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Investigating the learning effects of technological advancement on CO2 emissions: a regional analysis in China

Author

Listed:
  • Wei Li

    (Tianjin University)

  • Tao Zhao

    (Tianjin University)

  • Yanan Wang

    (Northwest A&F University)

  • Fang Guo

    (Tianjin University)

Abstract

Technological advancement plays a crucial role in CO2 emissions mitigation and has attracted great attention around the world. A multitude of literatures mainly focused on single technological impact on environmental issues at national level, while comprehensive studies concerning technological factors at regional level are rare. This paper employs environmental learning curve model to investigate the learning effects of different technological channels on CO2 emissions at the national and regional levels using panel data of China’s 29 provinces from 1997 to 2014. The technological advancement is disaggregated into indigenous research and development (R&D), foreign technology import and technological revolution. Furthermore, to comprehend the characteristics of various provinces with regard to CO2 emissions and emission efficiency, China’s 29 provinces are divided into four regions according to the features of “CO2 emissions-efficiency”. Empirically results manifest that technical renovation is the paramount driver to mitigate the national CO2 emissions. The CO2 learning abilities of indigenous R&D in high emissions regions are greater than those in the low ones, while boosting the investment of foreign technology import in low emission regions has significantly positive impacts on CO2 emissions, and the technical renovation is effective in abating CO2 emissions in all regions. The findings not only enrich technology innovation theories, but also deserve special attention from policymakers.

Suggested Citation

  • Wei Li & Tao Zhao & Yanan Wang & Fang Guo, 2017. "Investigating the learning effects of technological advancement on CO2 emissions: a regional analysis in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(2), pages 1211-1227, September.
    • Handle: RePEc:spr:nathaz:v:88:y:2017:i:2:d:10.1007_s11069-017-2915-2
    DOI: 10.1007/s11069-017-2915-2
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    4. Wang, Yanan & Li, Xinbei & Kang, Yanqing & Chen, Wei & Zhao, Minjuan & Li, Wei, 2019. "Analyzing the impact of urbanization quality on CO2 emissions: What can geographically weighted regression tell us?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 127-136.
    5. Jing Sun & Ningning Zhai & Jichao Miao & Huaping Sun, 2022. "Can Green Finance Effectively Promote the Carbon Emission Reduction in “Local-Neighborhood” Areas?—Empirical Evidence from China," Agriculture, MDPI, vol. 12(10), pages 1-13, September.
    6. Haoran Yang & Hao Zheng & Hongguang Liu & Qun Wu, 2019. "NonLinear Effects of Environmental Regulation on Eco-Efficiency under the Constraint of Land Use Carbon Emissions: Evidence Based on a Bootstrapping Approach and Panel Threshold Model," IJERPH, MDPI, vol. 16(10), pages 1-20, May.
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