Proceedings of the 2022 2nd International Conference on Public Management and Intelligent Society (PMIS 2022)

<Previous Article In Volume
Next Article In Volume>

Study on Urban Fiscal Revenue and Industrial Upgrading Based on a Big Data Model

Authors
Yu Feng Shi1, *, Jia Yue Kuang1
1School of Yueshang/MBA, Guangdong University of Finance & Economics, Guangzhou, China
*Corresponding author. Email: syf_nm@126.com
Corresponding Author
Yu Feng Shi
Available Online 7 December 2022.
DOI
10.2991/978-94-6463-016-9_9How to use a DOI?
Keywords
Local fiscal; Regional economic; Pearl River Delta; Dynamic Equilibrium Index model
Abstract

In order to reveal the high-quality level of fiscal revenue growth in the Chinese Pearl River Delta cities, this paper first constructs a Dynamic Equilibrium Index model. The model is based on the classical DEA model frame and includes two optimization indicators: maximum value and minimum value. It is compatible with stringent and loose evaluation standards, which can be weight adjusted according to the actual needs. This model belongs to the optimal dynamic planning algorithm and can be widely used to evaluate the production level. Then, the fiscal income, GDP, disposable income and employment population in the Pearl River Delta cities for nearly 10 years were taken as the variables of the above model, among which GDP, disposable income and employment population serve as the input variables, and fiscal income as the output variable. The results show that Shenzhen has been far ahead of the other six cities, followed by Guangzhou, Zhuhai, Foshan, Dongguan, Huizhou and Zhongshan. The results fully demonstrate the principle that the high-quality level of modern urban fiscal revenue growth depends on the proportion of advanced manufacturing, high-tech industry and modern services. Conclusion: Shenzhen is undoubtedly the city with the fastest growing fiscal revenue in the Pearl River Delta, because Shenzhen has high proportion of advanced manufacturing and high-tech industries.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2022 2nd International Conference on Public Management and Intelligent Society (PMIS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
7 December 2022
ISBN
978-94-6463-016-9
ISSN
2589-4900
DOI
10.2991/978-94-6463-016-9_9How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yu Feng Shi
AU  - Jia Yue Kuang
PY  - 2022
DA  - 2022/12/07
TI  - Study on Urban Fiscal Revenue and Industrial Upgrading Based on a Big Data Model
BT  - Proceedings of the 2022 2nd International Conference on Public Management and Intelligent Society (PMIS 2022)
PB  - Atlantis Press
SP  - 65
EP  - 73
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-016-9_9
DO  - 10.2991/978-94-6463-016-9_9
ID  - Shi2022
ER  -