Study on the Dynamic Analysis of the Evolutionary Game and Influence Effect of Green Taxation in Promoting the Development of New Energy Industry
DOI:
https://doi.org/10.47852/bonviewJCBAR42023951Keywords:
green tax, new energy industry, evolutionary dynamic modelingAbstract
The development of China’s new energy industry has accelerated, significantly advancing the country’s progress toward achieving ‘carbon neutrality’ and ‘carbon peak’. In this context, green tax serves as a powerful catalyst for the growth of the new energy sector. Taking into account the heterogeneity of enterprises, this paper constructs a dynamic evolution model involving the ‘government, local enterprises, and foreign enterprises’ to elucidate the decision-making mechanisms of traditional energy enterprises in their transition to new energy, driven by green tax incentives.Using corporate financial report data from the Wind database and energy and economic data from Chinese provinces from 2016 to 2021, this study empirically examines the impact of green tax on the development of the new energy industry. The findings indicate that implementing a green tax system can effectively promote the regional growth of the new energy sector. This positive effect remains robust even after accounting for intrinsic factors and employing various validation tools. Furthermore, a regional comparison reveals that the positive impact of environmental taxes is more pronounced in the western regions of China than in the more industrially developed eastern and central regions. This suggests that environmental taxes contribute to reducing disparities in the development of the new energy industry across provinces.In conclusion, this paper confirms that green tax significantly promotes the development of China’s new energy industry. It holds practical significance in fostering vigorous growth in this sector while also helping to narrow regional industrial development gaps through tax policy.
Received: 26 July 2024 | Revised: 25 September 2024 | Accepted: 10 November 2024
Conflicts of Interest
The authors declare that they have no conflicts of interest to this work.
Data Availability Statement
The data used in this study are all publicly available and can also all be found within this database: https://www.wind.com.cn/portal/zh/EDB/index.html.
Author Contribution Statement
Baoshuai Yao: Conceptualization, Methodology, Software, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration, Funding acquisition. Changlin Li: Software, Formal analysis, Writing - review & editing. Rui Huang: Validation, Investigation, Resources.
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This work is licensed under a Creative Commons Attribution 4.0 International License.