Abstract
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.
Highlights
With the rapid development of countries across the world, energy consumption has become the main driving force of economic development
Scholtens [4] studies the internal logic of economic sustainable development and ecological environment protection, proposing that green finance can effectively solve environmental pollution problems and make the economy develop continuously and efficiently through the innovation of various financial instruments, which is the best solution to solve environmental problems
We can see that the impact of financial development on energy consumption is not consistent and the impact of green finance on traditional and renewable energy consumption is scarcer. erefore, based on the current research situation, this paper studies the impact of green finance on energy consumption by constructing the green finance index (GFI) and carries out the research from an empirical point of view
Summary
With the rapid development of countries across the world, energy consumption has become the main driving force of economic development. More and more countries have begun to realize the importance of renewable energy and environmental protection. Rough financial services, green finance reduces the support for enterprises with high pollution and high energy consumption, encourages the development of environment-friendly enterprises, reduces the intensity of energy consumption, improves energy utilization, and optimizes the industrial structure of a nation, so as to realize the coordinated development of economic growth, green energy consumption, and environmental protection. It is of special significance to study the relationship between China’s green finance development level and energy consumption structure. Through the multiple regression model, panel regression model, and spatial Durbin model, this paper studies the impact of green finance development on traditional and renewable energy consumption. Through the multiple regression model, panel regression model, and spatial Durbin model, this paper studies the impact of green finance development on traditional and renewable energy consumption. e results show that the development level of green finance in China’s provinces is increasing yearly. ere are obvious spatial inconsistencies in the development of green finance in China’s provinces: the development of green finance in most provinces of China shows a positive spatial correlation, that is, there is a positive spatial spillover effect. en, there is a negative correlation between the development of green finance and traditional energy consumption and a positive correlation between the development of green finance and renewable energy consumption, that is, the higher the development level of green finance, the lower the traditional energy consumption and the higher the renewable energy consumption
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
