IDEAS home Printed from https://ideas.repec.org/a/aiy/jnljtr/v11y2025i1p149-174.html
   My bibliography  Save this article

Can Environmental Protection Tax Reform Promote Green Comprehensive Efficiency Productivity? Evidence from China’s Provincial Panel Data

Author

Listed:
  • Ye Chenghao
  • Igor A. Mayburov
  • Gao Hongjie

Abstract

This study is based on China’s provincial panel data from 2013 to 2022, using the Super-SBM and Difference-in-Difference (DID) Model, combined with SPSSAU online statistical calculator, Stata18.0 and Python3.12 software for econometric analysis, to explore the impact of environmental protection tax reform (EPTR) on provincial green comprehensive efficiency productivity (GCEP) and its internal mechanism. To ensure the rigor of the research, the GCEP measurement index based on the Super-SBM Model was first constructed. Furthermore, the mediating effect model is used to test the role of electricity productivity in the impact of EPTR. The empirical results show that the implementation of EPTR has significantly improved the GCEP of the pilot areas, and this improvement effect shows a trend of gradual and significant enhancement in the later stage of the policy implementation. The GCEP analysis by region shows that the GCEP is higher in the eastern and coastal provinces, while the GCEP is relatively lower in the central and western regions. When the measurement method of core variables is changed and the variable analysis of independent years is carried out, the robust results support the core conclusion that the environmental protection tax reform has a positive impact on GCEP. The mechanism analysis shows that there is a positive correlation between EPTR and regional power generation, and a negative correlation between power generation and GCEP. This study not only provides a scientific basis for the evaluation of EPTR, but also provides a reference for other countries to explore the policy design of market-based means to promote green development.

Suggested Citation

  • Ye Chenghao & Igor A. Mayburov & Gao Hongjie, 2025. "Can Environmental Protection Tax Reform Promote Green Comprehensive Efficiency Productivity? Evidence from China’s Provincial Panel Data," Journal of Tax Reform, Graduate School of Economics and Management, Ural Federal University, vol. 11(1), pages 149-174.
    • Handle: RePEc:aiy:jnljtr:v:11:y:2025:i:1:p:149-174
    DOI: https://doi.org/10.15826/jtr.2025.11.1.196
    as

