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The impact of the COVID-19 pandemic on China's economic structure: An input–output approach

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  • Han, Yang

Abstract

Recognizing the impact of COVID-19 on economic structure is an urgently required task for the post-pandemic era. However, studies have been hampered in undertaking this task by a lack of current data and the use of inappropriate methods. This paper fills the gap in the literature by applying a network analysis method using the newly released input–output tables of China and evaluating the structural impacts on the economy, including the changes in the sectoral closeness, betweenness, risk condition, and network backbone. The modelling results demonstrate that the pandemic has accelerated the structural transformation process of the Chinese economy: the traditional growth engines, such as the petroleum and finance industries, have lagged, whereas new growth engine sectors, including the digital services and scientific research industries, have expanded rapidly. Accordingly, we propose that the government formulate policies to stabilize old growth engine industries and foster new drivers to promote a sustainable economic recovery in China.

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  • 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.
  • Handle: RePEc:eee:streco:v:63:y:2022:i:c:p:181-195
    DOI: 10.1016/j.strueco.2022.09.014
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    as
    1. Costa, Vinicius B.F. & Pereira, Lígia C. & Andrade, Jorge V.B. & Bonatto, Benedito D., 2022. "Future assessment of the impact of the COVID-19 pandemic on the electricity market based on a stochastic socioeconomic model," Applied Energy, Elsevier, vol. 313(C).
    2. Deriu, S. & Cassar, I.P. & Pretaroli, R. & Socci, C., 2022. "The economic impact of Covid-19 pandemic in Sardinia," Research in Transportation Economics, Elsevier, vol. 93(C).
    3. Huang, Kainan & Cheng, Baodong & Chen, Moyu & Sheng, Yu, 2022. "Assessing impact of the COVID-19 pandemic on China’s TFP growth: Evidence from region-level data in 2020," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 362-377.
    4. Teng, Bin & Wang, Sicong & Shi, Yufeng & Sun, Yunchuan & Wang, Wei & Hu, Wentao & Shi, Chaojun, 2022. "Economic recovery forecasts under impacts of COVID-19," Economic Modelling, Elsevier, vol. 110(C).
    5. Dragičević, Davor & Sasu, Adina Luminiţa & Sasu, Bogdan, 2022. "Input-output criteria for stability and expansiveness of dynamical systems," Applied Mathematics and Computation, Elsevier, vol. 414(C).
    6. Xu, Ming & Liang, Sai, 2019. "Input–output networks offer new insights of economic structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    7. Battisti, Enrico & Alfiero, Simona & Leonidou, Erasmia, 2022. "Remote working and digital transformation during the COVID-19 pandemic: Economic–financial impacts and psychological drivers for employees," Journal of Business Research, Elsevier, vol. 150(C), pages 38-50.
    8. Michael Sonis & Geoffrey J. D. Hewings, 1998. "original: Economic complexity as network complication: Multiregional input-output structural path analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 32(3), pages 407-436.
    9. Garaus, Marion & Hudáková, Melánia, 2022. "The impact of the COVID-19 pandemic on tourists’ air travel intentions: The role of perceived health risk and trust in the airline," Journal of Air Transport Management, Elsevier, vol. 103(C).
    10. Federica Cerina & Zhen Zhu & Alessandro Chessa & Massimo Riccaboni, 2015. "World Input-Output Network," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-21, July.
    11. Grazzini, Jakob & Spelta, Alessandro, 2022. "An empirical analysis of the global input–output network and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    12. Leonidov, Andrey & Serebryannikova, Ekaterina, 2019. "Dynamical topology of highly aggregated input–output networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 234-252.
    13. Arin, K. Peren & Lacomba, Juan A. & Lagos, Francisco & Moro-Egido, Ana I. & Thum, Marcel, 2022. "Exploring the hidden impact of the Covid-19 pandemic: The role of urbanization," Economics & Human Biology, Elsevier, vol. 46(C).
    14. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, September.
    15. Yu, Miao & Zhao, Xintong & Gao, Yuning, 2019. "Factor decomposition of China’s industrial electricity consumption using structural decomposition analysis," Structural Change and Economic Dynamics, Elsevier, vol. 51(C), pages 67-76.
    16. Goswami, Binoy & Mandal, Raju & Nath, Hiranya K., 2021. "Covid-19 pandemic and economic performances of the states in India," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 461-479.
    17. Domínguez, Alvaro & Santos-Marquez, Felipe & Mendez, Carlos, 2021. "Sectoral productivity convergence, input-output structure and network communities in Japan," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 582-599.
    18. Zhou, Yuqin & Liu, Zhenhua & Wu, Shan, 2022. "The global economic policy uncertainty spillover analysis: In the background of COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 61(C).
    19. Bonfiglio, Andrea & Coderoni, Silvia & Esposti, Roberto, 2022. "Policy responses to COVID-19 pandemic waves: Cross-region and cross-sector economic impact," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 252-279.
    20. Stamopoulos, Dimitrios & Dimas, Petros & Tsakanikas, Aggelos, 2022. "Exploring the structural effects of the ICT sector in the Greek economy: A quantitative approach based on input-output and network analysis," Telecommunications Policy, Elsevier, vol. 46(7).
    21. Han, Yang & Zhang, Haotian & Zhao, Yong, 2021. "Structural evolution of real estate industry in China: 2002-2017," Structural Change and Economic Dynamics, Elsevier, vol. 57(C), pages 45-56.
    22. Feng, Qu & Wu, Guiying Laura & Yuan, Mengying & Zhou, Shihao, 2022. "Save lives or save livelihoods? A cross-country analysis of COVID-19 pandemic and economic growth," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 221-256.
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    More about this item

    Keywords

    COVID-19 pandemic; Economic structure transformation; Input–output approach; Network analysis method;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions

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