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Cited by 283

The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.

Internal and external effects of social distancing in a pandemic

Open access
Farboodi, Maryam, Jarosch, Gregor, Shimer, Robert·2021·Journal of Economic Theory
DOI 10.1016/j.jet.2021.105293
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Abstract

We develop a quantitative framework for exploring how individuals trade off the utility benefit of social activity against the internal and external health risks that come with social interactions during a pandemic. We calibrate the model to external targets and then compare its predictions with daily data on social activity, fatalities, and the estimated effective reproduction number R ( t ) from the COVID-19 pandemic in 2020. While the laissez-faire equilibrium is consistent with much of the decline in social activity in March in the US before any formal stay-at-home orders, optimal policy further imposes immediate and highly persistent social distancing. The expected cost of COVID-19 in the US is substantial, $12,700 in the laissez-faire equilibrium and $8,100 per person under an optimal policy. Optimal policy generates this large welfare gain by shifting the composition of costs from fatalities to persistent social distancing that largely suppresses the outbreak.

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Metadata

Authors
Farboodi, M., Jarosch, G., & Shimer, R.
Venue
Journal of Economic Theory
Publisher
Elsevier BV
Published
2021-09
Volume
196
Pages
105293
ISSN
0022-0531 (ISSN-L)
DOI
10.1016/j.jet.2021.105293
OpenAlex
W4285368685
Cited by
283
References
33
FWCI
16.03
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Internal and external effects of social distancing in a pandemic. https://app.cochat.ai/papers/10.1016/j.jet.2021.105293
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Farboodi, M., Jarosch, G., & Shimer, R. (2021). Internal and external effects of social distancing in a pandemic. Journal of Economic Theory. https://doi.org/10.1016/j.jet.2021.105293

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.