IDEAS home Printed from https://ideas.repec.org/a/bla/socsci/v102y2021i5p2412-2431.html
   My bibliography  Save this article

Polarization, partisanship, and pandemic: The relationship between county‐level support for Donald Trump and the spread of Covid‐19 during the spring and summer of 2020

Author

Listed:
  • David S. Morris

Abstract

Objective Republicans and Democrats have displayed widely divergent beliefs and behaviors related to COVID‐19, creating the possibility that geographic areas with more Donald Trump supporters may be more likely to suffer from the disease. Methods I use 2016 election data, COVID‐19 case and mortality data, and multilevel linear growth models with state fixed effects to estimate the relationship between county‐level support for Donald Trump and the trajectory of cumulative COVID‐19 cases and deaths per 100,000 county residents between March 17, 2020 and August 31, 2020. Results Counties more supportive of Trump had fewer COVID‐19 cases and deaths in the early months of the pandemic. However, as the summer moved into July and August, counties less supportive of Trump stopped growth rates of COVID‐19 cases and deaths, while counties more supportive of Trump saw a trajectory of increased cases and deaths in July and August. This is likely due to the widely divergent beliefs and behaviors displayed by Republicans and Democrats toward COVID‐19. Conclusion This study underscores the power of polarization and partisanship in the public sphere, even when it comes to a public health issue.

