for policymakers to optimize energy infrastructure, encourage sustainable investment practices, and integrate cleaner energy solutions to mitigate environmental degradation. The study provides valuable insights into the energy-emission nexus, offering a strategic direction for South Asia’s sustainability efforts.

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

The impact of natural resource depletion on energy use and CO2 emission in Belt & Road Initiative countries: A cross-country analysis

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.

Environment-economic growth nexus is one of the main concerns of the researchers in the modern era. Although there are several studies in this field, discussions are far from being reached a consensus. The main purpose of this study is to investigate the role of economic growth, renewable and non-renewable energy consumption, oil prices, and trade openness on CO2 emissions in 25 Organization for Economic Co-operation and Development (OECD) countries over the period 1990-2014. We provide a comparative panel data evidence using both the first- and second-generation estimation methods. The Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) estimations indicate that the Environmental Kuznets Curve (EKC) hypothesis is valid in OECD countries. However, the Augmented Mean Group (AMG) estimator revealed that the EKC hypothesis is invalid. The AMG estimator is a second-generation estimator and provides robust results under cross-sectional dependence compared to the first-generation methods; therefore, the EKC hypothesis is invalid. Our additional findings show that rising renewable energy consumption and oil prices mitigate CO2 emissions while non-renewable energy consumption increases it according to all estimators. No significant relationship is found between trade openness and CO2 emissions.