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Can smart transportation inhibit carbon lock-in? The case of China

Author

Listed:
  • Dong, Kangyin
  • Jia, Rongwen
  • Zhao, Congyu
  • Wang, Kun

Abstract

A thorough understanding of carbon lock-in is an essential precondition for the effective design and continuous improvement of climate policy. Based on a balanced panel dataset of 30 provinces in China during the period 2002–2021, we explore the nexus between smart transportation and carbon lock-in using the System-Generalized Method of Moments (SYS-GMM) model. We also investigate the heterogeneous, asymmetric, and threshold effects among the above two issues, and examine three internal impact mechanisms. We thus arrive at the following four main conclusions: (1) Smart transportation significantly reduces carbon lock-in, highlighting its importance in eradicating carbon lock-in. (2) Smart transportation has the most pronounced impact on carbon lock-in in the central region, and can effectively mitigate all aspects of carbon lock-in, especially industry lock-in and institution lock-in. (3) Smart transportation is more effective in alleviating carbon lock-in in provinces with a higher level of carbon lock-in. Moreover, a threshold of environmental regulation exists between smart transportation and carbon lock-in, with stricter environmental regulation leading to a stronger carbon lock-in reduction effect of smart transportation. (4) Smart transportation indirectly influences carbon lock-in through three channels of economic scale, industrial structure upgrading, and technological innovation. Based on these findings, we propose some policy recommendations for smart transportation development and carbon lock-in mitigation.

Suggested Citation

  • Dong, Kangyin & Jia, Rongwen & Zhao, Congyu & Wang, Kun, 2023. "Can smart transportation inhibit carbon lock-in? The case of China," Transport Policy, Elsevier, vol. 142(C), pages 59-69.
  • Handle: RePEc:eee:trapol:v:142:y:2023:i:c:p:59-69
    DOI: 10.1016/j.tranpol.2023.08.003
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    References listed on IDEAS

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    More about this item

    Keywords

    Carbon lock-in; Smart transportation; Mediating effect model; Threshold effect model; China;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single 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
    • P25 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Urban, Rural, and Regional Economics
    • P28 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Natural Resources; Environment
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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