数字金融发展对区域创新的激励效应研究

摘要/Abstract

摘要： 强化数字金融发展的创新激励效应，是我国在后疫情时期坚持创新赋能业态变革，助力经济新旧动能转换的重要抓手。为此，立足于我国30个省份2011—2018年面板统计数据，采用个体固定效应模型、空间计量模型、面板门槛模型和结构方程模型路径分析等方法，实证考察我国数字金融发展对区域创新的激励效应。结果显示：数字金融及其分解指数（覆盖广度、使用深度和数字化程度）都能正向激励区域创新，但激励效果存有差异，其中使用深度最为显著，其次是覆盖广度和数字化程度；在异质性方面，数字金融发展对区域创新的激励效应具有一定的创新主体异质性和区域异质性；在空间特征方面，某区域数字金融发展不仅直接激励本土创新，而且存在空间溢出效应能够间接激励其他区域创新，但这种空间溢出效应的贡献率十分有限；在非线性特征方面，数字金融发展对区域创新的激励效应在劳动者素质、政府支持和产业升级单一门槛的约束下，表现边际递增的态势，而在对外开放单一门槛的约束下，呈现边际递减的趋势；在传导路径方面，数字金融发展能够通过内部因素和外部因素两条路径间接激励区域创新，其中内部因素是主要的传导路径，研发强度在内部因素中起主要作用，而在外部因素中经济发展占主导地位。

关键词: 数字金融发展, 区域创新, 激励效应

Abstract: Adhering to innovation-driven development and cultivating new kinetic energy is an important strategy for China to promote stable economic development in the post-epidemic period. However, it is undeniable that China′s innovation has always faced the problems of difficult and expensive financing. The essential reason is the imbalance of China′s financial resource allocation. With the rapid development of China′s digital technology, the in-depth integration of the financial industry and digital technology has formed a new type of financial model—digital finance, triggering thinking: Can digital finance become a "new engine" for innovation and positively stimulate regional innovation? In order to verify this problem, based on the panel statistical data of 30 provinces in China from 2011 to 2018, this paper adopts methods such as individual fixed effects model, spatial measurement model, panel threshold model and structural equation model path analysis to empirically analyzes the incentive effect of China′s digital financial development on regional innovation. The main conclusions are as follows:
Firstly, the development of digital finance can positively stimulate regional innovation, but the incentive effect of the digital financial decomposition index is different. Among them, the depth of use of digital finance has the strongest incentive effect on regional innovation, followed by the breadth of coverage and the degree of digitalization of digital finance.

Secondly, in terms of heterogeneous characteristics, the innovation incentive effect of digital financial development has significant innovation subject heterogeneity and regional heterogeneity. From the results of the heterogeneity of innovation subjects, the development of digital finance has the strongest innovation incentive effect on scientific research institutions, followed by universities and industrial enterprises. From the perspective of regional heterogeneity, the innovation incentive effect of digital financial development in the eastern and western regions is significant, while the central region is not. At the same time, the western region has the strongest incentive effect, followed by the eastern and central regions.

Thirdly, in terms of spatial characteristics, the innovation incentives for digital finance development have significant direct effects and spatial spillover effects, indicating that the development of digital finance in a certain region can not only directly stimulate innovation in its own region, but also indirectly stimulate the innovation activities of other regions through spatial spillover effects. However, the contribution rate of direct effects to the total effect is higher than the spatial spillover effect, indicating that China′s digital financial development has insufficient spatial spillover power to stimulate regional innovation and there is room for further improvement.

Fourthly, in terms of non-linear characteristics, under the constraints of a single threshold of labor quality, government support and industrial upgrading, the development of digital finance has an incremental innovation incentive effect, while under the constraint of a single threshold of opening up, the development of digital finance has a diminishing innovation incentive effect.
Fifthly, in terms of transmission paths, the development of digital finance can indirectly stimulate regional innovation through internal factors and external factors. The transmission validity of internal factors is 0.128 and the transmission validity of external factors is 0.061, indicating that internal factors are the most important transmission path in the indirect incentive process. Although the transmission validity of external factors is low, the development of digital finance has a more significant impact on external factors. At the same time, R&D intensity plays a major role in internal factors, while economic development is dominant in external factors.
In addition, in order to ensure the consistency of the core estimation results, this paper carried out endogeneity discussion and stability test. In terms of endogeneity, this paper constructs dual instrumental variables of Internet penetration rate and mobile phone penetration rate to conduct IV-2SLS estimation test. The results show that the instrumental variables are effective and there is no problem of over-identification, the development of digital finance can still positively stimulate regional innovation, and the incentive validity has increased. In terms of stability testing, this paper uses three methods: dynamic panel model, replacing explained variables, and changing research objects to carry out stability testing. The results show that although the significance and validity of the innovation incentive effects of digital finance have changed, the direction of action is always consistent. It can be seen that based on the discussion of endogeneity and stability test, the core conclusion of this article is reliable.
Finally, based on the above research conclusions, this paper proposes policy recommendations from three perspectives: accelerating the digital transformation of the financial industry, building an interconnected digital financial ecosystem and improving the digital financial regulatory system.

Key words: digital financial development, regional innovation, incentive effect

郑万腾, 赵红岩, 范宏. 数字金融发展对区域创新的激励效应研究[J]. 科研管理, 2021, 42(4): 138-146.

Zheng Wanteng, Zhao Hongyan, Fan Hong. A research on the incentive effect of digital finance development on regional innovation[J]. Science Research Management, 2021, 42(4): 138-146.

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