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The impact of economic growth and energy use is still controversial regarding sustainability, and researchers have limited consensus in this regard. Electricity is considered more environmentally friendly compared with direct fossil fuel consumption. However, many developed economies still depend on fossil fuel sources for electricity generation. Therefore, this study attempted to verify the relationship between electricity consumption and carbon emissions in developed economies in the Group of Twenty (G20). Economic growth and foreign direct investment are other important variables for analyzing this relationship. For this purpose, a dataset from 1995–2018 was generated. The study used econometric methods including cross-sectional dependence, cointegration, Fully Modified Ordinary Least Square (FMOLS), Dynamic Ordinary Least Square (DOLS) estimators, and the Pair-wise panel Granger causality test to examine the relationship between dependent and independent variables. The findings show a positive relationship between electricity consumption and CO2 emissions. This indicates that electricity production is still dependent on sources that help increase CO2 emissions in G20 countries. Furthermore, the results show that gross domestic product and its square term confirm the Environmental Kuznets Curve (EKC) theory for these economies. These results suggest that policymakers promote green and clean electricity sources for sustainable economic growth.

Addressing the conflict between fossil fuel exploitation, usage, and greenhouse gas emissions is a top priority for China’s low-carbon socioeconomic development. Scalable Axisymmetric Matrix “a computerized general equilibrium model” is used to assess the impact of carbon tax policies on energy usage, carbon pollution, and macroeconomic drivers at reduction levels of 10%, 20%, and 30% of emissions. In the meantime, we examine the impact of various carbon tax recycling schemes in line with the tax neutrality concept. Although the carbon tax successfully reduces carbon emissions, we conclude that it will have a detrimental effect on the economy and social well-being. To cope with China’s increasing pollution emissions and ecological imbalances, the Chinese government promulgated the environmental protection tax law of the people’s Republic of China, which was officially implemented in 2018. Although carbon dioxide is not included in the Taxable Pollutants and Single Quantity Table attached to this law, China has almost reached a consensus on taxing carbon emissions. In 2021, the State Council of China issued the opinions on completely, accurately, and comprehensively implementing the new development concept and doing a good job in carbon peak and carbon neutralization, which made a comprehensive deployment to achieve the “double carbon” goal and improved the carbon tax policy and legal system, which is an essential part of it. Therefore, based on fiscal neutrality, an effective carbon tax recycling scheme can mitigate the adverse effects of its adoption. However, due to the current development in China’s energy-generating and transportation sectors, even minor steps can have huge effects on emissions with marginal economic implications.

This study conceptualizes the impact of Green Economy Policies, namely, green fiscal policy, green investment, and green jobs, on sustainable economic development through direct and serially mediated paths. Ecopreneurship and Green Technological Innovation have been perceived/recognized as potential mediators linking green economy policies to sustainable economic development. The conceptual model sheds light on the integrated role of two main actors—the government of the state and its market forces in moving toward the goal of sustainability and gains for all. It represents that incorporating “green” into public policy creates a suitable environment for green entrepreneurs to propose innovative green technologies and sustainability-led business models. Theoretically supported by Institutional theory, this article aims to contribute to sustainability transition research by focusing on the collective role of different institutional forces in achieving economic gains through a sustainability lens.

A range of studies have been observed, covering the title of climate change and its linkage with the agriculture sector. This would justify the claim that changing environment has its several outcomes for which the agriculture sector cannot be ignored. The purpose of this study is to investigate the impact of various climate change dynamics and modelling on the four indicators of agriculture sector. Overall, five panel economies were selected having highest level of agriculture output in the world economy. The time duration of the study was during 1990–2018 with yearly data as collected from world development indicator or WDI. The study analysis was conducted while applying four panel regression models like ordinary least square, fixed effect estimator, least square dummy variable, and finally the random effect. For better understanding, study findings are empirically explained. The results confirm that both positive and negative impact of various proxies of climate change on agriculture dimension of selected economies. More specifically, it is observed that higher climate change in the form of carbon emission from different sources are causing a downturn effect on the agriculture export while at the same time, they are causing an up-ward shift in the agriculture import of selected economies. Besides, study has reasonably disrobed various policy implications both in theoretical and practical perspective. However, some limitations are also under observation. Firstly, this study considers the limited number of explanatory variables for reflecting the changing climate trends among top five agriculture economies of the world. However, there are still range of other factors which can be observed in the future studies to examine their influence on the selected indicators of agriculture industry. Secondly, this study has applied traditional panel models where no implication is observed for the dynamic panel methods like Generalized methods of Moments or GMM. Thirdly, this study has not provided any evidence for the cross-country analysis. Fourthly, this study has limited time span along with missing examination of both short run and long as well. Future studies may address these limitations for better implication in both theoretical and practical perspective.

