IDEAS home Printed from https://ideas.repec.org/p/ajk/ajkdps/245.html
   My bibliography  Save this paper

Persuasion with Limited Data: A Case-Based Approach

Author

Listed:
  • Shiri Alon

    (Department of Economics, Bar-Ilan University)

  • Sarah Auster

    (Department of Economics, University of Bonn)

  • Gabi Gayer

    (Department of Economics, Bar-Ilan University)

  • Stefania Minardi

    (Department of Economics and Decision Sciences, HEC Paris)

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

  • Shiri Alon & Sarah Auster & Gabi Gayer & Stefania Minardi, 2023. "Persuasion with Limited Data: A Case-Based Approach," ECONtribute Discussion Papers Series 245, University of Bonn and University of Cologne, Germany.
    • Handle: RePEc:ajk:ajkdps:245
    as

    Download full text from publisher

    File URL: https://www.econtribute.de/RePEc/ajk/ajkdps/ECONtribute_245_2023.pdf
    File Function: Second version, 2024
    Download Restriction: no
    ---><---

    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. Simone Galperti, 2019. "Persuasion: The Art of Changing Worldviews," American Economic Review, American Economic Association, vol. 109(3), pages 996-1031, March.
    4. 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.
    5. 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.
    6. 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.
    7. Le Treust, Maël & Tomala, Tristan, 2019. "Persuasion with limited communication capacity," Journal of Economic Theory, Elsevier, vol. 184(C).
    8. Beauchêne, Dorian & Li, Jian & Li, Ming, 2019. "Ambiguous persuasion," Journal of Economic Theory, Elsevier, vol. 179(C), pages 312-365.
    9. 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.
    10. Eduardo Perez-Richet, 2014. "Interim Bayesian Persuasion: First Steps," American Economic Review, American Economic Association, vol. 104(5), pages 469-474, May.
    11. 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..
    12. Patil, Sanket & Salant, Yuval, 2024. "Optimal sample sizes and statistical decision rules," Theoretical Economics, Econometric Society, vol. 19(2), May.
    13. Kosterina, Svetlana, 2022. "Persuasion with unknown beliefs," Theoretical Economics, Econometric Society, vol. 17(3), July.
    14. Isabelle Brocas & Juan D. Carrillo, 2007. "Influence through ignorance," RAND Journal of Economics, RAND Corporation, vol. 38(4), pages 931-947, December.
    15. Blonski, Matthias, 1999. "Social learning with case-based decisions," Journal of Economic Behavior & Organization, Elsevier, vol. 38(1), pages 59-77, January.
    16. Matthew Gentzkow & Emir Kamenica, 2017. "Competition in Persuasion," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(1), pages 300-322.
    17. Pavan, Alessandro & Dworczak, Piotr, 2020. "Preparing for the Worst But Hoping for the Best: Robust (Bayesian) Persuasion," CEPR Discussion Papers 15017, C.E.P.R. Discussion Papers.
    18. Xiaoyu Cheng, 2020. "Ambiguous Persuasion: An Ex-Ante Formulation," Papers 2010.05376, arXiv.org, revised Nov 2023.
    19. 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. Wu, Wenhao, 2023. "Sequential Bayesian persuasion," Journal of Economic Theory, Elsevier, vol. 214(C).
    3. 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.
    4. Koessler, Frederic & Laclau, Marie & Renault, Jérôme & Tomala, Tristan, 2022. "Long information design," Theoretical Economics, Econometric Society, vol. 17(2), May.
    5. Frédéric Koessler & Marie Laclau & Jerôme Renault & Tristan Tomala, 2022. "Long information design," Post-Print hal-03700394, HAL.
    6. Frédéric Koessler & Marie Laclau & Jerôme Renault & Tristan Tomala, 2022. "Long information design," PSE-Ecole d'économie de Paris (Postprint) hal-03700394, HAL.
    7. Xiaoyu Cheng, 2020. "Ambiguous Persuasion: An Ex-Ante Formulation," Papers 2010.05376, arXiv.org, revised Nov 2023.
    8. Tommaso Denti & Doron Ravid, 2023. "Robust Predictions in Games with Rational Inattention," Papers 2306.09964, arXiv.org.
    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. Alexei Parakhonyak & Anton Sobolev, 2022. "Persuasion without Priors," Economics Series Working Papers 977, University of Oxford, Department of Economics.
    11. Krishnamurthy Iyer & Haifeng Xu & You Zu, 2023. "Markov Persuasion Processes with Endogenous Agent Beliefs," Papers 2307.03181, arXiv.org, revised Jul 2023.
    12. 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.
    13. Tsakas, Elias & Tsakas, Nikolas, 2021. "Noisy persuasion," Games and Economic Behavior, Elsevier, vol. 130(C), pages 44-61.
    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. Eitan Sapiro-Gheiler, 2021. "Persuasion with Ambiguous Receiver Preferences," Papers 2109.11536, arXiv.org, revised Aug 2023.
    16. Semyon Malamud & Andreas Schrimpf, 2021. "Persuasion by Dimension Reduction," Swiss Finance Institute Research Paper Series 21-69, Swiss Finance Institute.
    17. Shaofei Jiang, 2024. "Costly Persuasion by a Partially Informed Sender," Papers 2401.14087, arXiv.org, revised Feb 2024.
    18. Babichenko, Yakov & Talgam-Cohen, Inbal & Xu, Haifeng & Zabarnyi, Konstantin, 2022. "Regret-minimizing Bayesian persuasion," Games and Economic Behavior, Elsevier, vol. 136(C), pages 226-248.
    19. Todd Guilfoos & Andreas Duus Pape, 2020. "Estimating Case-Based Learning," Games, MDPI, vol. 11(3), pages 1-25, September.
    20. Dirk Bergemann & Stephen Morris, 2019. "Information Design: A Unified Perspective," Journal of Economic Literature, American Economic Association, vol. 57(1), pages 44-95, March.

    More about this item

    Keywords

    Persuasion; case-based inference; similarity-weighted frequencies;
    All these keywords.

    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

    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:ajk:ajkdps:245. 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: ECONtribute Office (email available below). General contact details of provider: https://www.econtribute.de .

    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.