首页|Does Information Exchange Affect Cross-border Tax Avoidance?Evidence from the Common Reporting Standard
Does Information Exchange Affect Cross-border Tax Avoidance?Evidence from the Common Reporting Standard
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
万方数据
Using panel data from 2012 to 2020for publicly traded Chinese companies,we explored the efficacy in mitigation of tax information asymmetry to combat profit shifting and transnational tax avoidance.Our empirical analysis revealed that,after the implementation of the inaugural multilateral automatic information exchange system known as the Common Reporting Standard,there was a statistically significantly increase in the effective tax rate by 1.4 percentage points,accompanied by an increase in instances of tax compliance.These trends were discernibly associated with a reduction in profit shifting and notable changes in reported profit margins,particularly influenced by actions related to debt shifting and strategic management of intellectual property assets.These findings underscore the strong connection between these effects and various factors such as investment destinations,asset portfolios,and industry classifications.The results imply a prospective decline in the incidence of cross-border tax avoidance by Chinese multinational entities and demonstrate the potential of emerging international tax cooperation frameworks for curbing the global tax avoidance practices of multinational corporations.
cross-border tax avoidanceCommon Reporting Standardprofit shiftingtax information
Muhan Wang、Kezhong Zhang、Sihan Gao
展开 >
School of Public Finance and Taxation,Zhongnan University of Economics and Law,China
School of Public Finance and Taxation,Center for International Cooperation and Disciplinary Innovation of Income Distribution and Public Finance(111 Center),Zhongnan University of Economics and Law,Public Finance and Development Research Center of Hubei,China
Center for International Cooperation and Disciplinary Innovation of Income Distribution and Public Finance(111 Center),Zhongnan University of Economics and Law,Public Finance and Development Research Center of Hubei,China
NETL
NSTL
万方数据
