IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/18428.html
   My bibliography  Save this paper

Persuasion with Limited Data: A Case-Based Approach

Author

Listed:
  • Alon, Shiri
  • Auster, Sarah
  • Gayer, Gabi
  • Minardi, Stefania

Abstract

A strategic sender collects data with the goal of persuading a receiver to adopt a new action. The receiver assesses the profitability of adopting the action by following a classical statistics approach: she forms an estimate via the similarity-weighted empirical frequencies of outcomes in past cases, sharing some attributes with the problem at hand. The sender has control over the characteristics of the sampled cases and discloses the outcomes of his study truthfully. We characterize the sender's optimal sampling strategy as the outcome of a greedy algorithm. The sender provides more relevant data–consisting of observations sharing relatively more characteristics with the current problem–when the sampling capacity is low, when a large amount of initial public data is available, and when the estimated benefit of adoption according to this public data is low. Competition between senders curbs incentives for biasing the receiver's estimate and leads to more balanced datasets.

Suggested Citation

  • Alon, Shiri & Auster, Sarah & Gayer, Gabi & Minardi, Stefania, 2023. "Persuasion with Limited Data: A Case-Based Approach," CEPR Discussion Papers 18428, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:18428
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP18428
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Au, Pak Hung & Kawai, Keiichi, 2020. "Competitive information disclosure by multiple senders," Games and Economic Behavior, Elsevier, vol. 119(C), pages 56-78.
    2. Glazer, Jacob & Rubinstein, Ariel, 2001. "Debates and Decisions: On a Rationale of Argumentation Rules," Games and Economic Behavior, Elsevier, vol. 36(2), pages 158-173, August.
    3. Itzhak Gilboa & David Schmeidler, 1995. "Case-Based Decision Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(3), pages 605-639.
    4. Emeric Henry & Marco Ottaviani, 2019. "Research and the Approval Process: The Organization of Persuasion," American Economic Review, American Economic Association, vol. 109(3), pages 911-955, March.
    5. Antoine Billot & Itzhak Gilboa & Dov Samet & David Schmeidler, 2012. "Probabilities as Similarity-Weighted Frequencies," World Scientific Book Chapters, in: Case-Based Predictions An Axiomatic Approach to Prediction, Classification and Statistical Learning, chapter 7, pages 169-184, World Scientific Publishing Co. Pte. Ltd..
    6. Kosterina, Svetlana, 2022. "Persuasion with unknown beliefs," Theoretical Economics, Econometric Society, vol. 17(3), July.
    7. Isabelle Brocas & Juan D. Carrillo, 2007. "Influence through ignorance," RAND Journal of Economics, RAND Corporation, vol. 38(4), pages 931-947, December.
    8. Matthew Gentzkow & Emir Kamenica, 2017. "Competition in Persuasion," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(1), pages 300-322.
    9. Xiaoyu Cheng, 2020. "Ambiguous Persuasion: An Ex-Ante Formulation," Papers 2010.05376, arXiv.org, revised Nov 2023.
    10. Simone Galperti, 2019. "Persuasion: The Art of Changing Worldviews," American Economic Review, American Economic Association, vol. 109(3), pages 996-1031, March.
    11. Le Treust, Maël & Tomala, Tristan, 2019. "Persuasion with limited communication capacity," Journal of Economic Theory, Elsevier, vol. 184(C).
    12. Gayer, Gabrielle, 2010. "Perception of probabilities in situations of risk: A case based approach," Games and Economic Behavior, Elsevier, vol. 68(1), pages 130-143, January.
    13. Beauchêne, Dorian & Li, Jian & Li, Ming, 2019. "Ambiguous persuasion," Journal of Economic Theory, Elsevier, vol. 179(C), pages 312-365.
    14. Golosnoy, Vasyl & Okhrin, Yarema, 2008. "General uncertainty in portfolio selection: A case-based decision approach," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 718-734, September.
    15. Eduardo Perez-Richet, 2014. "Interim Bayesian Persuasion: First Steps," American Economic Review, American Economic Association, vol. 104(5), pages 469-474, May.
    16. Patil, Sanket & Salant, Yuval, 2024. "Optimal sample sizes and statistical decision rules," Theoretical Economics, Econometric Society, vol. 19(2), May.
