IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2509.26517.html

Persuasion Effects in Regression Discontinuity Designs

Author

Listed:
  • Sung Jae Jun
  • Sokbae Lee

Abstract

We develop a framework for identifying and estimating persuasion effects in regression discontinuity (RD) designs. The RD persuasion rate measures the probability that individuals at the threshold would take the action if exposed to a persuasive message, given that they would not take the action without exposure. We present identification results for both sharp and fuzzy RD designs, derive sharp bounds under various data scenarios, and extend the analysis to local compliers. Estimation and inference rely on local polynomial regression, enabling straightforward implementation with standard RD tools. Applications to public health and media illustrate its empirical relevance.

Suggested Citation

  • Sung Jae Jun & Sokbae Lee, 2025. "Persuasion Effects in Regression Discontinuity Designs," Papers 2509.26517, arXiv.org.
    • Handle: RePEc:arx:papers:2509.26517
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2509.26517
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Caroline Le Pennec & Vincent Pons, 2023. "How do Campaigns Shape Vote Choice? Multicountry Evidence from 62 Elections and 56 TV Debates," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(2), pages 703-767.
    2. Paul Brehm & Martin Saavedra, 2025. "Vaccines and Verdicts: How Smallpox Court Decisions Affect Anti-Vaccine Discourse and Mortality," The Economic Journal, Royal Economic Society, vol. 135(668), pages 1229-1260.
    3. Michal Kolesár & Christoph Rothe, 2018. "Inference in Regression Discontinuity Designs with a Discrete Running Variable," American Economic Review, American Economic Association, vol. 108(8), pages 2277-2304, August.
    4. Guido Imbens & Stefan Wager, 2019. "Optimized Regression Discontinuity Designs," The Review of Economics and Statistics, MIT Press, vol. 101(2), pages 264-278, May.
    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. Adam C. Sales & Ben B. Hansen, 2020. "Limitless Regression Discontinuity," Journal of Educational and Behavioral Statistics, , vol. 45(2), pages 143-174, April.
    2. Blaise Melly & Rafael Lalive, 2020. "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften dp2016, Universitaet Bern, Departement Volkswirtschaft.
    3. Timothy B. Armstrong & Michal Kolesár & Soonwoo Kwon, 2020. "Bias-Aware Inference in Regularized Regression Models," Working Papers 2020-2, Princeton University. Economics Department..
    4. Koohyun Kwon & Soonwoo Kwon, 2020. "Inference in Regression Discontinuity Designs under Monotonicity," Papers 2011.14216, arXiv.org.
    5. Yang He & Otávio Bartalotti, 2020. "Wild bootstrap for fuzzy regression discontinuity designs: obtaining robust bias-corrected confidence intervals," The Econometrics Journal, Royal Economic Society, vol. 23(2), pages 211-231.
    6. Claudia Noack & Christoph Rothe, 2024. "Bias‐Aware Inference in Fuzzy Regression Discontinuity Designs," Econometrica, Econometric Society, vol. 92(3), pages 687-711, May.
    7. Martin Huber, 2019. "An introduction to flexible methods for policy evaluation," Papers 1910.00641, arXiv.org.
    8. Kikuta, Kyosuke & Uesugi, Mamoru, 2023. "Do Politically Irrelevant Events Cause Conflict? The Cross-continental Effects of European Professional Football on Protests in Africa," International Organization, Cambridge University Press, vol. 77(1), pages 179-216, January.
    9. Yingying Dong & Michal Kolesár, 2023. "When can we ignore measurement error in the running variable?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 735-750, August.
    10. Edmark, Karin & Persson, Lovisa, 2021. "The impact of attending an independent upper secondary school: Evidence from Sweden using school ranking data," Economics of Education Review, Elsevier, vol. 84(C).
    11. Dean Eckles & Nikolaos Ignatiadis & Stefan Wager & Han Wu, 2020. "Noise-Induced Randomization in Regression Discontinuity Designs," Papers 2004.09458, arXiv.org, revised Mar 2025.
    12. Yi Zhang & Eli Ben-Michael & Kosuke Imai, 2022. "Safe Policy Learning under Regression Discontinuity Designs with Multiple Cutoffs," Papers 2208.13323, arXiv.org, revised Sep 2024.
    13. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    14. Myoung-Jae Lee & Hyae-Chong Shim & Sang Soo Park, 2023. "Regression Discontinuity with Integer Score and Non-Integer Cutoff," Korean Economic Review, Korean Economic Association, vol. 39, pages 73-101.
    15. Kikuta,Kyosuke & Uesugi.Mamoru, 2022. "Do politically irrelevant events cause conflict? the cross-continental effects of European professional football on protests in Africa," IDE Discussion Papers 866, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    16. Rahul Singh & Moses Stewart, 2025. "Placebo Discontinuity Design," Papers 2507.12693, arXiv.org.
    17. Jeff DeSimone & Daniel Grossman & Nicolas Ziebarth, 2023. "Regression Discontinuity Evidence on the Effectiveness of the Minimum Legal E-cigarette Purchasing Age," American Journal of Health Economics, University of Chicago Press, vol. 9(3), pages 461-485.
    18. Giesecke, Matthias & Jäger, Philipp, 2021. "Pension incentives and labor supply: Evidence from the introduction of universal old-age assistance in the UK," Journal of Public Economics, Elsevier, vol. 203(C).
    19. Atı̇la Abdulkadı̇roğlu & Joshua D. Angrist & Yusuke Narita & Parag Pathak, 2022. "Breaking Ties: Regression Discontinuity Design Meets Market Design," Econometrica, Econometric Society, vol. 90(1), pages 117-151, January.
    20. Serena Canaan & Pierre Mouganie & Peng Zhang, 2025. "The long‐run educational benefits of high‐achieving classrooms," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 44(4), pages 1347-1373, September.

    More about this item

    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:arx:papers:2509.26517. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.