Summary:
This paper examines the relationship between digital finance and regional technology innovation by analyzing province-level panel data from 2011-2018 in a two-step system generalized method of moments model and a dynamic threshold regression model. First, we construct a benchmark linear regression model to verify the influence of digital finance and its sub-indices on regional technology innovation. Second, we use the dynamic threshold panel model to further explore the potential non-linear relationships. The factors include the perfection level of digital finance, the quality of the institutional environment, and the internal absorptive capacity of technology. We also explore two possible mechanisms for digital finance to promote regional technology innovation: the easing of financing constraints and the upgrading of industrial structure. Finally, we explore the potentially differing roles of digital finance in promoting technology innovation in the spatial and temporal dimensions. There are three main findings. First, digital finance exerts a significantly positive effect on the level of regional technological innovation by easing financing constraints and upgrading industrial structure. Second, the positive effect of digital finance on regional technological innovation is stronger in regions that have better developed digital finance, better institution quality, or a higher level of human capital. Third, we find significant heterogeneity in the spatial and temporal dimensions regarding the role of digital finance in promoting technology innovation. Specifically, the positive effect of digital finance on regional technology innovation is more pronounced in eastern regions and following reforms that promote the development of digital finance. We propose the following policy implications based on our empirical findings. First, we should promote the deployment of digital finance in China and the digital reform of traditional financial institutions using financial technology under proper governance to improve digital finance in new technology scenarios. At the same time, we must adhere to the unity of marketization, legalization, and internationalization principles, stabilize the pace of development, fully incorporate financial activities into supervision, ensure the safety and stability of the financial system, and optimize the function and efficiency of financial services in the economy. Second, we should improve the institutional environmental quality, local human capital, and other key supporting factors to promote the role of digital finance. On the one hand, we need to refine the existing intellectual property protection laws and regulatory systems, improve law enforcement efficiency, and establish a multi-level legal publicity system. On the other hand, we should build a diversified talent training model and strengthen the construction of technology innovation teams, and formulate appropriate incentive measures and institutional arrangements based on the development status of different regions to maximize the positive effect of digital finance on regional technology innovation. Finally, we should accelerate the transformation of innovation models, improve the level of regional innovation quality review and the construction of innovation evaluation systems, cautiously prevent the appearance of “false” or “strategic” innovation behaviors, and strengthen the effectiveness of financial support and industrial policies that promote the improvement of regional technology innovation. Our paper also contributes to the literature in several ways. First, we explore the effect of financial development on regional innovation in a new and extensive digital finance model, and validate two possible mechanisms for how digital finance affects the local innovation. To the best of our knowledge, this is the first paper to test the non-linear effect of financial development on technology innovation, thus providing an important supplement to the literature on financial functions. Second, this paper adopts a comprehensive variety of methods, including a dynamic panel model, instrumental variable method, and dynamic threshold panel model, to explore the linear and non-linear relationships between digital finance and the level of technology innovation; it thereby enriches the literature in terms of research methods in the field of innovation, and fully guarantees the robustness of the results. Third, this paper uses the market value of granted patents as a proxy variable, which effectively measures the level and quality of regional technology innovation, to comprehensively examine the impact of digital financial development on regional technology innovation. Therefore, this paper provides new insights on innovation measures and expands the literature on innovation.
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