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Economic structural change and freight transport demand in China

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  • Xu, Xun
  • Chase, Nicholas
  • Peng, Tianduo

Abstract

China's rapidly rising freight transport demand has been one of the primary contributors to global oil consumption growth since 2000 and has remained the dominant source of domestic transport energy consumption during the same period. The objective of this paper is to investigate the main structural driving forces of China's freight transport demand during its fastest growing period (1997–2012), and to analyze its potential future scenario. The results suggest that strong growth of total final demand, an increasingly freight-intensive economic structure, and lengthening inter-industry production linkages, which is consistent with China's investment and export driven development model from 1997 to 2012, have been the main propellers of rapid freight transport demand growth during this time. Looking ahead, as the Chinese economy gradually shifts to a consumption driven model in an increasingly uncertain global economic environment, policymakers need to be aware of both unexpected demand shocks and the inherent changes of the Chinese economy while considering their implications for China's transport energy demand and China's carbon emission mitigation strategy.

Suggested Citation

  • Xu, Xun & Chase, Nicholas & Peng, Tianduo, 2021. "Economic structural change and freight transport demand in China," Energy Policy, Elsevier, vol. 158(C).
    • Handle: RePEc:eee:enepol:v:158:y:2021:i:c:s0301421521004377
    DOI: 10.1016/j.enpol.2021.112567
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    1. Nealer, Rachael & Weber, Christopher L. & Hendrickson, Chris & Scott Matthews, H., 2011. "Modal freight transport required for production of US goods and services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(4), pages 474-489, July.
    2. Su, Bin & Ang, B.W. & Li, Yingzhu, 2017. "Input-output and structural decomposition analysis of Singapore's carbon emissions," Energy Policy, Elsevier, vol. 105(C), pages 484-492.
    3. Peng, Tianduo & Ou, Xunmin & Yuan, Zhiyi & Yan, Xiaoyu & Zhang, Xiliang, 2018. "Development and application of China provincial road transport energy demand and GHG emissions analysis model," Applied Energy, Elsevier, vol. 222(C), pages 313-328.
    4. Carrara, Samuel & Longden, Thomas, 2017. "Freight Futures: The Potential Impact of Road Freight on Climate Policy," MITP: Mitigation, Innovation and Transformation Pathways 253731, Fondazione Eni Enrico Mattei (FEEM).
    5. Pan, Xunzhang & Wang, Hailin & Wang, Lining & Chen, Wenying, 2018. "Decarbonization of China's transportation sector: In light of national mitigation toward the Paris Agreement goals," Energy, Elsevier, vol. 155(C), pages 853-864.
    6. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    7. Yin, Xiang & Chen, Wenying & Eom, Jiyong & Clarke, Leon E. & Kim, Son H. & Patel, Pralit L. & Yu, Sha & Kyle, G. Page, 2015. "China's transportation energy consumption and CO2 emissions from a global perspective," Energy Policy, Elsevier, vol. 82(C), pages 233-248.
    8. Anable, Jillian & Brand, Christian & Tran, Martino & Eyre, Nick, 2012. "Modelling transport energy demand: A socio-technical approach," Energy Policy, Elsevier, vol. 41(C), pages 125-138.
    9. Zhang, Hongjun & Chen, Wenying & Huang, Weilong, 2016. "TIMES modelling of transport sector in China and USA: Comparisons from a decarbonization perspective," Applied Energy, Elsevier, vol. 162(C), pages 1505-1514.
    10. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    11. Wang, Hailin & Ou, Xunmin & Zhang, Xiliang, 2017. "Mode, technology, energy consumption, and resulting CO2 emissions in China's transport sector up to 2050," Energy Policy, Elsevier, vol. 109(C), pages 719-733.
    12. Su, Bin & Ang, B.W., 2013. "Input–output analysis of CO2 emissions embodied in trade: Competitive versus non-competitive imports," Energy Policy, Elsevier, vol. 56(C), pages 83-87.
    13. Alises, Ana & Vassallo, José Manuel, 2015. "Comparison of road freight transport trends in Europe. Coupling and decoupling factors from an Input–Output structural decomposition analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 141-157.
    14. Xu, Ming & Li, Ran & Crittenden, John C. & Chen, Yongsheng, 2011. "CO2 emissions embodied in China's exports from 2002 to 2008: A structural decomposition analysis," Energy Policy, Elsevier, vol. 39(11), pages 7381-7388.
    15. Leontief, Wassily, 1970. "Environmental Repercussions and the Economic Structure: An Input-Output Approach," The Review of Economics and Statistics, MIT Press, vol. 52(3), pages 262-271, August.
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    Cited by:

    1. Yan, Jiaze & Wang, Ge & Chen, Siyuan & Zhang, He & Qian, Jiaqi & Mao, Yuxuan, 2022. "Harnessing freight platforms to promote the penetration of long-haul heavy-duty hydrogen fuel-cell trucks," Energy, Elsevier, vol. 254(PA).
    2. Wenjie Li & Chun Luo & Yiwei He & Yu Wan & Hongbo Du, 2023. "Estimating Inter-Regional Freight Demand in China Based on the Input–Output Model," Sustainability, MDPI, vol. 15(12), pages 1-16, June.
    3. Elżbieta Szaruga & Elżbieta Załoga, 2022. "Environmental Management from the Point of View of the Energy Intensity of Road Freight Transport and Shocks," IJERPH, MDPI, vol. 19(21), pages 1-22, November.

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