IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/30618.html
   My bibliography  Save this paper

The Impact of Large-Scale Social Media Advertising Campaigns on COVID-19 Vaccination: Evidence from Two Randomized Controlled Trials

Author

Listed:
  • Lisa Y. Ho
  • Emily Breza
  • Marcella Alsan
  • Abhijit Banerjee
  • Arun G. Chandrasekhar
  • Fatima Cody Stanford
  • Renato Fior
  • Paul Goldsmith-Pinkham
  • Kelly Holland
  • Emily Hoppe
  • Louis-Maël Jean
  • Lucy Ogbu-Nwobodo
  • Benjamin A. Olken
  • Carlos Torres
  • Pierre-Luc Vautrey
  • Erica Warner
  • Esther Duflo

Abstract

COVID-19 vaccines are widely available in wealthy countries, yet many people remain unvaccinated. Understanding the effectiveness -- or lack thereof -- of popular vaccination campaign strategies is therefore critical. In this paper, we report results from two studies that tested strategies central to current vaccination outreach: (1) direct communication by health professionals addressing questions about vaccination and (2) efforts to motivate individuals to promote vaccination within their social networks. Near the peak of the Omicron wave, doctor- and nurse-produced videos were disseminated to 17.8 million Facebook users in the US and 11.5 million in France. In both countries, we cannot reject the null of no effect of any of the interventions on any of the outcome variables (first doses - US and France, second doses and boosters - US). We can reject very small effects on first doses during the interventions in both countries (0.16pp - US, 0.021pp - France). In contrast with similar campaigns earlier in the pandemic to encourage health-preserving behaviors, messaging at this stage of the pandemic -- whether aimed at the unvaccinated or those tasked with encouraging others -- did not change vaccination decisions.

Suggested Citation

  • Lisa Y. Ho & Emily Breza & Marcella Alsan & Abhijit Banerjee & Arun G. Chandrasekhar & Fatima Cody Stanford & Renato Fior & Paul Goldsmith-Pinkham & Kelly Holland & Emily Hoppe & Louis-Maël Jean & Luc, 2022. "The Impact of Large-Scale Social Media Advertising Campaigns on COVID-19 Vaccination: Evidence from Two Randomized Controlled Trials," NBER Working Papers 30618, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:30618
    Note: DEV EH LS PE
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w30618.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hainmueller, Jens, 2012. "Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies," Political Analysis, Cambridge University Press, vol. 20(1), pages 25-46, January.
    2. Abhijit Banerjee & Arun G Chandrasekhar & Esther Duflo & Matthew O Jackson, 2019. "Using Gossips to Spread Information: Theory and Evidence from Two Randomized Controlled Trials," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(6), pages 2453-2490.
    3. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "Inference on Treatment Effects after Selection among High-Dimensional Controlsâ€," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(2), pages 608-650.
    4. Marcella Alsan & Sarah Eichmeyer, 2024. "Experimental Evidence on the Effectiveness of Nonexperts for Improving Vaccine Demand," American Economic Journal: Economic Policy, American Economic Association, vol. 16(1), pages 394-414, February.
    5. Vivi Alatas & Arun G. Chandrasekhar & Markus Mobius & Benjamin A. Olken & Cindy Paladines, 2019. "When Celebrities Speak: A Nationwide Twitter Experiment Promoting Vaccination In Indonesia," NBER Working Papers 25589, National Bureau of Economic Research, Inc.
    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. Islam, Asad & Kusnadi, Gita & Rezki, Jahen & Sim, Armand & van Empel, Giovanni & Vlassopoulos, Michael & Zenou, Yves, 2023. "Addressing Vaccine Hesitancy Using Local Ambassadors: A Randomized Controlled Trial in Indonesia," IZA Discussion Papers 15899, Institute of Labor Economics (IZA).

