Understanding the Spatial Impact of COVID-19: New Insights from Beijing after One Year into Post-Lockdown Recovery

Abstract

This paper studies the spatial impact of COVID-19 pandemic through the lens of intra-city population and house rent changes in Beijing, China. Drawing on multiple geospatial data sets, we find that the pandemic has flattened the housing bid-rent curve in Beijing, which corroborates existing literature mainly based on cities in developed countries. Through regression analysis and spatial equilibrium modelling, we identify key mechanisms of the flattened bid-rent curve and the accompanying decentralisation of residents. First, workplace population change, particularly in central Beijing, seems to be the main factor contributing to the resident population and house rent changes. Second, we find no significant evidence on the spatial impact from remote working, as the share of remote working in Beijing appears low after about one year recovery. This finding contrasts to existing studies where remote working has been perceived as the main driver for urban spatial structure change in a developed country context. Third, through a novel method for quantifying locational preference changes, it is found that the observed decentralisation trend in Beijing, ceteris paribus, may also be associated with increased (decreased) preference for living in suburban (central) locations. However, the preference change for central locations is marginal, hence providing an early rebuttal of the ‘demise of centres’ proposition.

Keywords: COVID-19, agglomeration, urban spatial structure, equilibrium model

JEL Classification: R00, E24