Abstract

Digitalization and big data are increasingly linked to taxation policies as technology advances and digital transformation accelerates. This study examines the complex interaction between these factors in China over the past two decades and their effects on taxation policy. This rigorous study uses quantitative analysis, econometric modeling, and empirical investigations to examine key variable relationships using the Dynamic Generalized Method of Momentum. The study’s variables are examined using longitudinal data from government reports, academic journals, and international databases. Descriptive statistics, correlation analysis, regression modeling, instrumental variable regression, and mediation analysis help researchers understand complex relationships. The analysis shows that digital infrastructure, tax policy, and big data use affect taxation directly and indirectly. The study found that digitalization and big data improve taxation policy, showing technology's fiscal governance potential. This research affects policy, business, and society beyond academia. Chinese and other digital taxation policymakers can use the findings to make evidence-based reforms. For Chinese companies, this study optimizes tax planning, compliance, and tax landscape navigation. The study's theoretical implications enhance our understanding of technology, governance, and public policy and contribute to the digitalization and big data taxation policy debate. This study advances digital taxation policy research and prepares future research such as integrating AI and blockchain technologies.