    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. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
    2. Michael C. Knaus, 2021. "A double machine learning approach to estimate the effects of musical practice on student’s skills," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 282-300, January.
    3. Angelucci, Manuela & Bennett, Daniel M, 2022. "Depression, Pharmacotherapy, and the Demand for a Novel Health Product," IZA Discussion Papers 15832, Institute of Labor Economics (IZA).
    4. Everding, Jakob & Marcus, Jan, 2020. "The effect of unemployment on the smoking behavior of couples," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 29(2), pages 154-170.
    5. Cátia Batista & Marcel Fafchamps & Pedro C Vicente, 2022. "Keep It Simple: A Field Experiment on Information Sharing among Strangers [Changing Saving and Investment Behavior: The Impact of Financial Literacy Training and Reminders on Micro-Businesses]," The World Bank Economic Review, World Bank, vol. 36(4), pages 857-888.
    6. Li, Jian & Zhou, Junjie & Chen, Ying-Ju, 2021. "The Limit of Targeting in Networks," ISU General Staff Papers 202112081957590000, Iowa State University, Department of Economics.
    7. Li, Jian & Zhou, Junjie & Chen, Ying-Ju, 2022. "The limit of targeting in networks," Journal of Economic Theory, Elsevier, vol. 201(C).
    8. Barrera,Oscar & Macours,Karen & Premand,Patrick & Vakis,Renos, 2020. "Texting Parents about Early Child Development : Behavioral Changes and Unintended Social Effects," Policy Research Working Paper Series 9492, The World Bank.
    9. Marianne BLÉHAUT & Xavier D'HAULTFOEUILLE & Jérémy L'HOUR & Alexandre B. TSYBAKOV, 2020. "An alternative to synthetic control for models with many covariates under sparsity," Working Papers 2020-17, Center for Research in Economics and Statistics.
    10. Carattini, Stefano & Gosnell, Greer & Tavoni, Alessandro, 2020. "How developed countries can learn from developing countries to tackle climate change," World Development, Elsevier, vol. 127(C).
    11. Jessica Goldberg & Mario Macis & Pradeep Chintagunta, 2023. "Incentivized Peer Referrals for Tuberculosis Screening: Evidence from India," American Economic Journal: Applied Economics, American Economic Association, vol. 15(1), pages 259-291, January.
    12. Shehryar Munir & Farah Said & Umar Taj & Maida Zafar, 2022. "Digital 'nudges' to increase childhood vaccination compliance: Evidence from Pakistan," Papers 2209.06624, arXiv.org.
    13. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    14. Alex Chin & Dean Eckles & Johan Ugander, 2022. "Evaluating Stochastic Seeding Strategies in Networks," Management Science, INFORMS, vol. 68(3), pages 1714-1736, March.
    15. Manuela Angelucci & Daniel Bennett, 2024. "The Economic Impact of Depression Treatment in India: Evidence from Community-Based Provision of Pharmacotherapy," American Economic Review, American Economic Association, vol. 114(1), pages 169-198, January.
    16. Zhang, Li & Xie, Lunyu & Zheng, Xinye, 2023. "Across a few prohibitive miles: The impact of the Anti-Poverty Relocation Program in China," Journal of Development Economics, Elsevier, vol. 160(C).
    17. Davide Viviano & Jelena Bradic, 2021. "Dynamic covariate balancing: estimating treatment effects over time with potential local projections," Papers 2103.01280, arXiv.org, revised Jan 2024.
    18. Jelena Bradic & Stefan Wager & Yinchu Zhu, 2019. "Sparsity Double Robust Inference of Average Treatment Effects," Papers 1905.00744, arXiv.org.
    19. Rafael Jimenez-Duran, 2021. "The Economics of Content Moderation: Theory and Experimental Evidence from Hate Speech on Twitter," Natural Field Experiments 00754, The Field Experiments Website.
    20. Jiménez-Durán, Rafael, 2022. "The economics of content moderation: Theory and experimental evidence from hate speech on Twitter," Working Papers 324, The University of Chicago Booth School of Business, George J. Stigler Center for the Study of the Economy and the State.

    More about this item

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    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:nbr:nberwo:30618. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.