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Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020
Open accessAbstract
The collapse of economic activity in 2020 from COVID-19 has been immense. An important question is how much of that collapse resulted from government-imposed restrictions versus people voluntarily choosing to stay home to avoid infection. This paper examines the drivers of the economic slowdown using cellular phone records data on customer visits to more than 2.25 million individual businesses across 110 different industries. Comparing consumer behavior over the crisis within the same commuting zones but across state and county boundaries with different policy regimes suggests that legal shutdown orders account for only a modest share of the massive changes to consumer behavior (and that tracking county-level policy conditions is significantly more accurate than using state-level policies alone). While overall consumer traffic fell by 60 percentage points, legal restrictions explain only 7 percentage points of this. Individual choices were far more important and seem tied to fears of infection. Traffic started dropping before the legal orders were in place; was highly influenced by the number of COVID deaths reported in the county; and showed a clear shift by consumers away from busier, more crowded stores toward smaller, less busy stores in the same industry. States that repealed their shutdown orders saw symmetric, modest recoveries in consumer visits, further supporting the small estimated effect of policy. Although the shutdown orders had little aggregate impact, they did have a significant effect in reallocating consumer visits away from "nonessential" to "essential" businesses and from restaurants and bars toward groceries and other food sellers.
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“we tend to find relatively small reductions in travel due to SIPOs.”
From Policy evaluation during a pandemic (2023) · cites this paper as Goolsbee and Syverson (2021)
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“First, our results on the effect of SIPOs on travel are more similar to existing estimates (e.g., Goolsbee and Syverson (2021)).”
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Metadata
- Authors
- Goolsbee, A., & Syverson, C.
- Affiliations
- University of Chicago (US)
- Corresponding author
- Goolsbee, Austan
- Venue
- Journal of Public Economics
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 193
- Pages
- 104311
- ISSN
- 0047-2727 (ISSN-L)
- PMC
- PMC7687454
- OpenAlex
- W3037490325
- Cited by
- 749
- References
- 55
- Citations by year
- 2026: 35 · 2025: 71 · 2024: 84 · 2023: 117 · 2022: 182 · 2021: 163
- FWCI
- 119.40
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Public Economics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › COVID-19 Pandemic Impacts
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
- Keywords
- COVID-19 pandemic, economic decline, consumer behavior, fear of infection, business closures, store traffic, essential businesses, COVID-19 mortality, policy effectiveness, restaurant closures, food retail
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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