Big Data Tax Collection and Management on Analyst Eearnings Impact of Prediction Quality
As an organic combination of emerging technology and tax work,big data tax collection and management is of great significance to the construction of a new governance pattern of"controlling tax by numbers"and the promotion of high-quality economic development.The article takes the pilot project of"Golden Tax Phase Ⅲ"as a quasi-natural experimental scenario,and takes the data of China's A-share listed companies from 2009 to 2021 as the sample for empirical analysis,and applies double-difference modelling to explore the relationship between big data tax collection and the quality of analysts'surplus forecasts.The study found that big data tax collection and management significantly improved the analyst earnings forecast accuracy,reduce the forecast divergence,in non-state-owned enterprises,high tax motivation,low institutional investors supervision level,weak analyst industry expertise,the positive effect is more obvious.Mechanism analysis finds that big data tax collection and management can improve the quality of analyst surplus forecast by improving the enterprise information environment and reducing the agency problem.In addition,the study of economic consequences shows that the improvement of the quality of analyst surplus forecast finally achieves the effect of reducing the cost of enterprise capital.This paper provides evidence support for relevant departments to use big data technology to improve the quality of analyst surplus forecast,and provides reference value for the evaluation of the economic consequences of big data tax collection and administration.
big data tax collection and managementaccuracy of earnings forecastdivergence of earnings forecastenterprise information environmententerprise agency problem
万方数据
维普
