IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v26y2024i12d10.1007_s10668-024-04655-w.html
   My bibliography  Save this article

Does environmental pollution governance contribute to carbon emission reduction under heterogeneous green technological innovation? Empirical evidence from China’s provincial panel data

Author

Listed:
  • Jianzhong Xu

    (Harbin Engineering University)

  • Bingjun Tong

    (Harbin Engineering University)

  • Manman Wang

    (Zhengzhou University of Light Industry)

  • Shi Yin

    (Hebei Agricultural University)

Abstract

With the rapidly developing global economy, CO2 emissions (CE) have become an important factor in global climate change. Ecological issues have received considerable attention worldwide. Environmental pollution governance (EPG) and green technological innovation (GTI) are important ways to reduce CE. However, there is relatively little empirical research on the relationship among GTI, EPG, and CE. Therefore, this study aimed to explore the role of GTI and EPG in reducing CE in China. This study used a spatial econometric model and threshold regression model to empirically analyze the relationship between EPG, different types of GTI, and CE. The empirical results showed a significant positive spatial spillover effect of CE in China under the adjacency weight matrix. EPG and different types of GTI have a significant inhibitory effect on CE; however, EPG has a stronger inhibitory effect on CE reduction than that of GTI. Inventive and improved GTI are two types of triple thresholds between EPG and CE. The impact of EPG on CE has spatial and temporal differences in the level of regional inventive/improved GTI, showing a trend in which the region gradually crosses from a low GTI level to medium and high GTI levels. These findings provide important insights for China and other developing countries to achieve development goals, implement GTI policies, and reduce CE.

