IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i15p6940-d1713815.html
   My bibliography  Save this article

Can Technological Innovation in Renewable Energy Promote Carbon Emission Efficiency in China? A U-Shaped Relationship

Author

Listed:
  • Ruichen Yin

    (School of Economics and Finance, Hohai University, Nanjing 211100, China)

  • Haiying Pan

    (Business School, Hohai University, Nanjing 211100, China)

  • Yuqing Lu

    (School of Economics and Finance, Hohai University, Nanjing 211100, China)

Abstract

In the context of growing global climate change awareness and intensifying environmental degradation, technological innovation in renewable energy has become a key realization method for sustainable development. This paper uses data samples from 30 provinces, municipalities, and autonomous regions in China (excluding Tibet, Hong Kong, Macao, and Taiwan due to data availability) from 2007–2022, constructs an SFA model to measure carbon emission efficiency, and innovatively investigates the U-shaped impact of technological innovation in renewable energy on carbon emission efficiency along with the moderating effects of informatization level and fiscal decentralization. The empirical findings reveal the following: (1) Technological innovation in renewable energy demonstrates a U-shaped impact on carbon emission efficiency, with a negative impact before inflection point 2.596605 and a positive impact after the inflection point. (2) The informatization level plays a positive regulating role in the impact of technological innovation in renewable energy toward carbon emission efficiency, while fiscal decentralization exerts a negative regulating effect. (3) The impact of technological innovation in renewable energy concerning carbon emission efficiency varies depending on regional differences, industrial structure levels, and technological innovation levels in renewable energy. The conclusions of this paper are helpful for promoting the development of technological innovation in renewable energy, improving carbon emission efficiency, and advancing sustainable socio-economic development.

