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Pandemics, Global Supply Chains, and Local Labor Demand: Evidence from 100 Million Posted Jobs in China

Author

Listed:
  • Hanming Fang

    (University of Pennsylvania)

  • Chunmian Ge

    (South China Uni-versity of Technology)

  • Hanwei Huang

    (City University of Hong Kong)

  • Hongbin Li

    (Stanford University)

Abstract

This paper studies how the COVID-19 pandemic has a?ected labor de-mand using over 100 million posted jobs on one of the largest online plat-forms in China. Our data reveals that, due to the e?ects of the pandemic both in China and abroad, the number of newly posted jobs within the ?rst 13 weeks after the Wuhan lockdown on January 23, 2020 was about one third lower than that of the same lunar calendar weeks in 2018 and 2019. Using econometric methods, we show that, via the global supply chain, COVID-19 cases abroad and in particular pandemic-control policies by foreign govern-ments reduced new job creations in China by 11.7%. We also ?nd that Chinese ?rms most exposed to international trade outperformed other ?rms at the beginning of the pandemic but underperformed during recovery as the Novel Coronavirus spread throughout the world.

Suggested Citation

  • Hanming Fang & Chunmian Ge & Hanwei Huang & Hongbin Li, 2020. "Pandemics, Global Supply Chains, and Local Labor Demand: Evidence from 100 Million Posted Jobs in China," PIER Working Paper Archive 20-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    • Handle: RePEc:pen:papers:20-035
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    References listed on IDEAS

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    Cited by:

    1. Zeng, Xiangquan & Chu, Shuai & Chen, Xuan, 2022. "China's Labor Market Demand in the Shadow of COVID-19: Evidence from an Online Job Board," IZA Discussion Papers 15201, Institute of Labor Economics (IZA).
    2. Zeng, Xiangquan & Chu, Shuai & Chen, Xuan, 2022. "China's Labor Market Demand in the Shadow of COVID-19: Evidence from an Online Job Board," GLO Discussion Paper Series 1074, Global Labor Organization (GLO).
    3. Qi Zhang & Xinxin Zhang & Qi Cui & Weining Cao & Ling He & Yexin Zhou & Xiaofan Li & Yunpeng Fan, 2022. "The Unequal Effect of the COVID-19 Pandemic on the Labour Market and Income Inequality in China: A Multisectoral CGE Model Analysis Coupled with a Micro-Simulation Approach," IJERPH, MDPI, vol. 19(3), pages 1-21, January.

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    More about this item

    Keywords

    OVID-19; labor demand; global supply chains; trade;
    All these keywords.

    JEL classification:

    • J00 - Labor and Demographic Economics - - General - - - General
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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