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Does low-carbon energy transition mitigate energy poverty? The case of natural gas for China

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  • Dong, Kangyin
  • Jiang, Qingzhe
  • Shahbaz, Muhammad
  • Zhao, Jun

Abstract

Low-carbon energy transition has promoted China's green and sustainable development; however, it will be hindered by energy poverty. To investigate whether low-carbon energy transition can mitigate the energy poverty, based on panel data of China's 30 provinces covering the period of 2004–2017, this study investigates the impact of natural gas consumption (NGC) on China's energy poverty by employing the differential generalized method of moments (D-GMM) as the benchmark method. For this purpose, China's energy poverty is assessed by constructing a composite index that includes four sub-indices. We also analyze the influencing mechanism and heterogeneous impact of NGC on energy poverty. The overall estimation results imply that the impact of NGC on China's energy poverty is significantly negative; in other words, increased NGC can effectively mitigate China's energy poverty. Moreover, through the influencing mechanism check, the impact of NGC on energy poverty is mainly sourced from the four sub-indices, i.e., energy service availability (ESA), energy consumption cleanliness (ECC), energy management completeness (EMC), and household energy affordability & energy efficiency (EAE). Furthermore, the impact of NGC on energy poverty differs across various regions. Finally, several important policy implications are highlighted for eliminating China's energy poverty and promoting growth in the country's low-carbon energy industry.

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  • Dong, Kangyin & Jiang, Qingzhe & Shahbaz, Muhammad & Zhao, Jun, 2021. "Does low-carbon energy transition mitigate energy poverty? The case of natural gas for China," Energy Economics, Elsevier, vol. 99(C).
  • Handle: RePEc:eee:eneeco:v:99:y:2021:i:c:s0140988321002309
    DOI: 10.1016/j.eneco.2021.105324
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    More about this item

    Keywords

    Low-carbon energy transition; Energy poverty; Natural gas consumption (NGC); Sub-indices and heterogeneous analysis; 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
    • 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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