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Assessing energy poverty and its effect on CO2 emissions: The case of China

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  • Zhao, Jun
  • Jiang, Qingzhe
  • Dong, Xiucheng
  • Dong, Kangyin

Abstract

With scholars paying increasing attention to the environmental effects of energy poverty, further discussion on the energy poverty-CO2 nexus is particularly useful for achieving carbon reduction targets from the perspective of energy poverty. Accordingly, this paper investigates the dynamic impact of energy poverty on CO2 emissions in China. By proposing a new and comprehensive evaluation index, we assess the energy poverty levels in 30 Chinese provinces for the period 2002–2017. Then, we re-estimate the impact of energy poverty on CO2 emissions using the system-generalized method of moments (SYS-GMM) method. We find that although significant differences exist in energy poverty across various regions in China, the country's total level of energy poverty displays a downward trend over the period 2002–2017. Furthermore, energy poverty can accelerate the growth of CO2 emissions in China. In regions with high-level energy poverty, a bidirectional causal link exists between energy poverty and CO2 emissions, while a unidirectional causality runs from energy poverty to CO2 emissions in regions with low-level energy poverty. The findings of this paper, therefore, add to the existing literature and provide important policy implications for curbing CO2 emissions.

Suggested Citation

  • Zhao, Jun & Jiang, Qingzhe & Dong, Xiucheng & Dong, Kangyin, 2021. "Assessing energy poverty and its effect on CO2 emissions: The case of China," Energy Economics, Elsevier, vol. 97(C).
  • Handle: RePEc:eee:eneeco:v:97:y:2021:i:c:s0140988321000967
    DOI: 10.1016/j.eneco.2021.105191
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    More about this item

    Keywords

    Energy poverty; CO2 emissions; SYS-GMM estimation; Heterogeneity and asymmetry; China;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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