    17. Blonski, Matthias, 1999. "Social learning with case-based decisions," Journal of Economic Behavior & Organization, Elsevier, vol. 38(1), pages 59-77, January.
    18. Piotr Dworczak & Alessandro Pavan, 2022. "Preparing for the Worst but Hoping for the Best: Robust (Bayesian) Persuasion," Econometrica, Econometric Society, vol. 90(5), pages 2017-2051, September.
    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. Emir Kamenica & Kyungmin Kim & Andriy Zapechelnyuk, 2021. "Bayesian persuasion and information design: perspectives and open issues," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 72(3), pages 701-704, October.
    2. Koessler, Frederic & Laclau, Marie & Renault, Jérôme & Tomala, Tristan, 2022. "Long information design," Theoretical Economics, Econometric Society, vol. 17(2), May.
    3. Frédéric Koessler & Marie Laclau & Jerôme Renault & Tristan Tomala, 2022. "Long information design," Post-Print hal-03700394, HAL.
    4. Jacopo Bizzotto & Adrien Vigier, 2021. "Can a better informed listener be easier to persuade?," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 72(3), pages 705-721, October.
    5. Wu, Wenhao, 2023. "Sequential Bayesian persuasion," Journal of Economic Theory, Elsevier, vol. 214(C).
    6. Frédéric Koessler & Marie Laclau & Jerôme Renault & Tristan Tomala, 2022. "Long information design," PSE-Ecole d'économie de Paris (Postprint) hal-03700394, HAL.
    7. Pe[combining cedilla]ski, Marcin, 2011. "Prior symmetry, similarity-based reasoning, and endogenous categorization," Journal of Economic Theory, Elsevier, vol. 146(1), pages 111-140, January.
    8. Tsakas, Elias & Tsakas, Nikolas, 2021. "Noisy persuasion," Games and Economic Behavior, Elsevier, vol. 130(C), pages 44-61.
    9. Han Bleichrodt & Martin Filko & Amit Kothiyal & Peter P. Wakker, 2017. "Making Case-Based Decision Theory Directly Observable," American Economic Journal: Microeconomics, American Economic Association, vol. 9(1), pages 123-151, February.
    10. Golosnoy, Vasyl & Okhrin, Yarema, 2008. "General uncertainty in portfolio selection: A case-based decision approach," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 718-734, September.
    11. Shaofei Jiang, 2024. "Costly Persuasion by a Partially Informed Sender," Papers 2401.14087, arXiv.org, revised Nov 2024.
    12. Koessler, Frederic & Laclau, Marie & Renault, Jérôme & Tomala, Tristan, 2022. "Long information design," Theoretical Economics, Econometric Society, vol. 17(2), May.
    13. Dirk Bergemann & Stephen Morris, 2019. "Information Design: A Unified Perspective," Journal of Economic Literature, American Economic Association, vol. 57(1), pages 44-95, March.
    14. Itzhak Gilboa & Offer Lieberman & David Schmeidler, 2012. "On the Definition of Objective Probabilities by Empirical Similarity," World Scientific Book Chapters, in: Case-Based Predictions An Axiomatic Approach to Prediction, Classification and Statistical Learning, chapter 11, pages 259-280, World Scientific Publishing Co. Pte. Ltd..
    15. Vladimir Asriyan & Dana Foarta & Victoria Vanasco, 2023. "The Good, the Bad, and the Complex: Product Design with Imperfect Information," American Economic Journal: Microeconomics, American Economic Association, vol. 15(2), pages 187-226, May.
    16. Tommaso Denti & Doron Ravid, 2023. "Robust Predictions in Games with Rational Inattention," Papers 2306.09964, arXiv.org.
    17. Sendhil Mullainathan & Joshua Schwartzstein & Andrei Shleifer, 2008. "Coarse Thinking and Persuasion," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(2), pages 577-619.
    18. Maxim Senkov & Toygar T. Kerman, 2024. "Changing Simplistic Worldviews," Papers 2401.02867, arXiv.org.
    19. Gayer, Gabrielle, 2010. "Perception of probabilities in situations of risk: A case based approach," Games and Economic Behavior, Elsevier, vol. 68(1), pages 130-143, January.
    20. Shih-Tang Su & Vijay G. Subramanian & Grant Schoenebeck, 2021. "Bayesian Persuasion in Sequential Trials," Papers 2110.09594, arXiv.org, revised Nov 2021.

    More about this item

    Keywords

    Persuasion;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    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:cpr:ceprdp:18428. 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://www.cepr.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.