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Influential Factors Regarding Carbon Emission Intensity in China: A Spatial Econometric Analysis from a Provincial Perspective

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  • Li-Ming Xue

    (Faculty of Energy & Mining, China University of Mining & Technology, Beijing (CUMTB), Beijing 100083, China
    These authors contributed equally to this work and should be considered co-first authors.)

  • Shuo Meng

    (Faculty of Energy & Mining, China University of Mining & Technology, Beijing (CUMTB), Beijing 100083, China
    These authors contributed equally to this work and should be considered co-first authors.)

  • Jia-Xing Wang

    (Faculty of Energy & Mining, China University of Mining & Technology, Beijing (CUMTB), Beijing 100083, China)

  • Lei Liu

    (Faculty of Energy & Mining, China University of Mining & Technology, Beijing (CUMTB), Beijing 100083, China)

  • Zhi-Xue Zheng

    (College of Engineering, Peking University, Beijing 100871, China)

Abstract

Emission reduction strategies based on provinces are key for China to mitigate its carbon emission intensity (CEI). As such, it is valuable to analyze the driving mechanism of CEI from a provincial view, and to explore a coordinated emission mitigation mechanism. Based on spatial econometrics, this study conducts a spatial-temporal effect analysis on CEI, and constructs a Spatial Durbin Model on the Panel data (SDPM) of CEI and its eight influential factors: GDP, urbanization rate (URB), industrial structure (INS), energy structure (ENS), energy intensity (ENI), technological innovation (TEL), openness level (OPL), and foreign direct investment (FDI). The main findings are as follows: (1) overall, there is a significant and upward trend of the spatial autocorrelation of CEI on 30 provinces in China. (2) The spatial spillover effect of CEI is positive, with a coefficient of 0.083. (3) The direct effects of ENI, ENS and TEL are significantly positive in descending order, while INS and GDP are significantly negative. The indirect effects of URB and ENS are significantly positive, while GDP, ENI, OPL and FDI are significantly negative in descending order. Economic and energy-related emission reduction measures are still crucial to the achievement of CEI reduction targets for provinces in China.

Suggested Citation

  • Li-Ming Xue & Shuo Meng & Jia-Xing Wang & Lei Liu & Zhi-Xue Zheng, 2020. "Influential Factors Regarding Carbon Emission Intensity in China: A Spatial Econometric Analysis from a Provincial Perspective," Sustainability, MDPI, vol. 12(19), pages 1-26, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:8097-:d:422373
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    as
    1. Azomahou, Theophile & Laisney, Francois & Nguyen Van, Phu, 2006. "Economic development and CO2 emissions: A nonparametric panel approach," Journal of Public Economics, Elsevier, vol. 90(6-7), pages 1347-1363, August.
    2. Grossman, G.M & Krueger, A.B., 1991. "Environmental Impacts of a North American Free Trade Agreement," Papers 158, Princeton, Woodrow Wilson School - Public and International Affairs.
    3. Pretis, Felix & Roser, Max, 2017. "Carbon dioxide emission-intensity in climate projections: Comparing the observational record to socio-economic scenarios," Energy, Elsevier, vol. 135(C), pages 718-725.
    4. J. Paul Elhorst, 2014. "Spatial Panel Data Models," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 37-93, Springer.
    5. Yujiao Xian & Ke Wang & Xunpeng Shi & Chi Zhang & Yi-Ming Wei & Zhimin Huang, 2018. "Carbon emissions intensity reduction target for China¡¯s power industry: An efficiency and productivity perspective," CEEP-BIT Working Papers 117, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    6. Hubert Jayet & Julie Le Gallo & Luc Anselin, 2008. "Spatial Econometrics and Panel Data Models," Post-Print hal-02389412, HAL.
    7. Abdallh, Atif Awad & Abugamos, Hoda, 2017. "A semi-parametric panel data analysis on the urbanisation-carbon emissions nexus for the MENA countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1350-1356.
    8. Yang, Xue & Su, Bin, 2019. "Impacts of international export on global and regional carbon intensity," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    9. Cui, Lian-Biao & Fan, Ying & Zhu, Lei & Bi, Qing-Hua, 2014. "How will the emissions trading scheme save cost for achieving China’s 2020 carbon intensity reduction target?," Applied Energy, Elsevier, vol. 136(C), pages 1043-1052.
    10. Kwon, Tae-Hyeong, 2005. "Decomposition of factors determining the trend of CO2 emissions from car travel in Great Britain (1970-2000)," Ecological Economics, Elsevier, vol. 53(2), pages 261-275, April.
    11. Chang, Chun-Ping & Dong, Minyi & Sui, Bo & Chu, Yin, 2019. "Driving forces of global carbon emissions: From time- and spatial-dynamic perspectives," Economic Modelling, Elsevier, vol. 77(C), pages 70-80.
    12. Sapkota, Pratikshya & Bastola, Umesh, 2017. "Foreign direct investment, income, and environmental pollution in developing countries: Panel data analysis of Latin America," Energy Economics, Elsevier, vol. 64(C), pages 206-212.
    13. Robaina Alves, Margarita & Moutinho, Victor, 2013. "Decomposition analysis and Innovative Accounting Approach for energy-related CO2 (carbon dioxide) emissions intensity over 1996–2009 in Portugal," Energy, Elsevier, vol. 57(C), pages 775-787.
    14. Vujović, Tanja & Petković, Zdravka & Pavlović, Miloš & Jović, Srdjan, 2018. "Economic growth based in carbon dioxide emission intensity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 179-185.
    15. De Oliveira-De Jesus, Paulo M., 2019. "Effect of generation capacity factors on carbon emission intensity of electricity of Latin America & the Caribbean, a temporal IDA-LMDI analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 516-526.
    16. Wang, Shaojian & Wang, Jieyu & Fang, Chuanglin & Feng, Kuishuang, 2019. "Inequalities in carbon intensity in China: A multi-scalar and multi-mechanism analysis," Applied Energy, Elsevier, vol. 254(C).
    17. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    18. Jeffrey, Cynthia & Perkins, Jon D., 2015. "Reply to Discussion of “The Association between Energy Taxation, Participation in an Emissions Trading System, and the Intensity of Carbon Dioxide Emissions in the European Union”," The International Journal of Accounting, Elsevier, vol. 50(4), pages 427-434.
    19. Jeffrey, Cynthia & Perkins, Jon D., 2015. "The association between energy taxation, participation in an emissions trading system, and the intensity of carbon dioxide emissions in the European Union," The International Journal of Accounting, Elsevier, vol. 50(4), pages 397-417.
    20. Li, Wei & Sun, Wen & Li, Guomin & Jin, Baihui & Wu, Wen & Cui, Pengfei & Zhao, Guohao, 2018. "Transmission mechanism between energy prices and carbon emissions using geographically weighted regression," Energy Policy, Elsevier, vol. 115(C), pages 434-442.
    21. Ahmad, Ashfaq & Zhao, Yuhuan & Shahbaz, Muhammad & Bano, Sadia & Zhang, Zhonghua & Wang, Song & Liu, Ya, 2016. "Carbon emissions, energy consumption and economic growth: An aggregate and disaggregate analysis of the Indian economy," Energy Policy, Elsevier, vol. 96(C), pages 131-143.
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