    Download full text from publisher

    File URL: https://taxreform.ru//fileadmin/user_upload/site_15907/2025/08-Chenghao_et_al.pdf
    Download Restriction: no
    File URL: https://libkey.io/https://doi.org/10.15826/jtr.2025.11.1.196?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Cheng, Yue & Zhao, Gongyan & Meng, Wentao & Wang, Qianrong, 2024. "Resources utilization, taxation and green education: A path to sustainable power generation," Resources Policy, Elsevier, vol. 88(C).
    2. Wu, Haitao & Hao, Yu & Weng, Jia-Hsi, 2019. "How does energy consumption affect China's urbanization? New evidence from dynamic threshold panel models," Energy Policy, Elsevier, vol. 127(C), pages 24-38.
    3. Yang, Siying & Liu, Fengshuo, 2024. "Impact of industrial intelligence on green total factor productivity: The indispensability of the environmental system," Ecological Economics, Elsevier, vol. 216(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhai, Ying & Wang, Wenzhi & Zhou, Liying, 2024. "Green efficiency loss caused by economic growth goals: Evidence from an emerging economy," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 983-995.
    2. Junhong Qu & Xiaoli Hao, 2022. "Digital Economy, Financial Development, and Energy Poverty Based on Mediating Effects and a Spatial Autocorrelation Model," Sustainability, MDPI, vol. 14(15), pages 1-24, July.
    3. Ren, Siyu & Hao, Yu & Xu, Lu & Wu, Haitao & Ba, Ning, 2021. "Digitalization and energy: How does internet development affect China's energy consumption?," Energy Economics, Elsevier, vol. 98(C).
    4. Chen, Zhenling & Zhao, Weigang & Zheng, Heyun, 2021. "Potential output gap in China's regional coal-fired power sector under the constraint of carbon emission reduction," Energy Policy, Elsevier, vol. 148(PA).
    5. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    6. Wu, Haitao & Ba, Ning & Ren, Siyu & Xu, Lu & Chai, Jingxia & Irfan, Muhammad & Hao, Yu & Lu, Zhi-Nan, 2022. "The impact of internet development on the health of Chinese residents: Transmission mechanisms and empirical tests," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    7. Luping Shi & Zhongyao Cai & Xuhui Ding & Rong Di & Qianqian Xiao, 2020. "What Factors Affect the Level of Green Urbanization in the Yellow River Basin in the Context of New-Type Urbanization?," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    8. Ren Wang & Yuxiang Bian & Han Gao & Jie Hou, 2023. "Optimal Environmental Policy for Heterogeneous Governments in China," IJERPH, MDPI, vol. 20(4), pages 1-12, February.
    9. Zhu, Bangzhu & Chen, Gang & Wang, Ping, 2024. "How does green fiscal policy promote the synergy of pollution mitigation and carbon reduction? Evidence from China," Energy, Elsevier, vol. 313(C).
    10. Li, Pin & He, Qi & Zhang, Jinsuo & Xia, Qiyuan, 2024. "Analyzing the impact of energy synergy and renewable energy generation on energy security: Empirical evidence from China's Yangtze River Delta region," Energy, Elsevier, vol. 302(C).
    11. Setareh Katircioglu, 2022. "Estimating the role of urban development in environment quality: Evidence from G7 countries," Energy & Environment, , vol. 33(2), pages 283-314, March.
    12. Wu, Wanlu & Cheng, Yuanyuan & Lin, Xiqiao & Yao, Xin, 2019. "How does the implementation of the Policy of Electricity Substitution influence green economic growth in China?," Energy Policy, Elsevier, vol. 131(C), pages 251-261.
    13. Yu, Yantuan & Zhang, Ning & Kim, Jong Dae, 2020. "Impact of urbanization on energy demand: An empirical study of the Yangtze River Economic Belt in China," Energy Policy, Elsevier, vol. 139(C).
    14. Weixiang Zhao & Yankun Xu, 2022. "Public Expenditure and Green Total Factor Productivity: Evidence from Chinese Prefecture-Level Cities," IJERPH, MDPI, vol. 19(9), pages 1-27, May.
    15. Kun Wang & Yingkai Tang & Yaozhi Chen & Longwen Shang & Xuanming Ji & Mengchao Yao & Ping Wang, 2020. "The Coupling and Coordinated Development from Urban Land Using Benefits and Urbanization Level: Case Study from Fujian Province (China)," IJERPH, MDPI, vol. 17(16), pages 1-18, August.
    16. Lee, Chien-Chiang & Wang, Chang-song, 2022. "Financial development, technological innovation and energy security: Evidence from Chinese provincial experience," Energy Economics, Elsevier, vol. 112(C).
    17. Jacques Simon Song & Thierry Messie Pondie & Loudi Njoya, 2024. "Urbanization in Africa: Does Energy Poverty Matter?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 11750-11783, September.
    18. Fu, Tong & Qiu, Zhaoxuan & Yang, Xiangyang & Li, Zijun, 2024. "The impact of artificial intelligence on green technology cycles in China," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    19. Feng, Suling & Sui, Bo & Liu, Huimin & Li, Guoxiang, 2020. "Environmental decentralization and innovation in China," Economic Modelling, Elsevier, vol. 93(C), pages 660-674.
    20. Huang, Junbing & Wang, Yajun & Guo, Lili, 2022. "Energy intensity and energy-specific technological progress: A case study in Guangdong province of China," Renewable Energy, Elsevier, vol. 184(C), pages 990-1001.

    More about this item

    Keywords

    China; Environmental Protection Tax Reform (EPTR); Green Comprehensive Efficiency Productivity (GCEP); Super-SBM Model; Difference-in-Difference Model (DID);
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aiy:jnljtr:v:11:y:2025:i:1:p:149-174. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Natalia Starodubets (email available below). General contact details of provider: https://edirc.repec.org/data/seurfru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.