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Quantifying the role of technical progress towards China’s 2030 carbon intensity target

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  • Peng Li
  • Yaofu Ouyang

Abstract

This paper constructs a dynamic computable general equilibrium (DCGE) model to investigate the macroeconomic effects of endogenous technical progress in achieving China’s 2030 carbon intensity reduction target of 60–65% compared with 2005. We show that a combination of a carbon tax and technological progress can achieve the carbon intensity target in 2030, but it will exert a negative impact on economic growth. This negative effect, however, can be relieved by endogenously directed technological progress in the long term. In doing so, industrial structure and energy structure are dynamically adjusted by inhibiting the output and employment of the coal and oil sectors but promoting that of the clean energy and the service industry. We also find that with technological progress, the unit carbon abatement cost in the long term is estimated to be 200–250 yuan/ton, much lower than that in the short term (over 367 yuan/ton). Several policy implications are discussed accordingly.

Suggested Citation

  • Peng Li & Yaofu Ouyang, 2021. "Quantifying the role of technical progress towards China’s 2030 carbon intensity target," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 64(3), pages 379-398, February.
    • Handle: RePEc:taf:jenpmg:v:64:y:2021:i:3:p:379-398
    DOI: 10.1080/09640568.2020.1764343
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    Cited by:

    1. Weijiang Liu & Min Liu & Tingting Liu & Yangyang Li & Yizhe Hao, 2022. "Does a Recycling Carbon Tax with Technological Progress in Clean Electricity Drive the Green Economy?," IJERPH, MDPI, vol. 19(3), pages 1-18, February.
    2. Cai Li & Luyu Li & Jiaqi Zheng & Jizhi Wang & Yi Yuan & Zezhong Lv & Yinghao Wei & Qihang Han & Jiatong Gao & Wenhao Liu, 2022. "China’s Public Firms’ Attitudes towards Environmental Protection Based on Sentiment Analysis and Random Forest Models," Sustainability, MDPI, vol. 14(9), pages 1-27, April.
    3. Xin Xu & Yuming Shen & Hanchu Liu, 2022. "What Cause Large Spatiotemporal Differences in Carbon Intensity of Energy-Intensive Industries in China? Evidence from Provincial Data during 2000–2019," IJERPH, MDPI, vol. 19(16), pages 1-18, August.
    4. Xiaoxiang Xu & Mingqiu Liao, 2022. "Prediction of China’s Economic Structural Changes under Carbon Emission Constraints: Based on the Linear Programming Input–Output (LP-IO) Model," Sustainability, MDPI, vol. 14(15), pages 1-13, July.

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