IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_8929.html
   My bibliography  Save this paper

The Association of Opening K-12 Schools and Colleges with the Spread of Covid-19 in the United States: County-Level Panel Data Analysis

Author

Listed:
  • Victor Chernozhukov
  • Hiroyuki Kasahara
  • Paul Schrimpf

Abstract

This paper empirically examines how the opening of K-12 schools and colleges is associated with the spread of COVID-19 using county-level panel data in the United States. Using data on foot traffic and K-12 school opening plans, we analyze how an increase in visits to schools and opening schools with different teaching methods (in-person, hybrid, and remote) is related to the 2-weeks forward growth rate of confirmed COVID-19 cases. Our debiased panel data regression analysis with a set of county dummies, interactions of state and week dummies, and other controls shows that an increase in visits to both K-12 schools and colleges is associated with a subsequent increase in case growth rates. The estimates indicate that fully opening K-12 schools with in-person learning is associated with a 5 (SE = 2) percentage points increase in the growth rate of cases. We also find that the positive association of K-12 school visits or in-person school openings with case growth is stronger for counties that do not require staff to wear masks at schools. These results have a causal interpretation in a structural model with unobserved county and time confounders. Sensitivity analysis shows that the baseline results are robust to timing assumptions and alternative specifications.

Suggested Citation

  • Victor Chernozhukov & Hiroyuki Kasahara & Paul Schrimpf, 2021. "The Association of Opening K-12 Schools and Colleges with the Spread of Covid-19 in the United States: County-Level Panel Data Analysis," CESifo Working Paper Series 8929, CESifo.
  • Handle: RePEc:ces:ceswps:_8929
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp8929.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Serina Chang & Emma Pierson & Pang Wei Koh & Jaline Gerardin & Beth Redbird & David Grusky & Jure Leskovec, 2021. "Mobility network models of COVID-19 explain inequities and inform reopening," Nature, Nature, vol. 589(7840), pages 82-87, January.
    2. Wright, Austin L. & Sonin, Konstantin & Driscoll, Jesse & Wilson, Jarnickae, 2020. "Poverty and economic dislocation reduce compliance with COVID-19 shelter-in-place protocols," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 544-554.
    3. Jinyong Hahn & Whitney Newey, 2004. "Jackknife and Analytical Bias Reduction for Nonlinear Panel Models," Econometrica, Econometric Society, vol. 72(4), pages 1295-1319, July.
    4. Dan Goldhaber & Scott A. Imberman & Katharine O. Strunk & Bryant G. Hopkins & Nate Brown & Erica Harbatkin & Tara Kilbride, 2022. "To What Extent Does In‐Person Schooling Contribute To The Spread Of Covid‐19? Evidence From Michigan And Washington," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 41(1), pages 318-349, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kurmann, André & Lalé, Etienne, 2021. "School Closures and Effective In-Person Learning during COVID-19: When, Where, and for Whom," School of Economics Working Paper Series 2021-18, LeBow College of Business, Drexel University.
    2. Marc Diederichs & Reyn van Ewijk & Ingo E. Isphording & Nico Pestel, 2022. "Schools under mandatory testing can mitigate the spread of SARS-CoV-2," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(26), pages 2201724119-, June.
    3. Emanuele Amodio & Michele Battisti & Antonio Francesco Gravina & Andrea Mario Lavezzi & Giuseppe Maggio, 2023. "School‐age vaccination, school openings and Covid‐19 diffusion," Health Economics, John Wiley & Sons, Ltd., vol. 32(5), pages 1084-1100, May.
    4. Dan Goldhaber & Scott A. Imberman & Katharine O. Strunk & Bryant G. Hopkins & Nate Brown & Erica Harbatkin & Tara Kilbride, 2022. "To What Extent Does In‐Person Schooling Contribute To The Spread Of Covid‐19? Evidence From Michigan And Washington," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 41(1), pages 318-349, January.
    5. Koppa, Vijetha & West, Jeremy, 2022. "School reopenings, COVID-19, and employment," Economics Letters, Elsevier, vol. 212(C).
    6. Lattanzio, Salvatore, 2024. "Schools and the transmission of Sars-Cov-2: Evidence from Italy," Economics & Human Biology, Elsevier, vol. 52(C).
