High-quality development of enterprises.

In the era of digital economy, big data tax collection and management has become an important governance tool for digital government. In this study, the quasi-natural test environment provided by the "Golden Tax Phase III" policy launched in 2013 and the method of propensity score matching and differentiation (PSM-DID) were used on combination of the samples of A-share listed enterprises in Shanghai and Shenzhen during 2010–2021 to analyze and demonstrate the impact of this policy on the innovation of the listed enterprises. To ensure the robustness of these findings, various statistical techniques such as parallel trend tests, placebo tests, and the explained variable replacement were employed. Additionally, an influence mechanism test was conducted to examine the mediating effect of big data tax collection and management on enterprise innovation, revealing the reduction of enterprise financialization. Furthermore, moderating effect tests and heterogeneity analyses were also performed, and the results showed that the agency costs and financing constraints play a negative role in regulation, and the promotion effect of big data tax collection and management on enterprise innovation is more significant in enterprises with high information transparency and non-high-tech enterprises. Finally, in the further study and economic consequence test, it is found that big data tax collection and management can promote the high-quality development of enterprises while promoting enterprise innovation. The conclusions of this study are helpful for government departments to continuously promote big data tax collection and management, promote the implementation of innovation-driven strategic policies, and promote high-quality economic development.数字经济时代，大数据税收征管已成为数字政务的重要治理工具。本研究以2013年推行的“金税三期（Golden Tax Phase III）”政策所提供的准自然实验环境为基础，结合2010-2021年沪深A股上市公司样本，采用倾向得分匹配-双重差分法（PSM-DID）分析并验证了该政策对上市公司创新活动的影响。为确保研究结论的稳健性，本研究采用平行趋势检验、安慰剂检验、被解释变量替换等多种统计方法进行稳健性验证。此外，本研究还开展了影响机制检验，考察了大数据税收征管对企业创新的中介传导效应，揭示了其可通过抑制企业金融化发挥作用。进一步地，本研究开展了调节效应检验与异质性分析，结果显示：代理成本与融资约束发挥负向调节作用；且在信息透明度较高企业与非高新技术企业中，大数据税收征管对企业创新的促进效应更为显著。最后，在拓展性研究与经济后果检验中，本研究发现大数据税收征管在推动企业创新的同时，还可促进企业高质量发展。本研究结论有助于政府部门持续推进大数据税收征管工作，助力创新驱动战略政策落地，推动经济高质量发展。