统计与数据科学学院知识库

 区域性金融风险是特定区域范围内金融产业可能产生累积的风险。由于金融市场特殊的渗透性和网络化，金融风险具有极强的传播特征，一旦区域性风险形成跨区域的传染途径，就可能导致整体金融风险的发生。数字金融是在传统普惠金融的基础上，融合现代信息技术，为用户提供更便捷的金融服务的一种新型金融模式。数字金融可以利用传统的征信系统预测风险，还可以通过整合用户的个性化信息来识别、测度和预测风险，从而降低金融机构的业务风险。因此，探究数字金融与区域性金融风险的关系，对防范金融风险和促进数字金融的发展具有重要意义。
       本文首先整理了近年来学者们关于数字金融和区域性金融风险的讨论，然后分析二者之间的影响机制，提出本文的研究假设，在此基础上本文以2011-2021年中国31个省（自治区、直辖市）为样本，首先采用双向固定效应模型探究数字金融对区域性金融风险的影响；其次采用中介效应模型和调节效应模型探究二者的影响机制；最后本文构建面板分位数回归模型探究数字金融对不同区域性金融风险水平的影响。研究表明：
       第一，数字金融对区域性金融风险具有显著的负向影响，说明数字金融能够缓解区域性金融风险。在区域异质性方面，数字金融能够显著抑制我国东部和中部地区的金融风险，对于西部地区的缓解效果不显著。
       第二，数字金融对区域性金融风险的影响机制分别选取三个变量进行讨论。本文选取政策集聚作为中介变量，风险投资和金融竞争作为调节变量。研究发现，政策集聚在数字金融与区域性金融风险之间具有中介效应，数字金融通过政策集聚缓解区域性金融风险；在数字金融缓解区域性金融风险的过程中，风险投资具有调节效应，即风险投资程度越高，数字金融对区域性金融风险的抑制作用越明显；数字金融与金融竞争在抑制区域性金融风险上存在替代效应，地区金融竞争程度较低时，数字金融缓解区域金融风险的效果更加明显。
       第三，数字金融对区域性金融风险的影响具有差异性。主要表现在数字金融缓解不同区域性金融风险水平上，数字金融的系数变化趋势表现为“倒U”型特征。同时，数字金融分指数对不同区域性金融风险水平的缓解效果也有所不同，主要表现在数字金融覆盖广度和普惠金融数字化程度上。
       因此，本文结合上述研究结论提出相关政策建议，帮助政府合理规划数字金融的发展结构，防范化解区域性金融风险。

  Regional financial risk is the risk that may accumulate in the financial industry within a specific region. Due to the special permeability and networking of financial markets, financial risks have strong propagation characteristics. Once regional risks form a cross-regional contagion pathway, it can lead to the occurrence of overall financial risks. Digital finance is a new financial model that integrates modern information technology on the basis of traditional inclusive finance to provide users with more convenient financial services. Digital finance can use the traditional credit information system to predict risks, and can also identify, measure and predict risks by integrating users' personalized information, so as to reduce the business risk of financial institutions. Therefore, it is of great significance to explore the relationship between digital finance and regional financial risks to prevent financial risks and promote the development of digital finance.
       This thesis first summarizes the discussions on digital finance and regional financial risks in recent years. Then, the influencing mechanism between the two is analyzed, and the research hypothesis of this paper is proposed. On this basis, this paper takes 31 provinces(autonomous regions and municipalities directly under the central government)  in China from 2011 to 2021 as a sample. First, the two-way fixed-effect model is used to explore the impact of digital finance on regional financial risks. Second, the mediating effect model and the moderating effect model were used to explore the influencing mechanism of the two. Finally, this paper constructs a panel quantile regression model to explore the impact of digital finance on different regional financial risk levels. Studies have shown that:
       Firstly, digital finance has a significant negative impact on regional financial risks, indicating that digital finance can alleviate regional financial risks. In terms of regional heterogeneity, digital finance can significantly inhibit the financial risks in the eastern and central regions of China, but has no significant mitigation effect on the western region.
       Secondly, the impact mechanism of digital finance on regional financial risks is discussed with three variables. In this paper, policy agglomeration is selected as the mediating variable, and venture capital and financial competition are selected as the moderating variables. The results show that policy agglomeration has an intermediary effect between digital finance and regional financial risks, and digital finance alleviates regional financial risks through policy agglomeration. In the process of alleviating regional financial risks in digital finance, venture capital has a moderating effect, that is, the higher the degree of risk investment, the more obvious the inhibitory effect of digital finance on regional financial risks. There is a substitution effect between digital finance and financial competition in inhibiting regional financial risks, and the effect of digital finance in alleviating regional financial risks is more obvious when the degree of regional financial competition is low.
       Thirdly, the impact of digital finance on regional financial risks is different. It is mainly manifested in the alleviation of different regional financial risk levels in digital finance, and the coefficient change trend of digital finance shows an "inverted U" shape. At the same time, the mitigating effect of the digital finance sub-index on the financial risk level of different regions is also different, which is mainly reflected in the breadth of digital financial coverage and the digitalization of inclusive finance.
       Therefore, this paper puts forward relevant policy suggestions based on the above research conclusions to help the government rationally plan the development structure of digital finance and prevent and resolve regional financial risks.