    7. Amodio, Emanuele & Battisti, Michele & Kourtellos, Andros & Maggio, Giuseppe & Maida, Carmelo Massimo, 2022. "Schools opening and Covid-19 diffusion: Evidence from geolocalized microdata," European Economic Review, Elsevier, vol. 143(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Victor Chernozhukov & Hiroyuki Kasahara & Paul Schrimpf, 2021. "The association of opening K–12 schools with the spread of COVID-19 in the United States: County-level panel data analysis," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(42), pages 2103420118-, October.
    2. Byungjin Park & Joonmo Cho, 2023. "COVID-19 and Age Disparity in Credit Card Expenditures in Korea: Implications on the Government Relief Fund," SAGE Open, , vol. 13(4), pages 21582440231, December.
    3. Haddou, Samira, 2024. "Determinants of CDS in core and peripheral European countries: A comparative study during crisis and calm periods," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    4. Taisuke Otsu & Martin Pesendorfer & Yuya Sasaki & Yuya Takahashi, 2022. "Estimation Of (Static Or Dynamic) Games Under Equilibrium Multiplicity," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1165-1188, August.
    5. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.
    6. Hoderlein, Stefan & White, Halbert, 2012. "Nonparametric identification in nonseparable panel data models with generalized fixed effects," Journal of Econometrics, Elsevier, vol. 168(2), pages 300-314.
    7. Nicola Fuchs-Schündeln & Dirk Krueger & André Kurmann & Etienne Lalé & Alexander Ludwig & Irina Popova, 2023. "The Fiscal and Welfare Effects of Policy Responses to the Covid-19 School Closures," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(1), pages 35-98, March.
    8. Hou, Yanxi & Leng, Xuan & Peng, Liang & Zhou, Yinggang, 2024. "Panel quantile regression for extreme risk," Journal of Econometrics, Elsevier, vol. 240(1).
    9. Lee, Yoon-Jin & Okui, Ryo & Shintani, Mototsugu, 2018. "Asymptotic inference for dynamic panel estimators of infinite order autoregressive processes," Journal of Econometrics, Elsevier, vol. 204(2), pages 147-158.
    10. repec:spo:wpmain:info:hdl:2441/eu4vqp9ompqllr09ij4j0h0h1 is not listed on IDEAS
    11. Anindya Ghose & Beibei Li & Meghanath Macha & Chenshuo Sun & Natasha Ying Zhang Foutz, 2020. "Trading Privacy for the Greater Social Good: How Did America React During COVID-19?," Papers 2006.05859, arXiv.org.
    12. Anubhab Gupta & Heng Zhu & Miki Khanh Doan & Aleksandr Michuda & Binoy Majumder, 2021. "Economic Impacts of the COVID−19 Lockdown in a Remittance‐Dependent Region," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(2), pages 466-485, March.
    13. Panarello, Demetrio, 2021. "Economic insecurity, conservatism, and the crisis of environmentalism: 30 years of evidence," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    14. Andersen, Torben G. & Fusari, Nicola & Todorov, Viktor & Varneskov, Rasmus T., 2019. "Unified inference for nonlinear factor models from panels with fixed and large time span," Journal of Econometrics, Elsevier, vol. 212(1), pages 4-25.
    15. Harbatkin, Erica & Strunk, Katharine O. & McIlwain, Aliyah, 2023. "School turnaround in a pandemic: An examination of the outsized implications of COVID-19 on low-performing turnaround schools, districts, and their communities," Economics of Education Review, Elsevier, vol. 97(C).
    16. Klein Teeselink, Bouke & Potter van Loon, Rogier J.D. & van den Assem, Martijn J. & van Dolder, Dennie, 2020. "Incentives, performance and choking in darts," Journal of Economic Behavior & Organization, Elsevier, vol. 169(C), pages 38-52.
    17. Arda Gitmez & Konstantine Sonin & Austin L. Wright, 2020. "Political Economy of Crisis Response," Working Papers 2020-68, Becker Friedman Institute for Research In Economics.
    18. Aguirregabiria, Victor & Gu, Jiaying & Luo, Yao, 2021. "Sufficient statistics for unobserved heterogeneity in structural dynamic logit models," Journal of Econometrics, Elsevier, vol. 223(2), pages 280-311.
    19. Jesus M. Carro & Alejandra Traferri, 2014. "State Dependence And Heterogeneity In Health Using A Bias‐Corrected Fixed‐Effects Estimator," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 181-207, March.
    20. Dhaene, Geert & Jochmans, Koen, 2016. "Likelihood Inference In An Autoregression With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1178-1215, October.
    21. Lu, Xuefei & Borgonovo, Emanuele, 2023. "Global sensitivity analysis in epidemiological modeling," European Journal of Operational Research, Elsevier, vol. 304(1), pages 9-24.

    More about this item

    Keywords

    K-12 school openings; in-person; hybrid; and remote; mask-wearing requirements for staff; foot traffic data; debiased estimator;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_8929. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.