We integrate an epidemiological model, augmented with contact and mobility analyses, with a two-sector macroeconomic model, to assess the economic costs of labor supply disruptions in a pandemic. The model is designed to capture key characteristics of the U.S. Input-Output Tables with a core sector that produces intermediate inputs not easily replaceable by the other sectors, possibly subject to minimum-scale requirements.

This paper documents that the COVID-19 pandemic induced pressures on the health care system have significant adverse knock-on effects on the accessibility and quality of non-COVID-19 care. We observe persistently worsened performance and longer waiting times in A&E; drastically limited access to specialist care; notably delayed or inaccessible diagnostic services; acutely undermined access to and quality of cancer care.

The coronavirus outbreak has caused significant disruptions to people’s lives. We exploit variation in lockdown measures across states to document the impact of stay-at-home orders on mental health using real-time survey data in the United States. We find that the lockdown measures lowered mental health by 0.083 standard deviations. This large negative effect is entirely driven by women. As a result of the lockdown measures, the existing gender gap in mental health has increased by 61%.

Not all countries provide universal access to publicly funded paid sick pay. Amongst countries that do, compensation rates can be low and coverage incomplete. This leaves a significant role for employer-provided paid sick pay in many countries. In this paper, we study who has access to employer-provided sick pay, how access to sick pay relates to labor supply when sick, and how much it is valued by workers for themselves and others.

Using daily data on vaccinations, disease spread, and measures of social interaction from Google Mobility reports aggregated at the country level for 112 countries, we present estimates of behavioral responses to the global rollout of COVID-19 vaccines.

Supermodularity, or complementarity, is a popular concept in economics which can characterize many objective functions, including utility, social welfare, and production functions. Further, supermodular dominance captures a preference for greater interdependence among inputs of those functions, and it can be applied to examine which input set would produce higher expected utility, social welfare, or production.

This paper studies the role of slums in shaping the economic and health dynamics of pandemics. Using data from millions of mobile phones in Brazil, an event-study analysis shows that residents of overcrowded slums engaged in less social distancing after the outbreak of Covid-19. We develop a choice-theoretic equilibrium model in which poorer agents live in high-density slums and others do not. The model is calibrated to Rio de Janeiro. Slum dwellers account for a disproportionately high number of infections and deaths.

Using large, geographically representative surveys from the US and UK, we document variation in the percentage of tasks workers can do from home. We highlight three dimensions of heterogeneity that have previously been neglected. First, the share of tasks that can be done from home varies considerably both across as well as within occupations and industries. The distribution of the share of tasks that can be done from home within occupations, industries, and occupation-industry pairs is systematic and remarkably consistent across countries and survey waves.

The coronavirus outbreak has caused significant disruptions to people’s lives. We exploit variation in lockdown measures across states to document the impact of stay-at-home orders on mental health using real time survey data in the US. We find that the lockdown measures lowered mental health by 0.083 standard deviations. This large negative effect is entirely driven by women. As a result of the lockdown measures, the existing gender gap in mental health has increased by 61%.