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In this paper, the panel data of 30 provinces in China from 2011 to 2019 are analyzed by the spatial measure model and the threshold regression model. The results show that the air quality level is positively correlated with green finance, but there is no spatial effect. The spatial effect of the three influencing factors, including the degree of openness, the level of infrastructure, and the level of education, is the crowding-out effect. At the same time, variables such as human resource level, air quality, and infrastructure construction level all have threshold effects in the relationship between green finance and economic development. The research conclusions suggested that local governments at all levels should formulate policies according to the actual situation to promote the development of provinces' intensive, intelligent, and green development, and build a regionally-linked green finance development model, thereby promoting the improvement of green finance. [ABSTRACT FROM AUTHOR]

Global warming has emerged as a serious threat to humans and sustainable development. China is under increasing pressure to curb its carbon emissions as the world's largest emitter of carbon dioxide. By combining the Tapio decoupling model and the environmental Kuznets curve (EKC) framework, this paper explores the relationship between China's carbon emissions and economic growth. Based on panel data of 29 provinces from 2007 to 2016, this paper quantitatively estimates the nexus of carbon emissions and economic development for the whole nation and the decoupling status of individual provinces. There is empirical evidence for the conventional EKC hypothesis, showing that the relationship between carbon emissions and per capita gross domestic product (GDP) is an inverted U shape and that the inflection point will not be attained soon. Moreover, following the estimation results of the Tapio decoupling model, there were significant differences between individual provinces in decoupling status. As a result, differentiated and targeted environmental regulations and policies regarding energy consumption and carbon emissions should be reasonably formulated for different provinces and regions based on the corresponding level of economic development and decoupling status. [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]