Suggested Citation

  • Jianzhong Xu & Bingjun Tong & Manman Wang & Shi Yin, 2024. "Does environmental pollution governance contribute to carbon emission reduction under heterogeneous green technological innovation? Empirical evidence from China’s provincial panel data," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(12), pages 31727-31756, December.
  • Handle: RePEc:spr:endesu:v:26:y:2024:i:12:d:10.1007_s10668-024-04655-w
    DOI: 10.1007/s10668-024-04655-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-024-04655-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10668-024-04655-w?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Du, Gang & Yu, Meng & Sun, Chuanwang & Han, Zhao, 2021. "Green innovation effect of emission trading policy on pilot areas and neighboring areas: An analysis based on the spatial econometric model," Energy Policy, Elsevier, vol. 156(C).
    2. Wu, Haitao & Xu, Lina & Ren, Siyu & Hao, Yu & Yan, Guoyao, 2020. "How do energy consumption and environmental regulation affect carbon emissions in China? New evidence from a dynamic threshold panel model," Resources Policy, Elsevier, vol. 67(C).
    3. Wang, Keying & Wu, Meng & Sun, Yongping & Shi, Xunpeng & Sun, Ao & Zhang, Ping, 2019. "Resource abundance, industrial structure, and regional carbon emissions efficiency in China," Resources Policy, Elsevier, vol. 60(C), pages 203-214.
    4. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    5. Kuang, Hewu & Akmal, Zeeshan & Li, Feifei, 2022. "Measuring the effects of green technology innovations and renewable energy investment for reducing carbon emissions in China," Renewable Energy, Elsevier, vol. 197(C), pages 1-10.
    6. Xu, Le & Fan, Meiting & Yang, Lili & Shao, Shuai, 2021. "Heterogeneous green innovations and carbon emission performance: Evidence at China's city level," Energy Economics, Elsevier, vol. 99(C).
    7. Chen, Huanyu & Yi, Jizheng & Chen, Aibin & Peng, Duanxiang & Yang, Jieqiong, 2023. "Green technology innovation and CO2 emission in China: Evidence from a spatial-temporal analysis and a nonlinear spatial durbin model," Energy Policy, Elsevier, vol. 172(C).
    8. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    9. J. Paul Elhorst, 2014. "Matlab Software for Spatial Panels," International Regional Science Review, , vol. 37(3), pages 389-405, July.
    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. Zhang, Wei & Liu, Xuemeng & Wang, Die & Zhou, Jianping, 2022. "Digital economy and carbon emission performance: Evidence at China's city level," Energy Policy, Elsevier, vol. 165(C).
    2. Shao, Hanhua & Wang, Yaning & Wen, Huwei, 2024. "Investigating the carbon curse of natural resource dependence: A carbon trading scheme," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 769-783.
    3. Litu Sethi & Biswanath Behera & Narayan Sethi, 2024. "Do green finance, green technology innovation, and institutional quality help achieve environmental sustainability? Evidence from the developing economies," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(3), pages 2709-2723, June.
    4. Wang, Kai-Hua & Wen, Cui-Ping & Xu, Bao-Chang & Li, Xin, 2024. "Receiver or transmitter? Unlocking the role of green technology innovation in sustainable development, energy, and carbon markets," Technology in Society, Elsevier, vol. 79(C).
    5. Hongyang Yu & Jiajun Xu & Hui Hu & Xunpeng Shi & Jinchao Wang & Yanli Liu, 2024. "How does green technology innovation influence industrial structure? Evidence of heterogeneous environmental regulation effects," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(7), pages 17875-17903, July.
    6. Yuxi Chen & Mengting Zhang & Chencheng Wang & Xin Lin & Zhijie Zhang, 2023. "High-Tech Industrial Agglomeration, Government Intervention and Regional Energy Efficiency: Based on the Perspective of the Spatial Spillover Effect and Panel Threshold Effect," Sustainability, MDPI, vol. 15(7), pages 1-29, April.
    7. Zhijie Hao & Ziqian Zhao & Zhiwei Pan & Decai Tang & Meiling Zhao & Hui Zhang, 2025. "Spatial Effects of Financial Agglomeration and Green Technological Innovation on Carbon Emissions," Sustainability, MDPI, vol. 17(6), pages 1-34, March.
    8. Xianpu Xu & Bijiao Yi, 2022. "New Insights into the Impact of Local Corruption on China’s Regional Carbon Emissions Performance Based on the Spatial Spillover Effects," Sustainability, MDPI, vol. 14(22), pages 1-26, November.
    9. Zhao, Mingxuan & Lv, Lianhong & Wu, Jing & Wang, Shen & Zhang, Nan & Bai, Zihan & Luo, Hong, 2022. "Total factor productivity of high coal-consuming industries and provincial coal consumption: Based on the dynamic spatial Durbin model," Energy, Elsevier, vol. 251(C).
    10. Lin, Boqiang & Ullah, Sami, 2023. "Towards the goal of going green: Do green growth and innovation matter for environmental sustainability in Pakistan," Energy, Elsevier, vol. 285(C).
    11. Zhao, Shikuan & Cao, Yuequn & Hunjra, Ahmed Imran & Tan, Yan, 2023. "How does environmentally induced R&D affect carbon productivity? A government support perspective," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 942-961.
    12. Haller, Peter & Heuermann, Daniel F., 2016. "Job search and hiring in local labor markets: Spillovers in regional matching functions," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 125-138.
    13. Yuan, Huaxi & Feng, Yidai & Lee, Chien-Chiang & Cen, Yan, 2020. "How does manufacturing agglomeration affect green economic efficiency?," Energy Economics, Elsevier, vol. 92(C).
    14. Xiaohang Zhai & Zhe Chen & Chunlan Tan & Guangliang Li, 2023. "Heterogeneity Analysis of Industrial Structure Upgrading on Eco-Environmental Quality from a Spatial Perspective: Evidence from 11 Coastal Provinces in China," Sustainability, MDPI, vol. 15(21), pages 1-22, October.
    15. Senlin Hu & Gang Zeng & Xianzhong Cao & Huaxi Yuan & Bing Chen, 2021. "Does Technological Innovation Promote Green Development? A Case Study of the Yangtze River Economic Belt in China," IJERPH, MDPI, vol. 18(11), pages 1-18, June.
    16. Sheng, Jichuan & Qiu, Wenge, 2022. "Water-use technical efficiency and income: Evidence from China's South-North Water Transfer Project," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    17. Bingtao Qin & Yulu Gai & Liming Ge & Pengbo Sun & Yongwei Yu & Yi Zheng, 2022. "FDI, Technology Spillovers, and Green Innovation: Theoretical Analysis and Evidence from China," Energies, MDPI, vol. 15(20), pages 1-25, October.
    18. Dechun Liu & Xinye Zheng & Yihua Yu, 2022. "Public Debt Competition in Local China: Evidence and Mechanism of Spatial Interactions," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S2), pages 91-105, November.
    19. Fang Qu & Wensen She, 2025. "Artificial Intelligence Technology and Regional Carbon Emission Performance: Does Energy Transition or Industrial Transformation Matter?," Sustainability, MDPI, vol. 17(5), pages 1-31, February.
    20. Xinye Zheng & Feng Song & Yihua Yu & Shunfeng Song, 2015. "In Search of Fiscal Interactions: A Spatial Analysis of Chinese Provincial Infrastructure Spending," Review of Development Economics, Wiley Blackwell, vol. 19(4), pages 860-876, November.

    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:spr:endesu:v:26:y:2024:i:12:d:10.1007_s10668-024-04655-w. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.