IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i12p9332-d1167457.html
   My bibliography  Save this article

Spatial and Heterogeneity Analysis of Environmental Taxes’ Impact on China’s Green Economy Development: A Sustainable Development Perspective

Author

Listed:
  • Minye Rao

    (School of Public Administration, Fujian Normal University, Fuzhou 350007, China)

  • László Vasa

    (Faculty of Economics, Széchenyi Istvàn University, 9026 Győr, Hungary)

  • Yudan Xu

    (School of Public Administration, Fujian Normal University, Fuzhou 350007, China)

  • Pinghua Chen

    (School of Accounting, Fujian Jiangxia University, Fuzhou 350108, China)

Abstract

Environmental taxation is an important tool used by governments to promote resource conservation and environmental protection. Given the current global constraints on resources and increasing environmental degradation, exploring how environmental taxes can effectively stimulate the development of a green economy is of utmost importance. This study utilized panel data from 30 provinces, autonomous regions, and municipalities in China, covering the period from 2006 to 2020. The research findings indicate a spatial correlation between environmental taxes and green economic efficiency in China, with the former significantly promoting the development of the latter. A heterogeneity analysis revealed varying impacts of different taxes on the efficiency of green economic development in different regions. Controlling for variables, the study results demonstrated a negative correlation between industrial structure and green economic efficiency, with a significance level of 1%. Additionally, no correlation was found between pollution control efforts and green economic benefits. The effects of different taxes on regional efficiency varied, and industrial structure exhibited a negative correlation with green economic efficiency. This study recommends strengthening intergovernmental coordination, improving tax policies, optimizing industrial structure, and enhancing the pollution control efficiency of local governments to promote China’s green economy.

