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The business restrictions introduced during the Covid-19 pandemic greatly affected the labour market. However, quantifying their costs is not trivial as local policies affect neighbouring areas through spillovers. Exploiting the U.S. local variation in restrictions and commuting, we estimate the causal direct and spillover impacts of lockdowns. Spillovers alone account for 10-15% of U.S. job losses. We corroborate these results with causal evidence for a consumption-based mechanism: shops whose consumers reside in neighbouring areas under lockdown experience larger employment losses, even if no local restriction is in place. Accounting for spillovers implies larger lockdowns’ total effects, but smaller direct ones.

Social distancing interventions can be effective against epidemics but are potentially detrimental for the economy. Businesses that rely heavily on face-to-face communication or close physical proximity when producing a product or providing a service are particularly vulnerable. There is, however, no systematic evidence on the role of human interactions across different lines of business and about which will be the most limited by social distancing. In this paper we provide theory-based measures of the reliance of US businesses on human interaction, detailed by industry and geographic location. We find that 49 million workers work in occupations that rely heavily on faceto-face communication or require close physical proximity to other workers. Our model suggests that when businesses are forced to reduce worker contacts by half, they need a 12% wage subsidy to compensate for the...

We extract aggregate demand and supply shocks for the US economy from real-time survey data on inflation and real GDP growth using a novel identification scheme. Our approach exploits non-Gaussian features of macroeconomic forecast revisions and imposes minimal theoretical assumptions. After verifying that our results for US post-war business cycle fluctuations are largely in line with the prevailing consensus, we proceed to study output and price fluctuations during COVID-19. We attribute two thirds of the decline in 2020:Q1 GDP to a negative shock to aggregate demand. In contrast, regarding the staggeringly large decline in GDP in 2020:Q2, we estimate two thirds of this shock was due to a reduction in aggregate supply. Statistical analysis suggests a slow recovery due to persistent effects of the supply shock, but surveys suggest a somewhat faster rebound with a recovery in...

We build a publicly available database that tracks economic activity at a granular level in real time using anonymized data from private companies. We report daily statistics on consumer spending, business revenues, employment rates, and other key indicators disaggregated by ZIP code, industry, income group, and business size. Using these data, we study how COVID-19 affected the economy by analyzing heterogeneity in its impacts. We first show that high-income individuals reduced spending sharply in mid-March 2020, particularly in areas with high rates of COVID-19 infection and in sectors that require in-person interaction. This reduction in spending greatly reduced the revenues of small businesses in affluent ZIP codes. These businesses laid off many of their employees, leading to widespread job losses especially among low-wage workers in affluent areas. High-wage workers experienced...

Many countries are shutting non-essential sectors of the economy to slow the spread of Covid-19. Older individuals have most to gain from slowing virus diffusion. Younger workers in sectors that are shuttered have the most to lose. In this paper we extend a standard epidemiological model of disease progression to include heterogeneity by age, and multiple sources of disease transmission. We then incorporate the epidemiological block into a multisector economic model in which workers differ by sector (basic and luxury) as well as by health status. We study optimal mitigation policies of a utilitarian government that can redistribute resources across individuals, but where such redistribution is costly. We show that optimal redistribution and mitigation policies interact, and reflect a compromise between the strongly diverging preferred policy paths across the subgroups of the population

The covid-19 crisis has led to a sharp deterioration in firm and bank balance sheets. The government has responded with a massive intervention in corporate credit markets. We study equilibrium dynamics of macroeconomic quantities and prices, and how they are affected by government policy. The interventions prevent a much deeper crisis by reducing corporate bankruptcies by about half and short-circuiting the doom loop between corporate and financial sector fragility. The additional fiscal cost is zero since program spending replaces what would otherwise have been spent on intermediary bailouts. The model predicts rising interest rates on government debt and slow debt pay-down. We analyze an alternative intervention that targets aid to firms at risk of bankruptcy. While this policy prevents more bankruptcies and has lower fiscal cost, it only enjoys marginally higher welfare. Finally,...

This paper develops a choice-theoretic equilibrium model of the labor market in the presence of a pandemic. It includes heterogeneity in productivity, age and the ability to work at home. Worker and firm behavior changes in the presence of the virus, which itself has equilibrium consequences for the infection rate. The model is calibrated to the UK and counterfactual lockdown measures are evaluated. We find a different response in both the evolution of the virus and the labor market with different degrees of severity of lockdown. We use these insights to make a labor market policy prescription to be used in conjunction with lockdown measures. Finally we find that, while the pandemic and ensuing policies impact the majority of the population negatively, consistent with recent studies, the costs are not borne equally. While the old face the highest health risks, it is the young low...

We analyze the externalities that arise when social and economic interactions transmit infectious diseases such as COVID-19. Individually rational agents do not internalize that they impose infection externalities upon others when the disease is transmitted. In an SIR model calibrated to capture the main features of COVID-19 in the US economy, we show that private agents perceive the cost an additional infection to be around $80k whereas the social cost including infection externalities is more than three times higher, around $286k. This misvaluation has stark implications for how society ultimately overcomes the disease: for a population of individually rational agents, the precautionary behavior by the susceptible flattens the curve of infections, but the disease is not overcome until herd immunity is acquired. The resulting economic cost is high; an initial sharp decline in...

This paper develops and implements a method to monetize the impact of moderate social distancing on deaths from Covid-19. Using the Ferguson et al. (2020) simulation model of Covid-19’s spread and mortality impacts in the United States, we project that three to four months of moderate distancing beginning in late March 2020 would save 1.7 million lives by October 1. Of the lives saved, 630,000 are due to avoided overwhelming of hospital intensive care units. Using the projected age-specific reductions in death and age-varying estimates of the United States Government’s value of a statistical life, we find that the mortality benefits of social distancing are about $8 trillion or $60,000 per US household. Roughly nine-tenths of the monetized benefits are projected to accrue to people age 50 or older. Overall, the analysis suggests that social distancing initiatives and policies in...