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Can low-carbon energy technology lead to energy resource carrying capacity improvement? The case of China

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  • Zhao, Congyu
  • Dong, Kangyin
  • Wang, Kun
  • Dong, Xiucheng

Abstract

Energy resource carrying capacity serves as a crucial yardstick for assessing the sustainability of energy systems. To explore to what extent and how low-carbon energy technology affects energy resource carrying capacity, this study first calculates the level of low-carbon energy technology and energy resource carrying capacity in China for the period 2000–2019, and then employs the instrumental variable generalized method of moments (IV-GMM) model to investigate the marginal impact of low-carbon energy technology on energy resource carrying capacity. We also explore their asymmetric, direct, as well as indirect nexus. We find that (1) low-carbon energy technology presents benefits to the energy resource carrying capacity improvement, which indicates their positive nexus. (2) Low-carbon energy technology has a diminishing marginal effect on energy resource carrying capacity as the level of energy resource carrying capacity increases, which implies their asymmetric nexus. (3) Low-carbon energy technology has significant promotion effects on socioeconomic development, energy capacity, and environment capacity, which are three dimensions of energy resource carrying capacity. (4) Energy transition and energy efficiency are two positive mediators in the impact of low-carbon energy technology on energy resource carrying capacity. Several targeted policy implications are proposed based on the above findings.

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  • Zhao, Congyu & Dong, Kangyin & Wang, Kun & Dong, Xiucheng, 2023. "Can low-carbon energy technology lead to energy resource carrying capacity improvement? The case of China," Energy Economics, Elsevier, vol. 127(PA).
    • Handle: RePEc:eee:eneeco:v:127:y:2023:i:pa:s014098832300590x
    DOI: 10.1016/j.eneco.2023.107092
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    More about this item

    Keywords

    Low-carbon energy technology; Energy resource carrying capacity; Energy transition; Energy efficiency; China;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • P28 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Natural Resources; Environment
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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