金融学院知识库

党的二十大报告提出，推动低碳产业发展，需要优化支持低碳发展的财政、税收、投资和标准体系，完善以市场为导向的资源环境要素供求体系，加快污染减排和碳减排技术的创新和应用，提倡低碳消费，倡导绿色低碳生产和生活方式，推动形成绿色低碳经济。绿色金融作为促进低碳经济发展的重要手段之一，已经引起政府和社会的广泛关注。因此，积极推动绿色金融的发展，既是推动生态文明建设的内在要求，也是促进我国低碳经济发展、实现金融供给侧结构性改革向生态化转型的必然要求。

首先，在回顾了现有文献和相关理论后，对绿色金融与低碳经济等概念进行了明确定义，并利用扩展的Kaya模型进行了绿色金融与低碳经济发展之间的非线性关系的数值模拟和分析。其次，本研究以2008至2020年中国30个省级行政单位的面板数据为基础，构建了绿色金融发展评价指标体系。采用遗传算法组合赋权法逐层计算指标权重，得到绿色金融发展综合指数。从经济增长和碳排放的角度计算碳生产力，衡量低碳经济的发展水平，并根据计算结果分析了绿色金融与低碳经济发展的现状。最后，运用半参数空间面板模型，探究绿色金融在低碳经济中的非线性作用及其在不同地区的异质性。

研究结果表明以下几点。第一，在研究期内，中国绿色金融和低碳经济发展的整体水平呈现出上升趋势，区域和省际之间的差异也呈现出不断扩大的发展态势。莫兰指数和空间异质性分布图显示，中国区域绿色金融发展与低碳经济发展之间存在着明显的空间依赖关系。此外，随着年份的增加，更多的省份呈现出高-高集聚和低-低集聚的特点。第二，绿色金融对低碳经济发展的影响呈现出明显的“U”型非线性关系，这一规律也适用于绿色金融对相邻地区低碳经济发展的影响。第三，二者之间的非线性关系具有区域异质性：东部地区绿色金融和低碳经济发展呈正向线性关系，中部地区呈“U”型非线性特征。然而，在西部地区，它显示出一种近似倒置的“N”型非线性关系。最后，基于理论和实证模型结果，提出了促进绿色金融发展、更好地服务于低碳经济发展的可行政策建议。

The report of the Twentieth National Congress of the Communist Party of China pointed out that to promote the development of low-carbon industries, it is necessary to optimize the financial, tax, investment and standard systems to support low-carbon development, improve the supply and demand system of market-oriented resources and environmental elements, accelerate the innovation and application of pollution emissions reduction and carbon reduction technologies, promote low carbon consumption, advocate green low carbon production and lifestyle, and promote a green and low carbon economy. As one of the important means to promote the development of a low-carbon economy, green finance has attracted widespread attention from governments and society. Therefore, actively promoting green finance development is both an inherent requirement for promoting the construction of ecological civilization, but also an inevitable requirement to facilitate China's development of the low carbon economy and realize the financial supply-side structural reform to the transformation of ecology.

First, after reviewing existing literature and related theories, concepts such as green finance and a low-carbon economy have been clearly defined, and a numerical simulation and analysis of the non-linear relationship between green financing and the development of a low-carbon economy have been carried out using the expanded Kaya model. Second, this study based on panel data from 30 provincial administrative units in China from 2008 to 2020, built a green financial development evaluation indicator system. The use of the genetic algorithm portfolio empowerment method layer by layer calculated the indicator weight, and obtained the comprehensive index of green financial development. Calculate carbon productivity from the perspective of economic growth and carbon emissions, measure the level of development of a low-carbon economy, and analyze the status quo of green finance and low-carbon economy development based on the results of the calculation. Finally, the semi-parameter spatial panel model explores the nonlinear role of green finance in a low-carbon economy and its heterogeneity in different regions.

The study results show the following points. First, during the study period, China’s overall level of green finance and low-carbon economy development showed an upward trend, and regional and inter-provincial differences also showed a growing trend of development. The Molland Index and the spatial heterogeneous distribution chart showed that there was a clear spatially dependent relationship between China's regional green finance development and the development of a low-carbon economy. In addition, as the years increased, more provinces showed characteristics of high-high concentration and lower-low concentration. Secondly, the impact of green finance on the development of a low-carbon economy shows a clear "U" type of non-linear relationship, which also applies to the effect of green financing on the growth of low-carbon economies in neighbouring regions. Third, the nonlinear relationship between the two has a regional heterogeneity: the development of green finance and low-carbon economies in the eastern region has a positive linear relationship, and the central region has a "U" type of non-linear characteristics. However, in the western region, it shows an approximately reversed "N" type of nonlinear relationship. Finally, based on the results of theoretical and empirical models, feasible policy suggestions are proposed to promote green finance development and better serve the development of a low-carbon economy.