大数据税收征管能够缓解企业税负粘性吗——基于“金税三期工程”的政策效应分析

Big Data in Tax Enforcement and Stickiness of Corporate Tax Burden-Analysis of policy effect based on“the Third Phase of the Golden Tax Project”

基于2008~2016年上市公司数据,借助“金税三期工程”在全国逐步试点作为准自然实验,运用双重差分法探究大数据税收征管对企业税负粘性的影响及作用机制。结果表明:大数据税收征管能够有效缓解企业税负粘性,这种缓解效应在民营企业、市场化程度较高地区的企业以及财政创收压力较小地区的企业中较为突出。机制检验发现,大数据税收征管通过减少征纳双方信息不对称、规范税务机关征税行为、切实落实税收优惠政策等路径可有效缓解企业税负粘性。此结论可为持续完善税收信息化建设、进一步优化税收营商环境和实施新的减税降费政策提供理论支撑和经验证据。

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.