Research on the Application of Computer Big Data Technology in the Fiscal Revenue Model Using Mathematical Statistics and Smart Information Systems

Abstract

This paper uses the data of China’s three major industries’ value-added, employment and China’s fiscal revenue from 2000 to 2020 to conduct an empirical study on the factors affecting China’s fiscal revenue. This article compares and analyzes the different effects of primary industry added value, secondary industry added value, tertiary industry added value, employment number and other variables on fiscal revenue. It can be seen that the largest impact is the tertiary industry added value, followed by the secondary industry’s increase. value. The national fiscal revenue is most affected by the total output value of the service industry and the total population of the country. Finally, we also draw on the relevant principles and technologies of mathematical statistics and information systems to build a fiscal revenue monitoring and early warning system, and try to achieve dynamic monitoring and early warning of government revenue on the computer through quantitative research and system analysis.