Green finance development is a comprehensive system with three aspects interacted: economic, environmental, and financial activities. Based on its internal mechanism, this paper constructs an evaluation system of green finance development, which fills the absence of existing studies on green finance development. The internal development of green finance is transformed into three subsystems by PSR (Pressure-State-Response) model, and the evaluation scores are calculated by the entropy weight method. As the applications of the evaluation system, the horizontal comparison and vertical trend of green finance development in different regions of China from 2004 to 2017 are analyzed, and the relationship between green finance and sustainable energy development can also be quantitatively analyzed. The results show that sustainable energy development can be promoted through the development of green finance, using various measures in dimensions of economic development, financial development, and environmental development.

Finance contributes to poverty alleviation through economic growth, and the development of green finance is related to the sustainable development of the world economy and environment. Green finance not only helps promote sustainable economic development but also helps reduce poverty. Based on the analysis of related theories about green finance and poverty alleviation, this paper selects 18 indicators from three dimensions of economic development, financial development, and social environmental development and uses the improved entropy method to measure the green finance development index of China’s 25 provinces and municipalities from 2004 to 2017. The results show that the development level of green finance in China’s 25 provinces and municipalities is quite different. On the basis of the above analysis, make an empirical analysis of the impact of the green finance development index on poverty alleviation using multiple regression analysis and static panel and dynamic panel estimation methods. The research results show that there is a significant positive correlation between green finance and poverty alleviation; the higher the level of green finance development, the more conducive the poverty alleviation. So, this paper suggests that poverty can be better alleviated by improving the level of green finance development, financial asset level, and economic development level.

This paper studies the impact of the development of green finance on China’s energy consumption structure. 17 basic indexes and the improved entropy weight method are used to construct the green finance index (GFI). Multiple regression, panel regression, and spatial regression are used to study the impact of green finance on China’s traditional energy and renewable energy consumption. The results show that there is a positive spatial spillover effect in the development of green finance among provinces in China. The development of green finance contributes to the conversion of traditional to renewable energy consumption. The effect of green finance on the transformation of energy consumption structure is mainly reflected in the direct effect. The green finance in each province not only helps the local development of green energy but also plays a good role in the production and utilization of clean energy consumption in surrounding provinces. Therefore, the government should support the green finance, reduce traditional energy consumption, and increase renewable energy consumption.

Based on the calculation of the inclusive financial development level of 22 provinces and 4 municipalities in China from 2004 to 2017, this paper uses the Kernel density estimation method to further analyze the evolution of the inclusive financial index. Based on the above analysis, we make empirical analysis of the impact of China's inclusive financial inclusion development index on farmers' entrepreneurship using static panel and dynamic panel estimation method. The empirical conclusions show that there are certain differences in inclusive financial inclusion development level in various provinces in China. Improving the inclusion development level of inclusive finance can better promote farmers' entrepreneurship. Urbanization level, economic openness and regional economic development level have a significant positive effect on farmers' entrepreneurship, while farmers' income and education level have a significant negative effect on farmers' entrepreneurship. It is possible to promote farmers' entrepreneurship by improving the inclusive development level of inclusive finance, combining urbanization, increasing government investment in productive fixed assets, increasing economic openness and improving regional economic development.

Utilizing provincial panel data from China spanning 2000 to 2020, this study constructed an indicator system for high-quality economic development by incorporating 35 indicators. These indicators stem from five domains: innovative, coordinated, green, open, and shared development. To assess carbon finance development, an evaluation system was created using twelve basic indicators derived from three categories: financial environment, energy efficiency, and scientific and technological progression. The entropy weight method facilitated the computation of indices such as the economic quality development, innovative development, coordinated development, green development, open development, shared development, and carbon finance development indices. Both static and dynamic panel models served to empirically ascertain the specific influence of carbon finance on high-quality economic development. Additionally, regional and temporal variances in carbon finance's impact on high-quality economic development were scrutinized. Findings indicate that provinces like Beijing, Shanghai, Jiangsu, and Guangdong, known for advanced economic development, exhibit elevated levels of high-quality economic and carbon finance development. Nonetheless, disparities among provinces are evident. While carbon finance significantly bolsters China's high-quality economic growth, its influence is not uniformly observed across all five development domains. It primarily augments coordinated, green, and shared development. Furthermore, the role of carbon finance in boosting China's high-quality economic development exhibits regional and temporal variations. The promotion of high-quality economic growth can be achieved by fostering an amenable carbon finance environment, addressing aging, maximizing governmental influence, enhancing transportation infrastructure, propelling new urbanization, and refining education standards.

The digital economy, as a new economic form with high information density, provides a new driving force for the realization of high-quality agricultural development. Panel data of 31 provinces in China from 2011 to 2020 were selected for analysis. The static panel data interaction effect model and panel threshold model were used to verify the nonlinear influence mechanism and heterogeneity of financial development in the process of the digital economy affecting high-quality agricultural development. The findings are as follows. (1) During the study period, the high-quality development of China’s agriculture showed a steady upward trend; however, the regional differences were significant, and the eastern part was larger than the central and western part. (2) The digital economy can promote high-quality agricultural development. (3) The digital economy has a double threshold effect in the process of affecting high-quality agricultural development, which depends on the level of financial development. When the threshold is exceeded, the digital economy has a more significant promoting effect on high-quality agricultural development. (4) The impact of the digital economy on high-quality agricultural development is heterogeneous. From the perspective of different regions, the impact effect is greatest in the eastern region, while the effect is smaller in the central and western regions. From different resource endowments, the positive impact effect is greatest in the major grain-selling areas, followed by the major grain producing areas, but the positive digital economy driving effect is not significant in the balance of production and sales areas. Finally, three policy suggestions are proposed. First, the Chinese government should increase investments in and support for digital technology to promote the integration of the digital economy and agriculture. Second, the Chinese government should promote the development of digital inclusive finance in areas with financial development below the threshold. Third, different regions should implement differentiated digital economies to promote high-quality agricultural development.