Suggested Citation

  • Minye Rao & László Vasa & Yudan Xu & Pinghua Chen, 2023. "Spatial and Heterogeneity Analysis of Environmental Taxes’ Impact on China’s Green Economy Development: A Sustainable Development Perspective," Sustainability, MDPI, vol. 15(12), pages 1-16, June.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:12:p:9332-:d:1167457
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/12/9332/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/12/9332/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mads Greaker & Tom‐Reiel Heggedal & Knut Einar Rosendahl, 2018. "Environmental Policy and the Direction of Technical Change," Scandinavian Journal of Economics, Wiley Blackwell, vol. 120(4), pages 1100-1138, October.
    2. Geng, Qianqian & Wang, Ying & Wang, Xiaoqing, 2023. "The impact of natural resource endowment and green finance on green economic efficiency in the context of COP26," Resources Policy, Elsevier, vol. 80(C).
    3. Yamazaki, Akio, 2022. "Environmental taxes and productivity: Lessons from Canadian manufacturing," Journal of Public Economics, Elsevier, vol. 205(C).
    4. Ian W. H. Parry & Kenneth A. Small, 2005. "Does Britain or the United States Have the Right Gasoline Tax?," American Economic Review, American Economic Association, vol. 95(4), pages 1276-1289, September.
    5. Zastempowski, Maciej, 2023. "Analysis and modeling of innovation factors to replace fossil fuels with renewable energy sources - Evidence from European Union enterprises," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    6. Ren, Qiuzhen & Albrecht, Johan, 2023. "Toward circular economy: The impact of policy instruments on circular economy innovation for European small medium enterprises," Ecological Economics, Elsevier, vol. 207(C).
    7. Rafique, Muhammad Zahid & Fareed, Zeeshan & Ferraz, Diogo & Ikram, Majid & Huang, Shaoan, 2022. "Exploring the heterogenous impacts of environmental taxes on environmental footprints: An empirical assessment from developed economies," Energy, Elsevier, vol. 238(PA).
    8. Tan, Junlan & Su, Xiang & Wang, Rong, 2023. "The impact of natural resource dependence and green finance on green economic growth in the context of COP26," Resources Policy, Elsevier, vol. 81(C).
    9. Zhao, Xin & Xu, Yong & Vasa, László & Shahzad, Umer, 2023. "Entrepreneurial ecosystem and urban innovation: Contextual findings in the lens of sustainable development from China," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    10. Zhao, Xin & Nakonieczny, Joanna & Jabeen, Fauzia & Shahzad, Umer & Jia, Wenxing, 2022. "Does green innovation induce green total factor productivity? Novel findings from Chinese city level data," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    11. Yang Shen & Xiuwu Zhang, 2022. "Study on the Impact of Environmental Tax on Industrial Green Transformation," IJERPH, MDPI, vol. 19(24), pages 1-18, December.
    12. Liu, Guangqiang & Yang, Zhiqing & Zhang, Fan & Zhang, Nan, 2022. "Environmental tax reform and environmental investment: A quasi-natural experiment based on China's Environmental Protection Tax Law," Energy Economics, Elsevier, vol. 109(C).
    13. Liu, Fangmei & Li, Li & Ye, Bin & Qin, Quande, 2023. "A novel stochastic semi-parametric frontier-based three-stage DEA window model to evaluate China's industrial green economic efficiency," Energy Economics, Elsevier, vol. 119(C).
    14. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    15. Zameer, Hashim & Yasmeen, Humaira & Zafar, Muhammad Wasif & Waheed, Abdul & Sinha, Avik, 2020. "Analyzing the association between Innovation, Economic Growth, and Environment: Divulging the Importance of FDI and Trade Openness in India," MPRA Paper 101323, University Library of Munich, Germany, revised 2020.
    16. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    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. Li Ji & Tian Zeng, 2022. "Environmental “Fee-to-Tax” and Heavy Pollution Enterprises to De-Capacity," Sustainability, MDPI, vol. 14(9), pages 1-24, April.
    2. Shao, Junli & Wu, Dengrong & Jin, Cheng, 2023. "How do financial inclusion and education increase resource efficiency?," Resources Policy, Elsevier, vol. 85(PA).
    3. Liang Liu & Yuhan Zhang & Xiujuan Gong & Mengyue Li & Xue Li & Donglin Ren & Pan Jiang, 2022. "Impact of Digital Economy Development on Carbon Emission Efficiency: A Spatial Econometric Analysis Based on Chinese Provinces and Cities," IJERPH, MDPI, vol. 19(22), pages 1-21, November.
    4. Yao, Shun & Li, Tongxin & Li, Ying, 2023. "Promoting sustainable fossil fuels resources in BRICS countries: Evaluating green policies and driving renewable energy development," Resources Policy, Elsevier, vol. 85(PA).
    5. Henryk Dzwigol & Aleksy Kwilinski & Oleksii Lyulyov & Tetyana Pimonenko, 2023. "The Role of Environmental Regulations, Renewable Energy, and Energy Efficiency in Finding the Path to Green Economic Growth," Energies, MDPI, vol. 16(7), pages 1-18, March.
    6. Kong, Yan & Dong, Chuntong & Zhang, Yingyu, 2023. "Quantile on Quantile Analysis of Natural resources-growth and geopolitical risk trilemma," Resources Policy, Elsevier, vol. 85(PA).
    7. Lan Yao & Zhenning Yu & Mengya Wu & Jiachen Ning & Tiangui Lv, 2020. "The Spatiotemporal Evolution and Trend Prediction of Ecological Wellbeing Performance in China," Land, MDPI, vol. 10(1), pages 1-17, December.
    8. Jinlin Li & Litai Chen & Ying Chen & Jiawen He, 2022. "Digital economy, technological innovation, and green economic efficiency—Empirical evidence from 277 cities in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(3), pages 616-629, April.
    9. Sohail Ahmad Javeed & Boon Heng Teh & Tze San Ong & Nguyen Thi Phuong Lan & Saravanan Muthaiyah & Rashid Latief, 2023. "The Connection between Absorptive Capacity and Green Innovation: The Function of Board Capital and Environmental Regulation," IJERPH, MDPI, vol. 20(4), pages 1-20, February.
    10. Wanzhe Chen & Jiaqi Liu & Xuanwei Ning & Lei Du & Yang Zhang & Chengliang Wu, 2023. "Low-Carbon City Building and Green Development: New Evidence from Quasi Natural Experiments from 277 Cities in China," Sustainability, MDPI, vol. 15(15), pages 1-28, July.
    11. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    12. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, April.
    13. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    14. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne, 2020. "Plant capacity notions in a non-parametric framework: a brief review and new graph or non-oriented plant capacities," Annals of Operations Research, Springer, vol. 288(2), pages 837-860, May.
    15. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    16. Juan Aparicio & Jesus T. Pastor & Jose L. Sainz-Pardo & Fernando Vidal, 2020. "Estimating and decomposing overall inefficiency by determining the least distance to the strongly efficient frontier in data envelopment analysis," Operational Research, Springer, vol. 20(2), pages 747-770, June.
    17. Börjesson, Maria & Asplund, Disa & Hamilton, Carl, 2021. "Optimal kilometre tax for electric passenger cars," Working Papers 2021:3, Swedish National Road & Transport Research Institute (VTI).
    18. Parry, Ian W.H., 2008. "How should heavy-duty trucks be taxed?," Journal of Urban Economics, Elsevier, vol. 63(2), pages 651-668, March.
    19. Bergeaud, Antonin & Raimbault, Juste, 2020. "An empirical analysis of the spatial variability of fuel prices in the United States," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 131-143.
    20. Vicente Rios Ibañez, 2014. "What drives regional unemployment convergence?," ERSA conference papers ersa14p924, European Regional Science Association.

    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:gam:jsusta:v:15:y:2023:i:12:p:9332-:d:1167457. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.