IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2503.06046.html
   My bibliography  Save this paper

Bounding the Effect of Persuasion with Monotonicity Assumptions: Reassessing the Impact of TV Debates

Author

Listed:
  • Sung Jae Jun
  • Sokbae Lee

Abstract

Televised debates between presidential candidates are often regarded as the exemplar of persuasive communication. Yet, recent evidence from Le Pennec and Pons (2023) indicates that they may not sway voters as strongly as popular belief suggests. We revisit their findings through the lens of the persuasion rate and introduce a robust framework that does not require exogenous treatment, parallel trends, or credible instruments. Instead, we leverage plausible monotonicity assumptions to partially identify the persuasion rate and related parameters. Our results reaffirm that the sharp upper bounds on the persuasive effects of TV debates remain modest.

Suggested Citation

  • Sung Jae Jun & Sokbae Lee, 2025. "Bounding the Effect of Persuasion with Monotonicity Assumptions: Reassessing the Impact of TV Debates," Papers 2503.06046, arXiv.org, revised Apr 2025.
    • Handle: RePEc:arx:papers:2503.06046
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2503.06046
    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. Tsunao Okumura & Emiko Usui, 2014. "Concave‐monotone treatment response and monotone treatment selection: With an application to the returns to schooling," Quantitative Economics, Econometric Society, vol. 5, pages 175-194, March.
    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. Sung Jae Jun & Sokbae Lee, 2024. "Causal Inference Under Outcome-Based Sampling with Monotonicity Assumptions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 998-1009, July.
    2. Sungwon Lee, 2024. "Partial identification and inference for conditional distributions of treatment effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 107-127, January.
    3. Sung Jae Jun & Sokbae (Simon) Lee, 2020. "Causal inference in case-control studies," CeMMAP working papers CWP19/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Wooyoung Kim & Koohyun Kwon & Soonwoo Kwon & Sokbae Lee, 2018. "The identification power of smoothness assumptions in models with counterfactual outcomes," Quantitative Economics, Econometric Society, vol. 9(2), pages 617-642, July.
    5. Demuynck, Thomas, 2015. "Bounding average treatment effects: A linear programming approach," Economics Letters, Elsevier, vol. 137(C), pages 75-77.
    6. Stefan Boes, 2009. "Bounds on Counterfactual Distributions Under Semi-Monotonicity Constraints," SOI - Working Papers 0920, Socioeconomic Institute - University of Zurich.
    7. Riako Granzier & Vincent Pons & Clemence Tricaud, 2023. "Coordination and Bandwagon Effects: How Past Rankings Shape the Behavior of Voters and Candidates," American Economic Journal: Applied Economics, American Economic Association, vol. 15(4), pages 177-217, October.
    8. Stefan Boes, 2010. "Convex Treatment Response and Treatment Selection," SOI - Working Papers 1001, Socioeconomic Institute - University of Zurich.
    9. Das, Tirthatanmoy & Polachek, Solomon, 2017. "Micro Foundations of Earnings Differences," IZA Discussion Papers 10922, Institute of Labor Economics (IZA).
    10. Nobuyoshi Kikuchi, 2017. "Intergenerational Transmission of Education in Japan: Nonparametric Bounds Analysis with Multiple Treatments," ISER Discussion Paper 1011, Institute of Social and Economic Research, The University of Osaka.

    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:arx:papers:2503.06046. 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.