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A new model of tax governance in the context of the integration of traditional industries and the digital economy

Authors :
Qin Yong
Source :
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Publication Year :
2024
Publisher :
Sciendo, 2024.

Abstract

Tax governance faces more complex challenges with the deepening integration between traditional industries and the digital economy. This paper analyzes the main features of the digital economy according to its development, measures the digital economy based on the mixed-frequency data sampling method, and studies the selection method of the weight function and the change of the shape of the weight function with the parameters through the exploration of parameter estimation. Meanwhile, the MF-VAR model combining vector autoregression is proposed for the characteristics of mixed-frequency data. Then, the MF-VAR model is used to measure the tax leakage of the digital economy from 2015 to 2019 and compare its tax rate with that of major economies worldwide. The VAT of e-commerce e-tailing in 2019 is measured to be 848.15 billion yuan, accounting for 4.97% of the annual tax revenue, and the personal income tax leakage is measured to be 141.25 billion yuan, accounting for The amount of VAT, and personal income tax loss from e-commerce and their proportion of annual tax revenue increased year by year from 2015 to 2019, with an average annual growth rate of 40.58% and 25.21%, respectively. Tax authorities should change the traditional thinking of levy and administration, respond to the changes of the times, and innovate the governance system to protect the digital economy model in its primary stage, but also bring its development into the rule of law and standardization.

Details

Language :
English
ISSN :
24448656
Volume :
9
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Applied Mathematics and Nonlinear Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.3620a690921145c6b5057bce12d9b4fd
Document Type :
article
Full Text :
https://doi.org/10.2478/amns.2023.2.00185