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Impact of Heterogeneous Environmental Regulations on Green Innovation Efficiency in China’s Industry

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  • Junfang Hao

    (The Research Center of Energy Economy, School of Business Administration, Henan Polytechnic University, Jiaozuo 454003, China)

  • Wanqiang Xu

    (College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Zhuo Chen

    (The Research Center of Energy Economy, School of Business Administration, Henan Polytechnic University, Jiaozuo 454003, China)

  • Baiyun Yuan

    (The Research Center of Energy Economy, School of Business Administration, Henan Polytechnic University, Jiaozuo 454003, China)

  • Yuping Wu

    (The Research Center of Energy Economy, School of Business Administration, Henan Polytechnic University, Jiaozuo 454003, China)

Abstract

Innovation is the primary driving force for development, and green innovation efficiency (GIE) plays a key role in regional sustainable development. Moreover, environmental regulations (ERs) are also crucial for innovation and green transformation. Considering the heterogeneity of ERs, we assess the dynamic GIE in the industrial sectors of China. We detect their spatial clustering characteristics, and distinguish the impacts of ERs. Results suggest that there exist significant differences in GIE. Provinces such as Hainan, Guangdong and Zhejiang are ranked high, while Gansu, Inner Mongolia and Ningxia are ranked at the bottom, which shows some spatial dependence. The relationship between the administrative regulation and GIE demonstrates a U-shape, and has not reached a critical point, whereas the relationship between the market-based regulation and GIE possesses an inverted U-shape, which is highly significant. Furthermore, a positive linear relationship exists between the lagged public participation regulation and GIE. This paper also proposes that the economic development level and industrial structure are vital factors in accelerating industrial GIE. These conclusions provide scientific support for formulating regional transformation strategies.

Suggested Citation

  • Junfang Hao & Wanqiang Xu & Zhuo Chen & Baiyun Yuan & Yuping Wu, 2024. "Impact of Heterogeneous Environmental Regulations on Green Innovation Efficiency in China’s Industry," Sustainability, MDPI, vol. 16(1), pages 1-16, January.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:1:p:415-:d:1312369
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    References listed on IDEAS

    as
    1. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    2. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    3. Erik Hille & Patrick Möbius, 2019. "Environmental Policy, Innovation, and Productivity Growth: Controlling the Effects of Regulation and Endogeneity," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(4), pages 1315-1355, August.
    4. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    5. 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.
    6. Wang, Juan & Hu, Mingming & Rodrigues, João F.D., 2018. "The evolution and driving forces of industrial aggregate energy intensity in China: An extended decomposition analysis," Applied Energy, Elsevier, vol. 228(C), pages 2195-2206.
    7. Wanfang Shen & Jianing Shi & Qinggang Meng & Xiaolan Chen & Yufei Liu & Ken Cheng & Wenbin Liu, 2022. "Influences of Environmental Regulations on Industrial Green Technology Innovation Efficiency in China," Sustainability, MDPI, vol. 14(8), pages 1-25, April.
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