Surviving COVID-19: Recovery Curves of Mall Traffic in China

Abstract

The outbreak of COVID-19 has caused huge disruptions to the world economy. As a number of countries make progress in containing this outbreak, some of them have started to reopen their economy. We study the curves of recovery after reopening the economy, using a unique real-time dataset of daily customer traffic of 463 malls from 88 cities in China. Our results demonstrate that 9 weeks after reopening the economy, mall traffic has recovered to 64.0% of its level before this outbreak. In addition, the progress of containing this outbreak, such as reporting zero new local cases and clearing all existing cases, could significantly boost the recovery of mall traffic. Furthermore, We find that the recovery follows different curves across different cities, and this heterogeneity can be explained by pandemic situations, city tiers and city characteristics such as population, GDP, industrial structure, etc. More specifically, faster recovery speeds are observed in cities with better pandemic situations, lower city tiers, smaller migrant population, lower proportion of tertiary industry, higher proportion of secondary industry and higher GDP per capita.

Keywords: COVID-19; Coronavirus; Economic Recovery; Mall Traffic; Event study