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Study on the impact of tax collection on corporate surplus management in the context of big data
Authors:
Xinyi Zheng, Mohamad Ali Abdul Hamid* , Yongpeng Ma , Leyi Zhang1 ,Tze San Ong ,Keywords
Tax administration, financial big data, corporate surplus management, multiple regression analysis, significance. ,Abstract
Exploring the impact of tax levy on corporate surplus management can better suggest tax policies. This paper takes listed enterprises in Shanghai and Shenzhen A-share markets in China as the research object, and selects a large sample of corporate financial data from 2011 to 2021. The modified Jones model and KLW model are used to measure corporate surplus management, and a multiple regression model of the impact of tax levy on corporate surplus management is constructed. The big data samples were entered into the model, significance was analyzed based on the baseline regression results, and the reliability of the results was verified using robustness tests and correlation analysis. The regression results show that the regression coefficient is -0.025 and significantly negative when regressing tax collection variables on surplus management with fixed effects, as expected. After adding the firm-level control variables, the coefficient is -0.018, which is still significantly negative. The value of the test coefficient significantly decreases by about 0.01 in the year of and after the implementation of the tax levy, indicating that the tax levy project significantly reduces the degree of surplus management of the firm. This paper addresses well the issue of measuring tax levies when studying tax levies on corporate governance and provides evidence for the existence of corporate tax avoidance and surplus management behavior. The paper provides evidence for the existence of corporate tax avoidance and surplus management behavior.