The economic cost of locking down like China: Evidence from city-to-city truck flows

Jingjing Chen, Wei Chen, Ernest Liu, Jie Luo and Zheng Song

Journal of Urban Economics, 2025, vol. 145, issue C

Abstract: Containing the COVID-19 pandemic by non-pharmacological interventions is costly. Using high-frequency, city-to-city truck flow data, this paper estimates the economic cost of lockdown in China, a stringent yet effective policy prior to the Omicron surge. By comparing the truck flow change in the cities with and without lockdown, we find that a one-month full-scale lockdown causally reduces the truck flows connected to the locked down city in the month by 54%, implying a decline of the city’s real income with the same proportion in a gravity model of city-to-city trade. We also structurally estimate the cost of lockdown in the gravity model, where the effects of lockdown can spill over to other cities through trade linkages. Imposing full-scale lockdown on the four largest cities in China (Beijing, Shanghai, Guangzhou, and Shenzhen) for one month would reduce the real national GDP by 8.7%, of which 8.5% is contributed by the spillover effects.

Keywords: COVID-19; Lockdown; City-to-city truck flow; Trade (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0094119024000998
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:juecon:v:145:y:2025:i:c:s0094119024000998

DOI: 10.1016/j.jue.2024.103729

Access Statistics for this article

Journal of Urban Economics is currently edited by S.S. Rosenthal and W.C. Strange

More articles in Journal of Urban Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().