Affiliation:
1. Hebei University of Engineering , Handan , Hebei , , China .
Abstract
Abstract
China’s modern cultural industry faces difficulties in tax collection and high pressure on expenditure; in order to solve such problems, this paper constructs a modern cultural industry tax model based on Lasso regression algorithm to promote the development of modern cultural industry. In order to further study the relationship between economic factors and the tax revenue of the modern culture industry, the relevant data on China’s tax revenue between 2000 and 2021 are selected, and 12 economic factors affecting the tax revenue of the modern culture industry are screened by combining the least squares method, Lasso regression algorithm and linear regression model. After the screening of indicator variables, according to the linear regression theory, the relationship between the key economic factors screened out by Lasso regression algorithm and the fiscal revenues is estimated by fitting and tested for normality, and the modern culture industry tax revenue model based on Lasso regression algorithm is constructed. Based on the tax revenue of the modern cultural industry between 2000 and 2021, the Lasso regression algorithm is used to analyze the modern cultural industry tax revenue. Examples are used to analyze the results. The results show that the tax revenue of the culture industry in 2020 is obtained as 208, 988, 838.42 billion yuan, and the tax revenue of the culture industry in a province in 2021 is 221, 794, 675 billion yuan, and its growth rate is 6.13%, which indicates that the Lasso regression algorithm is able to extract the information contained in the tax revenue of the modern culture industry well, and the coefficients of the parameter part are also in line with the actual tax situation coincides with the actual tax situation. Through the innovation of tax management structures and theoretical optimization, this study aims to promote the healthy and rapid development of modern cultural industries.
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