Who died, who survived? COVID-19 epidemic, industrial dynamics and urban economic resilience

Abstract

The COVID-19 epidemic has altered the economic geographies of cities. However, the academic focus on urban industries and their structural dynamics is far from enough. In this paper, we integrate literature from economic geography, business studies and network sciences, and design an adaptation framework to theorize urban economic resilience. Taking the COVID-19 outbreak in Xinfadi, Beijing during the summer of 2020 as a case study, we use Logit regressions and DID estimations to identify the impacts of the epidemic on local industrial dynamics. Our results support that the COVID-19 outbreak significantly increases the number of business exits. The negative impacts are concentrated in high-risk regions, pointing to specific industries and individual-owned firms. Furthermore, we use a machine learning method to visualize the dynamics of industry networks in a small-scale urban area, and then simulate the transmission paths of industry-failure. In doing so, we contribute to current economic resilience literature that firm-level adaptation and industrial dynamics complement regional adaptation theory, while the cascading effects in the industry network underpin the micro foundations of resilience formation.