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As China reaffirms its commitments to limit the climate change risk and improve air quality, a combination of new policy and technology opportunities is presenting itself. A national emission trading scheme (ETS) begun in 2017 and is showing great promise, creating decentralized incentives for cost effective pollution mitigation. At the same time, sustained energy sector innovation is driving the costs of renewable electric power generation below those of fossil fuel substitutes. Early economic evidence of ETS measured pollution reductions, but has not addressed important economy-wide net benefits. This paper focuses on technology and energy cost savings and is the first to account for three multiplier effects—shifting consumption patterns, job growth, and the benefits of induced productivity growth—that would result from accelerated renewable electricity deployment in China. Results from a dynamic recursive computable general equilibrium model for 2017 to 2030 show that expanding renewable deployment can interact with the ETS to slash GHG emissions, as well as energy costs, stimulating significant long-term economic growth. These results suggest that China should accelerate its clean energy transition, not only for the air-quality and climate benefits, but to fulfill the energy sector's potential to promote innovation, employment, and economic growth. [ABSTRACT FROM AUTHOR]

The rapid development of digital finance has delivered significant benefits, such as sustainable development and economic growth. We explore the relationship between digital finance and green total factor energy efficiency (GTFEE) for the first time, filling a gap in the existing literature. This paper uses dynamic panel models to explore digital finance's impact on GTFEE at the Chinese city-level panel data from 2011 to 2018. The results show that digital finance can significantly improve urban GTFEE, and the findings remain robust with various tests. Second, the mechanism analysis indicates that digital finance can improve GTFEE by promoting urban green technology innovation and industrial structure upgrading. Further study shows that digital finance has a better effect on the improvement of GTFEE in central and western cities, small cities and non-resource-based cities, but has no significant or small impact on GTFEE in eastern cities, large cities and resource-based cities, reflecting the inclusiveness of digital finance. [ABSTRACT FROM AUTHOR]

In the extant literature, there are numerous discussions on China's environmental sustainability. However, few scholars have considered renewable energy consumption and trade policy simultaneously to debate environmental sustainability. Therefore, this paper attempts to examine how renewable and non-renewable energy consumption, bio-capacity, economic growth, and trade policy dynamically affect the ecological footprint (a proxy for environmental sustainability). Using the data from 1971 to 2017 and employing the auto-regressive distributed lag model to perform an empirical analysis, the results demonstrate that renewable energy consumption and trade policy are conducive to environmental sustainability because of their negative impacts on the ecological footprint. However, the results also indicate that bio-capacity, non-renewable energy consumption, and economic growth are putting increasing pressure on environmental sustainability due to their positive impacts on the ecological footprint. Moreover, to determine the direction of causality between the highlighted variables, the Yoda-Yamamoto causality test was conducted. The results suggest a two-way causal relationship between renewable energy consumption and ecological footprint, non-renewable energy consumption and ecological footprint, and economic growth and ecological footprint. Conversely, the results also suggest a one-way causal relationship running from bio-capacity and trade policy to the ecological footprint. [ABSTRACT FROM AUTHOR]

Different regions in China have different energy consumption characteristics and changing trends. This paper focuses on analyzing trends in energy consumption changes along the timeline for 30 regions in China. Using the Hybrid Input-Output Model, this paper decomposes energy consumption in 30 regions in 2007, 2012 and 2016 into energy embedded of final consumption expenditure, gross capital formation, inflow and outflow. We use these four dimensions as coordinates to draw a regional radar map. According to the changing characteristics of the radar map, 30 regions are divided into three groups. By analyzing the reasons for the changes in three regions, we draw the following conclusions. For regions where energy consumption is mainly inflow, the economically developed regions have to form a low energy consumption environment while achieving economic growth. The economically underdeveloped regions need to carry out energy conservation and emission reduction as well as ensuring the level of economic development. For some outflow regions with moderately economic development, it is necessary to balance the economic development and energy consumption control according to regional characteristics. For resource-rich regions which are in the process of transformation from agriculture to industrialization, they have to maintain the rapid development speed and strengthen their infrastructure with less energy consumption of buildings. [ABSTRACT FROM AUTHOR]