Suggested Citation

  • Ruichen Yin & Haiying Pan & Yuqing Lu, 2025. "Can Technological Innovation in Renewable Energy Promote Carbon Emission Efficiency in China? A U-Shaped Relationship," Sustainability, MDPI, vol. 17(15), pages 1-25, July.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:15:p:6940-:d:1713815
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/15/6940/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/15/6940/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Boyd, Gale A. & McClelland, John D., 1999. "The Impact of Environmental Constraints on Productivity Improvement in Integrated Paper Plants," Journal of Environmental Economics and Management, Elsevier, vol. 38(2), pages 121-142, September.
    2. Jingyi Wang & Kaisi Sun & Jiupai Ni & Deti Xie, 2021. "Evaluation and Factor Analysis of Industrial Carbon Emission Efficiency Based on “Green-Technology Efficiency”—The Case of Yangtze River Basin, China," Land, MDPI, vol. 10(12), pages 1-23, December.
    3. Yu Wang & Xudong Chen, 2024. "Impact Mechanism of Renewable Energy Technology Innovation on Carbon Productivity Based on Spatial Durbin Model," Sustainability, MDPI, vol. 16(5), pages 1-18, March.
    4. Razzaq, Asif & Wang, Yufeng & Chupradit, Supat & Suksatan, Wanich & Shahzad, Farrukh, 2021. "Asymmetric inter-linkages between green technology innovation and consumption-based carbon emissions in BRICS countries using quantile-on-quantile framework," Technology in Society, Elsevier, vol. 66(C).
    5. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    6. Zhu, Yuke & Lan, Mudan, 2023. "Digital economy and carbon rebound effect: Evidence from Chinese cities," Energy Economics, Elsevier, vol. 126(C).
    7. Wei, Danqi & Ahmad, Fayyaz & Chandio, Abbas Ali & Khan, Irfan, 2024. "Digital financial inclusion role to promote renewable energy technology innovation in Chinese prefectural cities: Moderating role of environmental governance," Renewable Energy, Elsevier, vol. 237(PB).
    8. Cai, Bofeng & Guo, Huanxiu & Ma, Zipeng & Wang, Zhixuan & Dhakal, Shobhakar & Cao, Libin, 2019. "Benchmarking carbon emissions efficiency in Chinese cities: A comparative study based on high-resolution gridded data," Applied Energy, Elsevier, vol. 242(C), pages 994-1009.
    9. 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).
    10. Martin Gaynor & Harald Seider & William B. Vogt, 2005. "The Volume–Outcome Effect, Scale Economies, and Learning-by-Doing," American Economic Review, American Economic Association, vol. 95(2), pages 243-247, May.
    11. Zhang, Ning & Huang, Xuhui & Qi, Chao, 2022. "The effect of environmental regulation on the marginal abatement cost of industrial firms: Evidence from the 11th Five-Year Plan in China," Energy Economics, Elsevier, vol. 112(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. Zhongrui Sun & Xianhong Cheng & Yumei Zhuang & Yong Sun, 2024. "Spatial correlation network structure characteristics of carbon emission efficiency and its influencing factors at city level in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(2), pages 5335-5366, February.
    2. Zhao, Qiuyun & Jiang, Mei & Zhao, Zuoxiang & Liu, Fan & Zhou, Li, 2024. "The impact of green innovation on carbon reduction efficiency in China: Evidence from machine learning validation," Energy Economics, Elsevier, vol. 133(C).
    3. Liu, Yeshen & Wang, Beibei & Song, Zhe, 2025. "Promoting or inhibiting: The impact of artificial intelligence application on corporate environmental performance," International Review of Financial Analysis, Elsevier, vol. 97(C).
    4. Chen, Fu & Wang, Liyun & Gu, Qiaojing & Wang, Mingyue & Ding, Xuanwen, 2022. "Nexus between natural resources, financial development, green innovation and environmental sustainability in China: Fresh insight from novel quantile ARDL," Resources Policy, Elsevier, vol. 79(C).
    5. Xia, Weifeng & Ruan, Zhiyu & Ma, Shenglin & Zhao, Jin & Yan, Jiale, 2025. "Can the digital economy enhance carbon emission efficiency? Evidence from 269 cities in China," International Review of Economics & Finance, Elsevier, vol. 97(C).
    6. Meng, Yue & Wu, Haoyue & Wang, Yunchen & Duan, Yinying, 2022. "International trade diversification, green innovation, and consumption-based carbon emissions: The role of renewable energy for sustainable development in BRICST countries," Renewable Energy, Elsevier, vol. 198(C), pages 1243-1253.
    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. Nam, Pham Khanh & Man, Pham Nhu & Thuy, Truong Dang, 2023. "Heterogeneity in Shadow Prices of Water Pollutants: A Study of the Seafood Processing Industry in Vietnam," EfD Discussion Paper 23-15, Environment for Development, University of Gothenburg.
    9. Bashir, Muhammad Adnan & Qing, Li & Razi, Ummara & Xi, Zhang & Jingting, Lin, 2025. "A green leap forward: Environmental efficiency amidst natural resource and technological shifts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 216(C).
    10. Lingjun Guo & Wenyu Tan & Yi Xu & Qinchen Tang, 2025. "Curbing regional carbon emissions through green technology innovation: an empirical analysis in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(4), pages 9477-9500, April.
    11. Roberto Balado‐Naves & María A. García‐Valiñas & David Roibás Alonso, 2025. "Assessing the efficiency of residential water demand: The role of information," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 47(2), pages 556-585, May.
    12. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499.
    13. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    14. António Afonso & Ana Patricia Montes & José M. Domínguez, 2024. "Measuring Tax Burden Efficiency in OECD Countries: An International Comparison," CESifo Working Paper Series 11333, CESifo.
    15. Barros, Carlos Pestana & Williams, Jonathan, 2013. "The random parameters stochastic frontier cost function and the effectiveness of public policy: Evidence from bank restructuring in Mexico," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 98-108.
    16. Ligia Alba Melo-Becerra & Luis E. Arango & Oscar Iván Ávila-Montealegre & Jhorland Ayala-García & Leonardo Bonilla-Mejía & Jesús Alonso Botero-García & Carolina Crispin-Fory & Manuela Cardona & Daniel, 2023. "Aspectos financieros y fiscales del sistema de salud en Colombia," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, issue 106, pages 1-92, October.
    17. Khanal, Aditya & Koirala, Krishna & Regmi, Madhav, "undated". "Do Financial Constraints Affect Production Efficiency in Drought Prone Areas? A Case from Indonesian Rice Growers," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230087, Southern Agricultural Economics Association.
    18. Firna Varina & Sri Hartoyo & Nunung Kusnadi & Amzul Rifin, 2020. "The Determinants of Technical Efficiency of Oil Palm Smallholders in Indonesia," International Journal of Economics and Financial Issues, Econjournals, vol. 10(6), pages 89-93.
    19. Victor Moutinho & Mara Madaleno, 2021. "Assessing Eco-Efficiency in Asian and African Countries Using Stochastic Frontier Analysis," Energies, MDPI, vol. 14(4), pages 1-17, February.
    20. Mohammed, Rezgar & Saghaian, Sayed, "undated". "Technical Efficiency Estimation of Rice Production in South Korea," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 162231, Southern Agricultural Economics Association.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:gam:jsusta:v:17:y:2025:i:15:p:6940-:d:1713815. 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.