The DOI matches its Crossref record; 74 of the 74 references it cites were found in a registry or an index.
Misinformation During a Pandemic
Open accessAbstract
Media outlets often present diverging, even conflicting, perspectives on reality -not only informing, but potentially misinforming audiences.We study the extent to which misinformation broadcast on mass media at the early stages of the coronavirus pandemic influenced health outcomes.We first document large differences in content between the two most popular cable news shows in the US, both on the same network, and in the adoption of preventative behaviors among viewers of these shows.Through both a selection-on-observables strategy and an instrumental variable approach, we find that areas with greater exposure to the show downplaying the threat of COVID-19 experienced a greater number of cases and deaths.We assess magnitudes through an epidemiological model highlighting the role of externalities and provide evidence that contemporaneous information exposure is a key underlying mechanism.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Measurement of Observer Agreement for Categorical Data
Landis, J. R., & Koch, G. G. (1977) · Biometrics · doi:10.2307/2529310 · Cited by 81,148
A novel coronavirus from patients with pneumonia in China, 2019
Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001017 · Cited by 28,244
Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia
Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K. S. M., Lau, E. H. Y., Wong, J. Y., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001316 · Cited by 16,575
An interactive web-based dashboard to track COVID-19 in real time
Dong, E., Du, H., & Gardner, L. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30120-1 · Cited by 10,048
WHO Declares COVID-19 a Pandemic.
Cucinotta, D., & Vanelli, M. (2020) · Acta bio-medica dell'Ateneo parmense/Acta biomedica · doi:10.23750/abm.v91i1.9397 · Cited by 7,457
First case of 2019 novel coronavirus in the United States
Holshue, M. L., DeBolt, C., Lindquist, S., Lofy, K. H., Wiesman, J., Bruce, H., Spitters, C., Ericson, K., Wilkerson, S., Tural, A., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001191 · Cited by 6,030
Unobservable Selection and Coefficient Stability: Theory and Evidence
Oster, E. (2019) · Journal of Business & Economic Statistics · doi:10.1080/07350015.2016.1227711 · Cited by 5,367
Who Benefits from State and Local Economic Development Policies?
Bartik, T. J. (1991) · doi:10.17848/9780585223940 · Cited by 2,643
Bartik Instruments: What, When, Why, and How
Goldsmith-Pinkham, P., Sorkin, I., & Swift, H. (2020) · American Economic Review · doi:10.1257/aer.20181047 · Cited by 2,521
Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities
Miguel, E., & Kremer, M. (2004) · Econometrica · doi:10.1111/j.1468-0262.2004.00481.x · Cited by 2,268
Cited by
The psychological drivers of misinformation belief and its resistance to correction
Ecker, U. K. H., Lewandowsky, S., Cook, J., Schmid, P., Fazio, L. K., Brashier, N., Kendeou, P., Vraga, E. K., & Amazeen, M. A. (2022) · Nature Reviews Psychology · doi:10.1038/s44159-021-00006-y · Cited by 1,372
Allcott, H., Boxell, L., Conway, J., Gentzkow, M., Thaler, M., & Yang, D. (2020) · Journal of Public Economics · doi:10.1016/j.jpubeco.2020.104254 · Cited by 999
Gollwitzer, A., Martel, C., Brady, W. J., Pärnamets, P., Freedman, I. G., Knowles, E. D., & Van Bavel, J. J. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-00977-7 · Cited by 609
The Cost of the Covid-19 Crisis: Lockdowns, Macroeconomic Expectations, and Consumer Spending
Coibion, O., Gorodnichenko, Y., & Weber, M. (2020) · National Bureau of Economic Research · doi:10.3386/w27141 · Cited by 477
Mental distress among U.S. adults during the COVID-19 pandemic
Twenge, J. M., & Joiner, T. E. (2020) · Journal of Clinical Psychology · doi:10.1002/jclp.23064 · Cited by 330
Metadata
- Authors
- Bursztyn, L., Rao, A., Roth, C., & Yanagizawa-Drott, D.
- Venue
- National Bureau of Economic Research
- Publisher
- National Bureau of Economic Research
- Published
- 2020-06
- OpenAlex
- W3039651429
- Cited by
- 265
- References
- 74
- Type
- report
- Language
- en
- Open access
- green
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Misinformation During a Pandemic. https://app.cochat.ai/papers/10.3386/w27417
- The paper
- Bursztyn, L., Rao, A., Roth, C., & Yanagizawa-Drott, D. (2020). Misinformation During a Pandemic. National Bureau of Economic Research. https://doi.org/10.3386/w27417
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.