Can Green Finance Optimize Energy Structure: A Spatial Econometric Analysis based on China's Traditional and Renewable Energy Consumption

: This paper studies the impact of the development of green finance on China’s energy 15 consumption structure. In terms of the construction of the green finance index (GFI), this paper 16 selects 17 basic indexes from the three aspects of economy, finance, and environment, uses the 17 improved entropy weight method to construct the GFI, and studies the spatial spillover effect of the 18 GFI of China's provinces. This paper further studies the impact of green finance on traditional and 19 renewable energy consumption. We first uses panel regression to determine that the development of 20 green finance has a positive effect on the slowdown of traditional energy consumption and 21 acceleration of renewable energy consumption, and then further studies the spatial characteristics 22 of green finance development on energy consumption by using spatial Durbin model. The results 23 show that there is a positive spatial spillover effect in the development of green finance among 24 provinces in China. The development of green finance contributes to the conversion of traditional 25 to renewable energy consumption. The effect of green finance on the transformation of energy 26 consumption structure is mainly reflected in the direct effect. Therefore, the government should 27 support the green finance, reduce traditional energy consumption and increase renewable energy 28 consumption.

improvement, climate change, and efficient use of resources, that is, financial services provided for 53 project investment and financing, project operation, and risk management in environmental 54 protection, energy conservation, clean energy, green transportation, green building, and other fields.

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Through financial services, green finance reduces the support for enterprises with high pollution 56 and high energy consumption, encourages the development of environment-friendly enterprises, 57 reduces the intensity of energy consumption, improves energy utilization, and optimizes the 58 industrial structure of a nation, so as to realize the coordinated development of economic growth, 59 green energy consumption, and environmental protection. In recent years, more and more countries   In 1974, Germany first established an environmental bank, namely the "ecological bank," to provide 84 preferential lending policies for environmental protection projects. Salazar (1998)     investment theory model, and through empirical analysis, they find that green finance has a strong 112 spatial spillover effect; the higher the level of green finance development, the more beneficial it will 113 be for investors. At the same time, the development of green finance can reduce risk and improve 114 the return rate of green energy. In contrast to Jiang, et al. (2020), who use the entropy weight method 115 to measure the GFI, this paper uses the method of annual measurement to calculate it. Because the 116 GFI measured by entropy weight method is a relative index, this paper adopts the method of annual 117 measurement to make the measurement result not time comparable.

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At this stage, there is no research on the traditional and renewable energy consumption of green 119 finance, but there is research on energy consumption of financial development. Some scholars 120 believe that financial development plays a positive role in slowing down energy consumption.

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Shahbaz (2013) studied the long-term relationship between Malaysia's carbon dioxide emissions, 122 financial development, and energy, found that financial development slowed down carbon dioxide 123 emissions to a certain extent, and proved the relationship between the two through the Granger 124 causality test. Abbasi (2016) used the ARDL method to study the long-term relationship between 125 financial development and carbon emissions, and, through the vector error correction model and 126 VECM, determined that financial variables had a greater impact on emission reduction. Khan (2017) 127 explored the relationship between per capita greenhouse gas emissions and financial development 128 by selecting the data of 34 middle and high-income countries in Asia and Europe. The study found 129 that the effect of financial development on greenhouse gas emissions in each country is different,    technologies has also adjusted the energy use structure to a great extent.

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(3) Policy support. As China pays more and more attention to the development of green finance,   China's provinces is studied from the perspectives of the economy, environment, and finance, 218 respectively, as shown in Table 1 Per capita gross regional product + Gross regional product / regional population Per capita disposable income + Regional total disposable income / regional population

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Thirdly, there are some imbalances and spatial characteristics in the development of various 267 regions in China, so this paper further uses the spatial econometric method to carry out the research;

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The SEM model only contains the spatial autocorrelation term of error term: SAR models usually contain the spatial autocorrelation terms of the explained variables: In SDM model, the spatial autocorrelation of explanatory variables is added under the 285 limitation of SAR model: In this paper, the LM Test, Hausmann test, Wald test, and joint significance test are used to 290 determine the specific model.

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Therefore, this paper will select the logarithm of coal consumption as the explained variable to 303 measure China's energy consumption level.

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(2) Explanatory variable 305 Green finance development level (GFI). The GFI is our core explanatory variable, but there is 306 no unified conclusion on whether the development of green finance helps to reduce energy 307 consumption. On the one hand, when the development level of green finance rises, the economy 308 realizes sustainable development, promotes coordination, sustainability, and equality, and helps to 309 reduce energy consumption. On the other hand, when the development level of green finance 310 increases, the environmental protection requirements of the industry will increase additional costs, 311 which will lead to more difficult operation of enterprises and may reduce the implementation of 312 environmental protection projects. Therefore, it must be determined whether the development of 313 green finance helps to reduce energy consumption.

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(3) Control variables 315 Urbanization level (LUR). We found that the development of a region is often from led by the

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The higher the education level of people, the higher the level of science and technology, and the 342 higher the energy utilization rate. In this paper, the logarithm of the average number of students per 343 100,000 people in Colleges and universities is selected to represent the proxy variable of generalized 344 technological progress.

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Specific indicators are shown in Table 2 346   Table 3.  Table 4 and Figure 1 report the GFI of China's provinces. Overall, China's GFI is increasing yearly.

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There are some differences in the development level of green finance among different regions in

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It also can be found that there is a positive correlation between green finance development and  In the theoretical analysis part of this paper, we introduce the commonly used spatial econometric 428 models and use the LM Test to determine whether to use the SEM model or SAR model. If  The results of the spatial econometric regression further confirm that the development of green 449 finance can improve the energy consumption structure. According to the results in Table 11, the 450 negative relationship between green finance and traditional energy consumption can be confirmed.

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If the development level of green finance is increased by 1%, the energy consumption will be 452 reduced by 0.845%, which is significant at the level of 1%. The positive relationship between green 453 finance and renewable energy consumption can also be confirmed. If the development level of green 454 finance is increased by 1%, the energy consumption will be increased by 1.309%, which is 455 significant at the level of 1%.

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We also can see that the direct, indirect and total effects of green finance development on

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Based on the existing research conclusions, this paper puts forward the following policy

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(2) Increase government support. From the above research results, it can be found that the 497 active intervention of the government can reduce energy consumption to a certain extent. Therefore,

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the government should increase its support for green enterprises, guide more investors and funds 499 into green enterprises through policy support, help green enterprises optimize industrial structure, 500 promote enterprise technological progress and improve energy efficiency, so as to improve energy 501 structure and reduce energy consumption.

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Availability of data and materials

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The data used to support the findings of this study are available from the corresponding author 509 upon request.

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Author contribution

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Hui Wang contributed to the writing of this manuscript.

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Lili Jiang contributed to the empirical study of this manuscript.

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Hongjun Duan contributed to the writing of this manuscript.

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Yifeng Wang contributed to the revision of this manuscript.

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Yichen Jiang contributed to the data collection of this manuscript.

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Funding 519 This paper is supported by Suqian Science and Technology Bureau(S202005). It also supported 520 by Suqian-Taiwan Convergence Development Research Center.

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Ethics approval and consent to participate: Not applicable.

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Consent for publication: Not applicable.

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Competing interests: The authors declare no competing interests 526 527