金融学院知识库

“十四五”规划和2035年远景目标明确提出在经济发展中实现“双碳目标”。这一目标要求我国产业结构向绿色创新转型、能源消费结构向绿色清洁转型，改变以往粗放发展模式，实现经济高质量发展。2024年政府工作报告进一步提出要加快发展新质生产力，要求在经济发展过程中摆脱落后的经济发展模式，以高质量、高效率和可持续作为追求目标。数字普惠金融凭借自身的优势能有效弥补传统金融服务的不足，缓解绿色创新面临的融资难题，推动绿色创新发展。因此，深入研究数字普惠金融对我国绿色创新效率的影响具有一定的理论和现实意义。

本文在现有学者研究和相关理论的基础上，首先利用Super-SBM-Windows-DEA模型，测算了2011-2021年我国275个地级市（剔除直辖市及数据严重缺失的地级市）的绿色创新效率值。其次，采用双向固定效应模型分析数字普惠金融对我国绿色创新效率的影响。再次，运用中介效应模型分析了环境规制和产业结构优化升级在其中的传导机制，并进一步运用空间杜宾模型探究在考虑空间因素下，数字普惠金融对绿色创新效率的影响。最后，根据理论分析和实证结果，并结合我国的“十四五”规划和2035年远景目标，对数字普惠金融和绿色创新效率发展提出一些建设性意见。

根据实证研究结果，本文得出以下结论：第一，数字普惠金融的发展对我国绿色创新效率水平有显著促进作用，在覆盖广度、使用深度和数字化程度三个子维度均能促进我国绿色创新效率水平提升；第二，在区域异质性方面，发现数字普惠金融对东部地区绿色创新效率的促进作用略强于中西部地区；第三，数字普惠金融能通过环境规制和促进产业结构优化升级两条传导渠道提升本地区绿色创新效率水平；第四，纳入空间效应因素后，发现数字普惠金融的发展不仅有助于提高当地绿色创新效率，也推动了邻近地区绿色创新效率水平提升。

The 14th Five-Year Plan and the Long-Range Objectives Through 2035 clearly state that the "dual carbon goals" should be achieved in economic development. This goal requires the transformation of China's industrial structure to green innovation, the transformation of energy consumption structure to green and clean, the change of the previous extensive development model, and the realization of high-quality economic development. The 2024 government work report further proposes to accelerate the development of new quality productive forces, requiring that in the process of economic development, we should get rid of the backward economic development model and pursue the goal of high quality, high efficiency and sustainability. With its own advantages, digital inclusive finance can effectively make up for the shortcomings of traditional financial services, alleviate the financing problems faced by green innovation, and promote the development of green innovation. Therefore, it is of theoretical and practical significance to study the impact of digital inclusive finance on the efficiency of green innovation in China.

Based on the existing scholars' research and related theories, this paper first uses the Super-SBM-Windows-DEA model to calculate the green innovation efficiency of 275 prefecture-level cities in China from 2011 to 2021 (excluding municipalities directly under the central government and prefecture-level cities with serious data deficiency). Secondly, the two-way fixed-effect model is used to analyze the impact of digital inclusive finance on the efficiency of green innovation in China. Thirdly, the mediating effect model is used to analyze the transmission mechanism of environmental regulation and industrial structure optimization and upgrading, and the Spatial Durbin Model is further used to explore the impact of digital inclusive finance on the efficiency of green innovation under the consideration of spatial factors. Finally, based on the theoretical analysis and empirical results, combined with China's 14th Five-Year Plan and the long-term goals of 2035, some constructive suggestions are put forward for the development of digital inclusive finance and green innovation efficiency.

Based on the empirical research results, this paper draws the following conclusions: first, the development of digital inclusive finance has a significant role in promoting the efficiency level of green innovation in China, and can promote the improvement of China's green innovation efficiency in three sub-dimensions: coverage breadth, depth of use and digitalization; Second, in terms of regional heterogeneity, it is found that digital inclusive finance has a slightly stronger role in promoting green innovation efficiency in the eastern region than in the central and western regions. Third, digital inclusive finance can improve the efficiency of green innovation in the region through two transmission channels: environmental regulation and promoting the optimization and upgrading of industrial structure. Fourthly, after taking into account the spatial effect factor, it is found that the development of digital inclusive finance not only helps to improve the efficiency of local green innovation, but also promotes the improvement of green innovation efficiency in neighboring regions.