Suggested Citation

  • David S. Morris, 2021. "Polarization, partisanship, and pandemic: The relationship between county‐level support for Donald Trump and the spread of Covid‐19 during the spring and summer of 2020," Social Science Quarterly, Southwestern Social Science Association, vol. 102(5), pages 2412-2431, September.
    • Handle: RePEc:bla:socsci:v:102:y:2021:i:5:p:2412-2431
    DOI: 10.1111/ssqu.13053
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/ssqu.13053
    Download Restriction: no
    File URL: https://libkey.io/10.1111/ssqu.13053?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. John Manuel Barrios & Yael V. Hochberg, 2020. "Risk Perception Through the Lens of Politics in the Time of the COVID-19 Pandemic," Working Papers 2020-32, Becker Friedman Institute for Research In Economics.
    2. Joshua M. Blank & Daron Shaw, 2015. "Does Partisanship Shape Attitudes toward Science and Public Policy? The Case for Ideology and Religion," The ANNALS of the American Academy of Political and Social Science, , vol. 658(1), pages 18-35, March.
    3. Bursztyn, Leonardo & Rao, Akaash & Roth, Christopher & Yanagizawa-Drott, David, 2020. "Misinformation during a Pandemic," The Warwick Economics Research Paper Series (TWERPS) 1274, University of Warwick, Department of Economics.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Ester Faia & Andreas Fuster & Vincenzo Pezone & Basit Zafar, 2024. "Biases in Information Selection and Processing: Survey Evidence from the Pandemic," The Review of Economics and Statistics, MIT Press, vol. 106(3), pages 829-847, May.
    3. Abel Brodeur & David Gray & Anik Islam & Suraiya Bhuiyan, 2021. "A literature review of the economics of COVID‐19," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1007-1044, September.
    4. Maxim Ananyev & Michael Poyker & Yuan Tian, 2021. "The safest time to fly: pandemic response in the era of Fox News," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(3), pages 775-802, July.
    5. Coibion, Olivier & Gorodnichenko, Yuriy & Weber, Michael, 2020. "The Cost of the COVID-19 Crisis: Lockdowns, Macroeconomic Expectations, and Consumer Spending," Department of Economics, Working Paper Series qt4jn1x65h, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    6. Egorov, Georgy & Enikolopov, Ruben & Makarin, Alexey & Petrova, Maria, 2021. "Divided we stay home: Social distancing and ethnic diversity," Journal of Public Economics, Elsevier, vol. 194(C).
    7. Rafkin, Charlie & Shreekumar, Advik & Vautrey, Pierre-Luc, 2021. "When guidance changes: Government stances and public beliefs," Journal of Public Economics, Elsevier, vol. 196(C).
    8. Michael Bailey & Drew M. Johnston & Martin Koenen & Theresa Kuchler & Dominic Russel & Johannes Stroebel, 2020. "Social Networks Shape Beliefs and Behavior: Evidence from Social Distancing During the COVID-19 Pandemic," NBER Working Papers 28234, National Bureau of Economic Research, Inc.
    9. Khan, Adnan & Nasim, Sanval & Shaukat, Mahvish & Stegmann, Andreas, 2021. "Building trust in the state with information: Evidence from urban Punjab," Journal of Public Economics, Elsevier, vol. 202(C).
    10. Shoji, Masahiro & Cato, Susumu & Ito, Asei & Iida, Takashi & Ishida, Kenji & Katsumata, Hiroto & McElwain, Kenneth Mori, 2022. "Mobile health technology as a solution to self-control problems: The behavioral impact of COVID-19 contact tracing apps in Japan," Social Science & Medicine, Elsevier, vol. 306(C).
    11. J Anthony Cookson & Joseph E Engelberg & William Mullins & Hui Chen, 0. "Does Partisanship Shape Investor Beliefs? Evidence from the COVID-19 Pandemic," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(4), pages 863-893.
    12. Burcu Ozgun & Tom Broekel, 2024. "Saved by the news? COVID-19 in German news and its relationship with regional mobility behaviour," Regional Studies, Taylor & Francis Journals, vol. 58(2), pages 365-380, February.
    13. Lea-Rachel Kosnik & Allen Bellas, 2020. "Drivers of COVID-19 Stay at Home Orders: Epidemiologic, Economic, or Political Concerns?," Economics of Disasters and Climate Change, Springer, vol. 4(3), pages 503-514, October.
    14. Allcott, Hunt & Boxell, Levi & Conway, Jacob & Gentzkow, Matthew & Thaler, Michael & Yang, David, 2020. "Polarization and public health: Partisan differences in social distancing during the coronavirus pandemic," Journal of Public Economics, Elsevier, vol. 191(C).
    15. Milosh, Maria & Painter, Marcus & Sonin, Konstantin & Van Dijcke, David & Wright, Austin L., 2021. "Unmasking partisanship: Polarization undermines public response to collective risk," Journal of Public Economics, Elsevier, vol. 204(C).
    16. Nicolás Ajzenman & Tiago Cavalcanti & Daniel Da Mata, 2023. "More than Words: Leaders' Speech and Risky Behavior during a Pandemic," American Economic Journal: Economic Policy, American Economic Association, vol. 15(3), pages 351-371, August.
    17. Ströbel, Johannes & Bailey, Michael & Johnston, Drew & Koenen, Martin & Kuchler, Theresa & Russel, Dominic, 2020. "Social Distancing During a Pandemic - The Role of Friends," CEPR Discussion Papers 15593, C.E.P.R. Discussion Papers.
    18. Eslami, Keyvan & Lee, Hyunju, 2024. "Overreaction and the value of information in a pandemic," European Economic Review, Elsevier, vol. 161(C).
    19. Christopher Avery & William Bossert & Adam Clark & Glenn Ellison & Sara Fisher Ellison, 2020. "An Economist's Guide to Epidemiology Models of Infectious Disease," Journal of Economic Perspectives, American Economic Association, vol. 34(4), pages 79-104, Fall.
    20. Nicolás Ajzenman & Tiago Cavalcanti & Daniel Da Mata, 2020. "More than Words: Leaders' Speech and Risky Behavior During a Pandemic," Department of Economics Working Papers wp_gob_2020_03, Universidad Torcuato Di Tella.

    More about this item

    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:bla:socsci:v:102:y:2021:i:5:p:2412-2431. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0038-4941 .

    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.