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Industrial Carbon Emissions of China’s Regions: A Spatial Econometric Analysis

Author

Listed:
  • Yu Liu

    (Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, China)

  • Hongwei Xiao

    (Economic Forecasting Department, State Information Center, Beijing 100045, China)

  • Ning Zhang

    (School of Economics, Jinan University, Guangzhou 510632, China)

Abstract

This paper proposes an extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to investigate the factors driving industrial carbon emissions in China. In the first stage, a spatial Durbin model is applied to investigate the determinants of regional industrial carbon emissions. In the second stage, a geographically and temporally weighted regression is applied to investigate temporal and spatial variations in the impacts of these driving factors on the scale and intensity of regional industrial carbon emissions. The empirical results suggest that the provinces with low carbon emissions act as exemplars for those with high carbon emissions and that driving factors impact carbon emission both directly and indirectly. All of the factors were investigated, except energy intensity, energy price, and openness, significantly impact carbon emissions. Overall, the results suggest that spatial correlation, heterogeneity, and spillover effects should be taken into account when formulating policies aiming at reducing industrial carbon emissions. The paper concludes with relevant policy recommendations taking full account of the regional industrial carbon emissions, heterogeneity and spillover.

Suggested Citation

  • Yu Liu & Hongwei Xiao & Ning Zhang, 2016. "Industrial Carbon Emissions of China’s Regions: A Spatial Econometric Analysis," Sustainability, MDPI, vol. 8(3), pages 1-14, February.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:3:p:210-:d:64706
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    References listed on IDEAS

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    Cited by:

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