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To reflect the trend of electricity consumption (EC) in China's Pearl River Delta (PRD) under a balanced environment and economy, this paper proposes an EC forecasting framework from the perspective of optimal economic growth. The historical GDP statistics of the PRD are calibrated with data from the new "NPP-VIIRS-like" nighttime light dataset from 2000 to 2020, and two simulation scenarios of optimal economic growth are constructed according to the carbon emission reduction rate. Finally, based on the electricity data from 2000 to 2017, an error correction model is constructed to predict and compare the trend of EC in the PRD under different carbon emission scenarios. The results demonstrate the following. (1) The economic growth path under low-carbon constraints is more closely aligned with the actual economic development of the PRD. (2) The electricity demand required to sustain optimal economic growth in the PRD under low-carbon constraints is projected to reach saturation around 2037, approximately a decade earlier than the scenario without carbon constraints. The results of the projections are expected to guide future work on power system planning and economic development assessment in the context of carbon reduction. • The balance between environmental resources and economic development is considered. • The optimal economic growth path under the low-carbon goal is measured. • Calibration of regional statistics with the nighttime light dataset "NPP-VIIRS-like". • The error correction model is built as a short-term regulation mechanism for power prediction. • Predicted electricity demand for optimal economic growth in the PRD under different scenarios. [ABSTRACT FROM AUTHOR]

As the largest carbon emission emitter, China has made a commitment to the international community to achieve carbon neutrality before 2060. While most literature suggests such a goal could be achieved mainly through slowing down economic growth, promoting energy transformation, and adjusting the industrial structure, little is known about how improving the economic development quality would have an impact on China's carbon emissions and achieving carbon neutrality goal. Here based on the environmental Kuznets curve model and scenario analysis, we explored future courses of carbon neutrality, in terms of CO 2 emissions, in China under different scenarios of economic development quality. Results suggest that under the conventional, accelerated, and enhanced improvement scenarios, China could reach a carbon peak in 2027, 2026, and 2025 (3.5075, 3.5074, and 3.5066 billion tonnes, respectively), and then achieve the zero carbon emission goal in 2050, 2044 and 2040, respectively. However, achieving such an ambitious trajectory is contingent upon significant improvements in the economic development quality that China should focus on at present and in the future. • We aimed to study when China can reach carbon neutrality in terms of CO 2. • The economic development quality would have great impacts on achieving China's carbon neutrality goal. • The Environmental Kuznets Curve model and scenario analysis were adopted. • China can reach carbon neutrality before 2050 through improving economic development quality. [ABSTRACT FROM AUTHOR]

Green economic growth and sustainable development complement each other, promoting green economic growth has important practical significance. However, the existing research focuses on qualitative analysis and less on quantitative analysis of the green economic growth. This study constructs a comprehensive index system of green economy, and uses entropy weighted TOPSIS method to evaluate the green economic growth from 2000 to 2017 in China. This study shows that:(1) Since the 21st century, China's green economy has been constantly improved. Ecological civilization and social progress are the main support for green economic growth. Economic development is secondary, and innovation-driven is lagging behind. (2) There are obvious regional differences in green economic growth. The eastern region is obviously better than the central and western regions, but the overall regional differences are shrinking. At the same time, the green economic growth shows obvious spatial agglomeration effect. (3) Population size, economic development level, technological innovation, industrial structure, urbanization, environmental regulation and FDI have impacts on the green economic growth, but the spatial effect of each influencing factor is different. In the process of developing the green economy, policy-makers should fully combine the spatiotemporal evolution of the green economy and its influencing factors, and make targeted policies. • This paper measures China's green economic growth. • Entropy weighted TOPSIS framework is employed. • China has made great progress in green economic growth. • China's green economic growth has obvious regional heterogeneity. • China's green economic growth has a spatial effect. [ABSTRACT FROM AUTHOR]

Climate change, the imbalance between China's domestic energy supply and demand, and the success of the shale gas revolution in the United States have been the main motivators for China to actively issue shale gas development policies and explore its own path on this industry. This paper estimates three indicators of economic development: regional GDP, employment level, and the housing price index by using data from China's largest shale gas region, the Fuling District in Chongqing (a municipality in China). The analysis uses a Synthetic Control Method (SCM) model based on data from Fuling itself and other 34 counties of the Chongqing municipality over the period from 2005 to 2018. The results demonstrate that shale gas development has a significant positive effect on both regional GDP and employment level, with average impact growth rates respectively of 9.8% and 12.0%. By contrast, we find an insignificant effect of shale gas development on housing prices. These results support the case for further development of shale gas in China. Note that in some areas our results differ from existing literature, providing a reference for further research in this area. • We estimate the effect of shale gas development on the regional economy in China. • We apply the Synthetic Control Method for model identification. • We find a positive effect of shale gas development on regional GDP and employment. [ABSTRACT FROM AUTHOR]

