We use a conventional dynamic economic model to integrate individual optimization, equilibrium interactions, and policy analysis into the canonical epidemiological model. Our tractable framework allows us to represent both equilibrium and optimal allocations as a set of differential equations that can jointly be solved with the epidemiological model in a unified fashion. Quantitatively, the laissez-faire equilibrium accounts for the decline in social activity we measure in US micro-data from SafeGraph. Relative to that, we highlight three key features of the optimal policy: it imposes immediate, discontinuous social distancing; it keeps social distancing in place for a long time or until treatment is found; and it is never extremely restrictive, keeping the effective reproduction number mildly above the share of the population susceptible to the disease.
We leverage an event-study research design focused on the seven costliest hurricanes to hit the US mainland since 2004 to identify the elasticity of unemployment insurance filings with respect to search intensity. Applying our elasticity estimate to the state-level Google Trends indexes for the topic unemployment
In this study, I discuss the role of international air traffic in spreading the new corona virus COVID-19 around the world, with a focus on travel restrictions. I build on a sample of 34 mostly European countries reporting international flights to 154 destination countries. This dataset is combined with information on daily reported cases of COVID-19 infections in these countries. I find that more connected countries registered first infection cases significantly earlier than less connected countries. This effect was reinforced by direct flight connections to China. I also show that severe travel restrictions were implemented relatively late in most countries. For a group of 120 countries included in the sample of analysis, three out of four countries already had more than 50 confirmed cases when travel restrictions were implemented. In contrast, very early implementations of air travel restrictions were associated with a delayed onset of infections. As a takeaway for future outbreaks of infectious diseases, the results suggests that the early implementation of travel restrictions could be key in slowing down the spread of infections around the world. The design of a global emergency stop in international travel requires a high level of coordination at a multilateral level in order to preserve supply chains as much as possible.
The British government has been debating how and when to escape from the lockdown without provoking a resurgence of the Covid-19 disease. There is a growing recognition of the damage the lockdown is causing to economic and social life, including deaths and illness amongst the non-infected population. This paper presents a simple cost-benefit analysis based on optimal control theory and incorporating the SIR model of disease propagation. It concludes by presenting some simulations informed by the theoretical discussion. The main conclusions are: (1) the lockdown should be continued for some weeks, and (2) if there is an inexpensive way of reducing the net reproductive rate of the disease to r = 1, this policy should be adopted within a few weeks of exiting lockdown. It is not cost-effective to linger in intermediate stages with more expensive policies designed to keep r well below unity with the hope eradicating the disease.
We study the impact of working from home on (i) infection risk in German regions and (ii) output using an input-output (IO) model of the German economy. We find that working from home is very effective in reducing infection risk: regions whose industry structure allows for a larger fraction of work to be done from home experienced much fewer Covid-19 cases and fatalities. Moreover, confinement is significantly more costly in terms of induced output loss in regions where the share of workers who can work from home is lower. When phasing out confinement, home office should be maintained as long as possible, to allow those workers who cannot work from home to go back to work, while keeping infection risk minimal. Finally, systemic industries (with high multipliers and/or high value added per worker) should be given priority, especially those where home office is not possible.
The outbreak of COVID-19 has significantly disrupted the economy. This paper attempts to quantify the macroeconomic impact of costly and deadly disasters in recent US history, and to translate these estimates into an analysis of the likely impact of COVID-19. A costly disaster series is constructed over the sample 1980:1-2020:04 and the dynamic impact of a disaster shock on economic activity and on uncertainty is studied using a VAR. While past natural disasters are local in nature and come and go quickly, COVID-19 is a global, multiperiod event. We therefore study the dynamic responses to a sequence of large disaster shocks. Even in a fairly conservative case where COVID-19 is a 5-month shock with its magnitude calibrated by the cost of March 2020 Coronavirus relief packages, the shock is forecast to lead to a cumulative loss in industrial production of 20% and in service sector employment of nearly 39% or 55 million jobs over the next 12 months. For each month that a shock of a given magnitude is prolonged from the base case, heightened macro uncertainty persists for another month.