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Assessment of national economic repercussions from Shanghai’s COVID-19 lockdown

Author

Listed:
  • Zengming Liu

    (Chinese Academy of Sciences
    University of Chinese Academy of Social Sciences)

  • Yanan Wang

    (University of Chinese Academy of Social Sciences
    Northwest A&F University)

  • Xiaoyong Huang

    (University of Chinese Academy of Social Sciences
    University of Chinese Academy of Social Sciences)

  • Zihan Zhang

    (Tsinghua University)

  • Qingsheng Lai

    (Fudan University)

  • Meng Li

    (Northwest A&F University)

Abstract

In today’s increasingly specialized and fragmented sectoral chain, as well as increasingly close economic connections between regions, regional economic fluctuations caused by natural or human factors can be transmitted through the interregional economic network to external regions, causing losses. The assessment of external losses is the foundation for fully understanding the impact of emergencies and taking effective response measures. On the basis of the MRIO model, this paper constructs a model of the impact of the COVID-19 lockdown in Shanghai on the national economy and investigates the impact of artificial controls on the economies of various regions and sectors in China after the outbreak of the COVID-19 pandemic. The results indicate that the external losses caused by regional emergencies are much greater than the local losses. Second, the sectors with the greatest GDP losses caused by Shanghai’s lockdown are wholesale and retail, whereas the sectors with the greatest decline are metal product manufacturing, machinery and equipment maintenance services. Finally, the impact of Shanghai’s lockdown on other regions is not significantly related to their economic size or geographical location.

Suggested Citation

  • Zengming Liu & Yanan Wang & Xiaoyong Huang & Zihan Zhang & Qingsheng Lai & Meng Li, 2024. "Assessment of national economic repercussions from Shanghai’s COVID-19 lockdown," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-04100-3
    DOI: 10.1057/s41599-024-04100-3
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    References listed on IDEAS

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    1. Krista Danielle S. Yu & Kathleen B. Aviso & Joost R. Santos & Raymond R. Tan, 2020. "The Economic Impact of Lockdowns: A Persistent Inoperability Input-Output Approach," Economies, MDPI, vol. 8(4), pages 1-14, December.
    2. d'Artis Kancs, 2024. "Uncertainty of supply chains: Risk and ambiguity," The World Economy, Wiley Blackwell, vol. 47(5), pages 2009-2033, May.
    3. José Balsa-Barreiro & Aymeric Vié & Alfredo J. Morales & Manuel Cebrián, 2020. "Deglobalization in a hyper-connected world," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-4, December.
    4. Han, Yang, 2022. "The impact of the COVID-19 pandemic on China's economic structure: An input–output approach," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 181-195.
    5. I�aki Arto & Valeria Andreoni & Jose Manuel Rueda Cantuche, 2015. "Global Impacts of the Automotive Supply Chain Disruption Following the Japanese Earthquake of 2011," Economic Systems Research, Taylor & Francis Journals, vol. 27(3), pages 306-323, September.
    6. Li, Zhinan & Pei, Shan & Li, Ting & Wang, Yu, 2023. "Risk spillover network in the supply chain system during the COVID-19 crisis: Evidence from China," Economic Modelling, Elsevier, vol. 126(C).
    7. Janssen, Marijn & van der Voort, Haiko, 2020. "Agile and adaptive governance in crisis response: Lessons from the COVID-19 pandemic," International Journal of Information Management, Elsevier, vol. 55(C).
    8. Li, Zhong-fei & Zhou, Qi & Chen, Ming & Liu, Qian, 2021. "The impact of COVID-19 on industry-related characteristics and risk contagion," Finance Research Letters, Elsevier, vol. 39(C).
    9. Kazancoglu, Yigit & Ekinci, Esra & Mangla, Sachin Kumar & Sezer, Muruvvet Deniz & Ozbiltekin-Pala, Melisa, 2023. "Impact of epidemic outbreaks (COVID-19) on global supply chains: A case of trade between Turkey and China," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    10. Ichev, Riste & Marinč, Matej, 2018. "Stock prices and geographic proximity of information: Evidence from the Ebola outbreak," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 153-166.
    11. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
    12. Ma, Dan & Zhu, Yanjin, 2024. "The impact of economic uncertainty on carbon emission: Evidence from China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
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