The impact of big data tax administration on local fiscal revenue: New evidence from the "Golden Tax Project Phase III"

Abstract

Adequate local fiscal revenue (LFR) is the foundation for governments to provide public services, maintain operations, and promote economic development. Big data tax administration (BDTA), by optimizing tax management, improving tax compliance, and combating tax evasion, has effectively driven the growth of LFR. Using the Golden Tax Project Phase Ⅲ (GTPP Ⅲ) as a quasi-natural experiment in BDTA, this paper examines the impact of BDTA on LFR, based on panel data from 290 cities between 2009 and 2015, employing a multi-period difference-in-differences (MP-DID) model. Furthermore, the study explores the mechanism effects of industrial output and information infrastructure. The main findings of this paper are as follows: First, the results show that BDTA significantly promotes the growth of LFR, and this conclusion remains robust after a series of robustness checks. Second, BDTA indirectly increases LFR by boosting industrial output and improving information infrastructure. Finally, heterogeneity analysis reveals that the impact of BDTA on LFR is more pronounced in cities with low fiscal transparency, low levels of information infrastructure, and in general cities, indicating that the policy has stronger marginal effects in these areas. By analyzing the impact of the GTPP III on LFR, this paper highlights the role of BDTA in enhancing LFR, providing a basis for optimizing BDTA policies.