IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i20p9011-d1501185.html
   My bibliography  Save this article

Can Environmental Protection Tax Promote Urban Green Transformation? Experimental Evidence from China

Author

Listed:
  • Zhankun Qi

    (School of Management, Hangzhou Dianzi University, Hangzhou 310036, China
    The Center for Environmental Tax, Chinese Academy of Environmental Planning, Beijing 100041, China)

  • Feng Long

    (The Center for Environmental Tax, Chinese Academy of Environmental Planning, Beijing 100041, China
    National Joint Research Center for Ecological Conservation and High Quality Development of the Yellow River Basin, Beijing 100012, China)

  • Fenfen Bi

    (The Center for Environmental Tax, Chinese Academy of Environmental Planning, Beijing 100041, China
    National Joint Research Center for Ecological Conservation and High Quality Development of the Yellow River Basin, Beijing 100012, China)

  • Xue Tian

    (The Center for Environmental Tax, Chinese Academy of Environmental Planning, Beijing 100041, China
    National Joint Research Center for Ecological Conservation and High Quality Development of the Yellow River Basin, Beijing 100012, China)

  • Ziwei Qian

    (School of Management, Hangzhou Dianzi University, Hangzhou 310036, China
    The Center for Environmental Tax, Chinese Academy of Environmental Planning, Beijing 100041, China)

  • Xianming Duan

    (School of Management, Hangzhou Dianzi University, Hangzhou 310036, China)

  • Chazhong Ge

    (The Center for Environmental Tax, Chinese Academy of Environmental Planning, Beijing 100041, China)

Abstract

As one of China’s important environmental and economic policies, the environmental protection tax (EPT) is important in promoting economic and social green transformation. In this study, the green total factor productivity (GTFP) of 283 prefecture-level cities in China from 2013 to 2022 was calculated using a Super Slack-Based Model (Super-SBM) and the Malmquist-Luenberger (ML) index, which includes undesirable outputs. Moreover, the implementation effect of environmental tax on promoting urban green transformation is identified through the difference-in-differences (DID) model. This study revealed that (1) an EPT can significantly increase the GTFP of a city and promote its green transformation. (2) Industrial structure optimization and technological innovation are important mechanisms through which EPT drives urban green transformation. (3) The implementation effect of EPT in promoting urban green transformation presents significant policy differences across geographic locations, whether cities are key environmental protection cities or types of resource-based cities. EPT can significantly promote the green transformation of local cities, which in turn can positively affect the green transformation of neighboring cities. Based on this study’s conclusions, suggestions are put forward to improve the EPT system to promote urban green transformation.

