Variable description.

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.