Travel and tourism have glimpsed a significant and promising implication for economic development. Despite the commendatory implication of tourism, it levies a stringent environmental cost such as environmental degeneration. Hence, this study will incorporate the 18 countries out of the top 20 travel and tourism contributors to economic growth to assess the progressive correlation between tourist arrival, economic growth, energy consumption, and oil consumption on carbon emission by applying panel ARDL spanning from 1995 to 2019. The outcome of the panel ARDL reveals that both periods have witnessed that the endogenous variables have a substantial and positive impact on environmental degradation except for tourism as it indicates −0.22 and −0.48% in the long and short run, having a rate of adjustment as −0.52 toward the equilibrium. The simultaneous quantile regression reveals that in the 50 and 75 percentiles, the effect of tourism has a negative impact, which contradicts the PMG findings. These determinations suggest that the policymakers look for more manageable and environmentally sound tourism and economic growth procedures to safeguard the sustainable environment in the studied countries.

The present study examines the potential of the traditional environmental Kuznets curve (EKC) with an extension for growing industrialized economies, including Brazil, China, India, Indonesia, Russia, Mexico and Turkey (E-7 economies) spanning from 1995 to 2019. Since the E-7 economies are still in a growing phase, this study adds to the EKC phenomenon by taking into description human development, the use of renewable energy, and technological innovations for investigation. Second-generational panel econometrics techniques, such as cross-sectional augmented autoregressive distributive lag (CS-ARDL), Augmented Mean Group (AMG), and Dumitrescu-Hurlin causality tests, form the basis of the experimental framework’s design. The study confirms the existence of the EKC phenomena in E-7 economies, where income expansion is prioritized in relation to environmental sustainability. The study’s findings demonstrate that technological modernization helps to mitigate pollution level. Therefore, human development, technological innovation, and the use of renewable energy are held up as the panacea for reducing carbon emissions over the time period under study. Finally, some further policy suggestions are provided.

Local government innovation support (LGIS) is an exogenous pulling force for high-quality economic development. Accurately identifying the mechanism by which LGIS affects green development remains practically and theoretically significant for building a long-term framework for driving green development. Based on provincial panel data (2010–2019), this paper uses the Super-SBM model to measure the green development efficiency (GDE) of different provinces in China. A dynamic panel GMM model is constructed to evaluate the significant relationship between LGIS and GDE and to explore the potential impact mechanism of other key factors such as fixed asset investment (FAI), environmental regulation (ER), industrial structure (IS), and foreign direct investment (FDI) on GDE. The estimation showed that LGIS had a positive impact on GDE. The data analysis indicated that GDE in the lag period significantly affected the GDE in the current period. More so, as per the results, the promoting effect of GDE in the second lag period gradually weakened due to the decline of LGIS and ER restrictions. The current model also revealed that FAI and ER inhibited the GDE progress, while IS and FAI had improved the state of GDE in the region. The research findings imply that China should further increase the government innovation expenditure, FDI utilization, and IS upgrade to promote high-quality economic development.

The rapid development of e-commerce in China in recent years has transformed China’s economic and social production landscape as well as people’s lifestyles. In addition, it has an increasing impact on China’s energy consumption. Based on Melitz [Econometrica, 2003, 71 (6), 1695–1725], this paper introduces the energy efficiency parameters to propose a theoretical analysis model, and performs theoretical and empirical analysis of the impact of e-commerce on China’s energy consumption using panel data at the provincial level in China. This paper suggests that the development of e-commerce can significantly enhance China’s energy output efficiency, reduce energy consumption per unit of GDP, and curb the excessive growth of total energy consumption. Meanwhile, increased investment in energy conservation, technological progress, and optimized energy consumption structure can also help decrease China’s energy consumption per unit of GDP, thus decreasing environmental pollution. Finally, this paper proposes policy suggestions to lower energy consumption per unit of GDP and control the excessive growth of China’s total energy consumption. Compared with existing studies, the main contributions of this paper are as follows. First, because there are only a few studies on e-commerce and energy consumption, this paper further supplements and enriches relevant literature. Second, this paper proposes a theoretical model regarding the impact of e-commerce development on energy consumption, adding a new perspective to research. Third, there is a lack of adequate studies on the development of China’s e-commerce landscape. While using China’s e-commerce development index data at the provincial level, this paper sets up a panel data regression model and performs in-depth analysis of the impact of e-commerce development on China’s energy consumption.