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Robustly Non-Harmful Information for Biased Learners

Author

Listed:
  • Malte Kornemann

    (University of Bonn)

Abstract

I examine when robustly beneficial information can be provided to a receiver who also learns from misspecified background sources that are outside the provider’s control. In contrast to information provision for rational receivers, any source can be harmful under certain misspecifications of background sources. I show that the key aspect of the background environment enabling robustly beneficial design is the receiver’s perception rather than the true structure. For any background source structure and design of the provided source, there exists a misspecification under which harm occurs. Consequently, even complete knowledge of the true structure is insufficient and knowledge of the receiver’s perception is necessary. Under complete knowledge of the perception, I demonstrate how to design an information source that is robustly non-harmful and often strictly beneficial, regardless of the true background sources.

Suggested Citation

  • Malte Kornemann, 2026. "Robustly Non-Harmful Information for Biased Learners," ECONtribute Discussion Papers Series 411, University of Bonn and University of Cologne, Germany.
  • Handle: RePEc:ajk:ajkdps:411
    as

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    File URL: https://www.econtribute.de/RePEc/ajk/ajkdps/ECONtribute_411_2026.pdf
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    References listed on IDEAS

    as
    1. Ignacio Esponda & Demian Pouzo, 2016. "Berk–Nash Equilibrium: A Framework for Modeling Agents With Misspecified Models," Econometrica, Econometric Society, vol. 84, pages 1093-1130, May.
    2. He, Kevin, 2022. "Mislearning from censored data: The gambler's fallacy and other correlational mistakes in optimal-stopping problems," Theoretical Economics, Econometric Society, vol. 17(3), July.
    3. Esponda, Ignacio & Pouzo, Demian & Yamamoto, Yuichi, 2021. "Asymptotic behavior of Bayesian learners with misspecified models," Journal of Economic Theory, Elsevier, vol. 195(C).
    4. Hyun Song Shin & Stephen Morris, 1997. "The rationality and efficacy of decisions under uncertainty and the value of an experiment (*)," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 9(2), pages 309-324.
    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General

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