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Dealing with COVID-19 Across Countries

Project Overview

I evaluate the effects of COVID-19 across countries. Social distancing implies potentially long periods of no income, which may be too hard to sustain in some places. In addition, low income countries have less jobs that can be performed from home, and lower hospital capacity. To study this, I extend the SIR model in Eichenbaum et al. (2020), with a subsistence level of consumption, heterogenous work-at-home possibilities, and hospital capacity constraints. Subsistence consumption reduces the elasticity of labor when income is low, and working from home milds the recession down without risking contagion. Lower hospital capacity increases the death rate per infected individual. I find that the health crisis is worse in low income countries, with higher infection and death rates, while the economic crisis is milder. More precisely, a decrease in income per capita of 1% increases infections by almost 300 people per million, and the number of deaths by 12 per million. On the other hand, it reduces the fall of consumption relative to steady state by 0.03%. Using Google mobility data, I confirm that traffic around workplaces has fallen more in relatively rich countries, consistent with the theory. I argue that a better strategy in low income countries would consist of loans to finance imports: assuming an interest rate of 5%, the optimal loan would reduce the number of infected in U.S. by 8.4%, and in Mexico by 11.7%. In addition, loans are cheaper in low income countries: in the U.S., the optimal loan is worth $4,700 per person, while in Mexico it is $909.

Study Design

Cross-sectional study

Project Keywords

COVID-19; Coronavirus; Social Distancing; Low income countries; Inequality.

Principal Investigator

Name: Loris

Title: PhD.

Department or Unit: Department of Economics

Organization: University Of New Hampshire

Co-Project Investigators

    Funding Source


    Expected Study Timeline

    May 1, 2020 to May 1, 2021

    Study Design

    Cross-sectional study

    Primary Methods of Data Collection


    Unit of Analysis


    Study Population(s)


    Sample Size


    Geographic Focus Area(s)


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