Developing energy from renewable sources and modernizing the energy system are critical components of China's efforts to combat climate change. Policymakers and authorities have made significant attempts to bring them. However, one of the major impediments to China's energy revolution is financial limitations, which are inextricably linked to the country's economic growth. The present research paper intends to investigate the relationship between economic growth and sustainable financial development on the use of energy from renewable sources in both the short and long run in the context of China. To achieve this, the researchers have utilized the panel data consisting of 10 years from 2011 to 2020. When compared to cross-sectional and time-series data samples, the panel data model offers many benefits. For starters, the panel data includes information on the passage of time and the cross-sectional area. Another benefit of using panel-data models with a larger degree of freedom is that they provide more stable and reliable estimates across short periods across cross-sections. In the case of the short run, there is a positive relationship between economic and financial development and the use of energy from renewable sources in the context of all of China. While in the case of long-term effects, the results indicate the adverse impact of financial development on the use of energy from renewable sources in the western regions of China. These results were deduced using the causality test Granger proposed to determine the path of the causal relationship and the direction of the relationship between the variables. These results indicated that the relationship between economic and financial development in east China was unidirectional, and the nature of the underlying relationship was causal. Meanwhile, in east and west China, economic development in China as a whole has been unidirectionally increasing energy from renewable sources. Our empirical findings suggest many strategies for promoting the growth of energy from renewable sources. [ABSTRACT FROM AUTHOR]

The present research aims to conduct a systemic review on Renewable Energy, Economic Growth and Economic Development and look for links between the papers published between 2008 and May 2021. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, it was possible to reach a sample of 111 articles selected by Web of Science and a sample of 199 academic articles selected by Scopus in that specific period. The analysis of the group of Renewable and Non-renewable Energy Consumption, Economic Growth and Economic Development shows that most of the articles published in this subsample use the quantitative methodology in economic sciences. The results indicate that research on the subject has a growing trend and that most of the articles are post-2015 publications. In addition, China has been the leading nation in published works. The journal Renewable and Sustainable Energy Reviews is considered the most relevant in this category, and Sustainability has the most publications. Finally, a research gap was identified to be explored, lacking studies aimed at understanding the consumption of renewable energies and economic development and studies that focus on renewable energies and economic growth in less developed economies. [ABSTRACT FROM AUTHOR]

Energy consumption is of great significance to the sustainable development of the economy. Due to the spatial heterogeneity of low-carbon growth in regional economies, the relationship between energy consumption and economic growth is complicated. However, a few researches have been published about spatial spillover effects and non-linearity of energy consumption and financial development on regional economic growth in China. Based on the panel data of 30 provinces in China from 2007 to 2017, this paper analyzes the spatial spillover effects and threshold effects of energy consumption and financial development on regional economic growth by using spatial and nonlinear econometric methods. The main conclusions are as follows. Spatial econometric methods show that financial development and energy consumption are two factors of production input to promote China's economic growth. Meanwhile, energy consumption and financial development have spillover effects on regional economic growth. Additionally, the nonlinear econometric method finds that with increasing financial development, the impact of energy consumption on economic growth is segmented. Therefore, relevant policies should be implemented to enhance the role of finance in energy consumption to promote low-carbon growth of China's economy. [ABSTRACT FROM AUTHOR]

The empirical conclusions regarding the relationship between energy price and energy efficiency are relatively mixed. This paper systematically examines the influence of energy price on energy efficiency in China based on data from 30 provinces between 2003 and 2017, using linear and nonlinear effect analysis. We found that the impact of energy price on energy efficiency in China was positive in general. However, there existed heterogeneous effects of energy price on energy efficiency in various regions, and the effect differed with differences in energy efficiency levels based on the panel quantile regression analysis. Finally, the nonlinear effect analysis based on the panel threshold model indicated that the effect of energy price on energy efficiency increased with the rise of the environmental regulation level and economic growth rate, while it decreased with the ascent of the degree of energy price distortion and economic development level. In particular, when the value of a region's economic development level and economic growth rate was within a certain range, the impact was not statistically significant. Overall, these findings contribute to a deeper understanding regarding the effect of energy price on energy efficiency in China. [ABSTRACT FROM AUTHOR]