This study explored the relationship between renewable energy consumption and economic growth from new risk-based perspectives, including political risks, financial risks, economic risks and composite risks. The study uses a panel threshold model to empirically analyze panel data for the Organization for Economic Cooperation and Development (OECD) countries from 1997 to 2015. The results show when composite risks and political risks are used as threshold variables, there is a single threshold between renewable energy consumption and economic growth. When that threshold is exceeded, the positive effect of renewable energy on economic development increases. When economic risks and financial risks are used as threshold variables, there is a double threshold between renewable energy consumption and economic growth. When the first threshold value is exceeded, but not the second, renewable energy positively impacts economic development. However, when economic risk and financial risk do not lie between the two threshold values, there is an insignificant negative correlation between renewable energy consumption and economic growth. [Display omitted] • This paper explores the impact of country risks on renewable energy consumption and economic growth. • At different risk levels, the impact of renewable energy consumption on economic development is different. • When the composite risk and political risk crosses the threshold, the positive effect is significantly enhanced. • Effect is positive only if economic risks and financial risks crosses the first threshold but not crosses the second. [ABSTRACT FROM AUTHOR]

Our work provides a comprehensive investigation of the coupling between the efficiency of economic growth and the efficiency of carbon emissions reduction in China, and makes a distinction between the coupling over the long-run and the short-run. Our estimates suggested significant evidence of coupling between economic growth and efficiency in carbon emissions reduction in the long-run, but China's economic growth still increased carbon emissions at the aggregate level. In the short-run, coupling effects were different across provinces that were at different stages of economic development. Provinces with low- and high-stages of development saw positive short-run coupling, but provinces at the intermediate stage of development saw the contrary, which resulted in an obvious "U" shaped relationship between short-run coupling effects and real GDP per capita. Finally, our findings provide an economic rationale for differentiated low-carbon policies. • Coupling Economic Growth with Carbon Emissions Reduction at the Efficiency Level. • Making a distinction between the coupling in the long-run and that in the short-run. • Over the period 1997–2017, we saw evidence of the long-run coupling. • The Short-run coupling varies across different provinces. [ABSTRACT FROM AUTHOR]

Solving the resource and environmental constraints faced by China benefits from studies on the decoupling relationship between the power industry's CO 2 emissions and economic development. This study provides new ideas for economic development by measuring the decoupling index of CO 2 emissions within the power industry from 1985 to 2017 based on the Tapio decoupling model. Next, this study determines the key influencing factors of the decoupling index in the long- and short-term based on the autoregressive distributed lag model. The results show that: (1) In the past 30 years, the relationship between CO 2 emissions and economic development has exhibited synchronization within the power industry; the base for the decoupling state is expansive negative decoupling and weak decoupling, and the strong decoupling state has existed for only five years. (2) The estimation results for the long-term effect indicate that coal-fired power generation efficiency and terminal energy intensity can effectively reduce the decoupling index with a coefficient of 3.0422 and 2.4822, respectively. (3) The estimation results for the short-term effect imply that decreasing terminal energy intensity reduces the decoupling index the most followed by energy consumption, and the two show coefficients of 9.5986 and 2.6404, respectively. Based on this conclusion, the study provides some recommendations for policy design, collaborative emissions reduction, and low-carbon energy construction in China's power industry. ● Interaction between CO 2 emissions in power industry and economic growth in China. ● Topia decomposition analysis, ARDL, and ECM are employed. ● Decoupling consist of expansive negative decoupling and weak decoupling. ● Strong decoupling only exists for 5 years. ● The key influencing factors of the decoupling index in the long-term and short-term is distinguished. [ABSTRACT FROM AUTHOR]

What impact will increasing renewable energy consumption have on economic growth? What is the direction or magnitude of the impact and the determinants behind it? Existing research on the relationship between renewable energy and economic growth focuses on the linear relationship, whereas ignoring the non-linear relationship between them. In this study, the nonlinear relationship between renewable energy and economic growth in OECD countries was investigated by developing panel threshold regression models. Non-renewable energy intensity, urbanization level and per capita income are used as threshold variables to explore the internal mechanism of renewable energy for economic development. Three panel threshold models are developed based on these three threshold variables. The results show that the effect of renewable energy consumption on economic growth is positive, which indicates that increased renewable energy consumpiotn contributes to economic growth. In addition, this positive relationship changes as the threshold value changes, which means that the role of increasing renewable energy consumption to promote economic development is nonlinear. In other words, if the EU countries increase their renewable energy consumption by more than a certain amount (threshold value), the role of renewable energy consumption in promoting economic development is more significant. • Analyzing renewable energy and economic in OECD countries. • The fixed-effect model and non-linear threshold model are employed. • Three factors were used as threshold variables to explore the mechanism. • Renewable energy has a threshold effect on economic growth. [ABSTRACT FROM AUTHOR]