Beschreibung:
Since the outbreak of the coronavirus disease (COVID-19) pandemic, governments around the globe have undertaken multiple policies to control its spread. Yet, only a few studies estimated the cost of COVID-19-related stringency measures on economic output, which can be attributable to the time lag and low frequency of conventional economic data. To bridge this gap in the literature, this paper uses novel high-frequency and spatially granular surface urban heat island (SUHI) data from satellites to quantify the impact of COVID-19-related containment policies in the People's Republic of China, exploiting variations in such policies. Three empirical results emerge. First, we find stringency measures decrease urban heat island in locked cities only marginally, which is equivalent to 0.04-0.05 standard deviation or CNY22.2 billion ($3.6 billion) of economic output drop which is a 0.09% annual gross domestic product decline in 2020. Second, our results suggest that governments have been learning continuously to manage containment measures better. Third, the government's containment policies have generated both positive and negative spillover effects on unlocked cities in which the former effect has dominated the latter.