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Driving Factors and Growth Potential of Provincial Carbon Productivity in China

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  • Miaomiao Niu

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
    School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Xianchun Tan

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
    School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jianxin Guo

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
    School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Guohao Li

    (Business School, Sichuan University, Chengdu 610064, China)

  • Chen Huang

    (School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Climate change has become a global concern, and the development of a green economy has attracted wide attention. Understanding the driving factors and growth potential of provincial-level carbon productivity is crucial for China’s green economic development in the new normal phase. In this study, the logarithmic mean Divisia index (LMDI) is adopted to systematically investigate the driving factors of provincial carbon productivity and explore the growth potential of provinces’ carbon productivity based on the clustering analysis. The results show that: (1) China’s provincial carbon productivity presents an increasing trend in 2001–2017, but the differences in carbon productivity among provinces are widening. (2) Economic activity and industrial structure are key to push up regional carbon productivity in China, while energy intensity is the main factor pulling it down. (3) The potential for carbon productivity improvement varies greatly among provinces in the four groups. Specifically, in groups 1 and 2, the developed provinces have little potential for improving carbon productivity, while the developing provinces in group 4 are just the opposite. These findings can enlighten policymakers that the development of a green economy should focus on optimizing and upgrading industrial structure and reducing energy intensity, and provincial heterogeneity must be considered when formulating green economic development policies.

Suggested Citation

  • Miaomiao Niu & Xianchun Tan & Jianxin Guo & Guohao Li & Chen Huang, 2021. "Driving Factors and Growth Potential of Provincial Carbon Productivity in China," Sustainability, MDPI, vol. 13(17), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:17:p:9759-:d:625723
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    References listed on IDEAS

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    1. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    2. Ralf Martin & Mirabelle Muûls & Ulrich J. Wagner, 2016. "The Impact of the European Union Emissions Trading Scheme on Regulated Firms: What Is the Evidence after Ten Years?," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 10(1), pages 129-148.
    3. Oestreich, A. Marcel & Tsiakas, Ilias, 2015. "Carbon emissions and stock returns: Evidence from the EU Emissions Trading Scheme," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 294-308.
    4. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    5. Pietzcker, Robert C. & Osorio, Sebastian & Rodrigues, Renato, 2021. "Tightening EU ETS targets in line with the European Green Deal: Impacts on the decarbonization of the EU power sector," Applied Energy, Elsevier, vol. 293(C).
    6. B. W. Ang & Ki-Hong Choi, 1997. "Decomposition of Aggregate Energy and Gas Emission Intensities for Industry: A Refined Divisia Index Method," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 59-73.
    7. Ang, B.W. & Zhang, F.Q., 2000. "A survey of index decomposition analysis in energy and environmental studies," Energy, Elsevier, vol. 25(12), pages 1149-1176.
    8. Long, Ruyin & Shao, Tianxiang & Chen, Hong, 2016. "Spatial econometric analysis of China’s province-level industrial carbon productivity and its influencing factors," Applied Energy, Elsevier, vol. 166(C), pages 210-219.
    9. Jianchang Lu & Weiguo Fan & Ming Meng, 2015. "Empirical Research on China’s Carbon Productivity Decomposition Model Based on Multi-Dimensional Factors," Energies, MDPI, vol. 8(4), pages 1-25, April.
    10. Pietzcker, Robert & Osorio, Sebastian & Rodrigues, Renato, 2021. "Tightening EU ETS targets in line with the European Green Deal: Impacts on the decarbonization of the EU power sector," EconStor Preprints 222579, ZBW - Leibniz Information Centre for Economics, revised 2021.
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    Cited by:

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    2. Wenhao Qi & Changxing Song & Meng Sun & Liguo Wang & Youcheng Han, 2022. "Sustainable Growth Drivers: Unveiling the Role Played by Carbon Productivity," IJERPH, MDPI, vol. 19(3), pages 1-25, January.
    3. Meng Sun & Yue Zhang & Yaqi Hu & Jiayi Zhang, 2022. "Spatial Convergence of Carbon Productivity: Theoretical Analysis and Chinese Experience," IJERPH, MDPI, vol. 19(8), pages 1-19, April.

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