Suggested Citation

  • Zhankun Qi & Feng Long & Fenfen Bi & Xue Tian & Ziwei Qian & Xianming Duan & Chazhong Ge, 2024. "Can Environmental Protection Tax Promote Urban Green Transformation? Experimental Evidence from China," Sustainability, MDPI, vol. 16(20), pages 1-17, October.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:9011-:d:1501185
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/20/9011/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/20/9011/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pereira, Alfredo M. & Pereira, Rui M. & Rodrigues, Pedro G., 2016. "A new carbon tax in Portugal: A missed opportunity to achieve the triple dividend?," Energy Policy, Elsevier, vol. 93(C), pages 110-118.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. Zhao, Aiwu & Wang, Jingyi & Sun, Zhenzhen & Guan, Hongjun, 2022. "Environmental taxes, technology innovation quality and firm performance in China—A test of effects based on the Porter hypothesis," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 309-325.
    4. Jinhua Sun & Decai Tang & Haojia Kong & Valentina Boamah, 2022. "Impact of Industrial Structure Upgrading on Green Total Factor Productivity in the Yangtze River Economic Belt," IJERPH, MDPI, vol. 19(6), pages 1-15, March.
    5. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    6. 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. Davtalab-Olyaie, Mostafa & Begen, Mehmet A. & Yang, Zijiang & Asgharian, Masoud, 2024. "Incentivization in centrally managed systems: Inconsistencies resolution," Omega, Elsevier, vol. 129(C).
    2. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    3. Suzuki, Soushi & Nijkamp, Peter, 2016. "An evaluation of energy-environment-economic efficiency for EU, APEC and ASEAN countries: Design of a Target-Oriented DFM model with fixed factors in Data Envelopment Analysis," Energy Policy, Elsevier, vol. 88(C), pages 100-112.
    4. Haixiang Xu & Rui Zhang, 2024. "Dynamic Analysis of Urban Land Use Efficiency in the Western Taiwan Strait Economic Zone," Land, MDPI, vol. 13(8), pages 1-26, August.
    5. Mousavi, Mohammad M. & Ouenniche, Jamal & Xu, Bing, 2015. "Performance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 64-75.
    6. Fan Wang & Lili Feng & Jin Li & Lin Wang, 2020. "Environmental Regulation, Tenure Length of Officials, and Green Innovation of Enterprises," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    7. Chia-Nan Wang & Jen-Der Day & Nguyen Thi Kim Lien & Luu Quoc Chien, 2018. "Integrating the Additive Seasonal Model and Super-SBM Model to Compute the Efficiency of Port Logistics Companies in Vietnam," Sustainability, MDPI, vol. 10(8), pages 1-17, August.
    8. Josef Jablonsky, 2022. "Individual and team efficiency: a case of the National Hockey League," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 479-494, June.
    9. Vicente J. Bolós & Rafael Benítez & Vicente Coll-Serrano, 2023. "Continuous models combining slacks-based measures of efficiency and super-efficiency," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(2), pages 363-391, June.
    10. Yung-ho Chiu & Chin-wei Huang & Chung-te Ting, 2012. "A non-radial measure of different systems for Taiwanese tourist hotels’ efficiency assessment," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(1), pages 45-63, March.
    11. Guo, I-Lung & Lee, Hsuan-Shih & Lee, Dan, 2017. "An integrated model for slack-based measure of super-efficiency in additive DEA," Omega, Elsevier, vol. 67(C), pages 160-167.
    12. Min Wang & Meng Ji & Xiaofen Wu & Kexin Deng & Xiaodong Jing, 2023. "Analysis on Evaluation and Spatial-Temporal Evolution of Port Cluster Eco-Efficiency: Case Study from the Yangtze River Delta in China," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    13. Jorge Guardiola & Andrés J. Picazo-Tadeo, 2013. "Weighting life domains with Data Envelopment Analysis," Working Papers 1311, Department of Applied Economics II, Universidad de Valencia.
    14. Huang, Hongyun & Wang, Fengrong & Song, Malin & Balezentis, Tomas & Streimikiene, Dalia, 2021. "Green innovations for sustainable development of China: Analysis based on the nested spatial panel models," Technology in Society, Elsevier, vol. 65(C).
    15. Zhen Shi & Huinan Huang & Yingju Wu & Yung-Ho Chiu & Shijiong Qin, 2020. "Climate Change Impacts on Agricultural Production and Crop Disaster Area in China," IJERPH, MDPI, vol. 17(13), pages 1-23, July.
    16. Ji, Xiang & Li, Guo & Wang, Zhaohua, 2017. "Impact of emission regulation policies on Chinese power firms’ reusable environmental investments and sustainable operations," Energy Policy, Elsevier, vol. 108(C), pages 163-177.
    17. Tran, Trung Hieu & Mao, Yong & Nathanail, Paul & Siebers, Peer-Olaf & Robinson, Darren, 2019. "Integrating slacks-based measure of efficiency and super-efficiency in data envelopment analysis," Omega, Elsevier, vol. 85(C), pages 156-165.
    18. Mahmoudi, Reza & Emrouznejad, Ali & Shetab-Boushehri, Seyyed-Nader & Hejazi, Seyed Reza, 2020. "The origins, development and future directions of data envelopment analysis approach in transportation systems," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    19. Soushi Suzuki & Karima Kourtit & Peter Nijkamp, 2017. "The robustness of performance rankings of Asia-Pacific super cities," Asia-Pacific Journal of Regional Science, Springer, vol. 1(1), pages 219-242, April.
    20. Kao, Chiang, 2019. "Inefficiency identification for closed series production systems," European Journal of Operational Research, Elsevier, vol. 275(2), pages 599-607.

    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:16:y:2024:i:20:p:9011-:d:1501185. 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.