Abstract: Big data in tax enforcement inhibits corporate tax avoidance, which shows the situation of "tax reduction is difficult to reduce burden". However, few literatures reveal the positive significance of big data in tax enforcement in alleviating corporate tax burden. Based on the data of listed companies from 2008 to 2016, and with the help of the "Golden Tax Phase III Project" as a quasi-natural experiment, the double-difference method is used to explore the impact and mechanism of big data tax collection and management on corporate tax burden. The results show that big data in tax enforcement can effectively alleviate the stickiness of corporate tax burden, and this mitigation effect is more prominent in private enterprises, enterprises in areas with a high degree of marketization, and enterprises in areas with less financial income pressure. Mechanism inspection finds that big data in tax enforcement can effectively alleviate the stickiness of corporate tax burden by reducing the information asymmetry between the two parties, regulating the tax collection behavior of tax authorities, and effectively implementing preferential tax policies. The above conclusions provide theoretical support and empirical evidence for the continuous improvement of tax informatization construction, the further optimization of the tax business environment, and the implementation of new tax and fee reduction policies.

Key words: big data in tax enforcement, third phase of the golden tax project, corporate tax burden, stickiness of corporate tax burden