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

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.