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Improving Information from Manipulable Data

Author

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  • Alex Frankel
  • Navin Kartik

Abstract

Data-based decision making must account for the manipulation of data by agents who are aware of how decisions are being made and want to affect their allocations. We study a framework in which, due to such manipulation, data become less informative when decisions depend more strongly on data. We formalize why and how a decision maker should commit to underutilizing data. Doing so attenuates information loss and thereby improves allocation accuracy.

Suggested Citation

  • Alex Frankel & Navin Kartik, 2022. "Improving Information from Manipulable Data," Journal of the European Economic Association, European Economic Association, vol. 20(1), pages 79-115.
    • Handle: RePEc:oup:jeurec:v:20:y:2022:i:1:p:79-115.
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    File URL: http://hdl.handle.net/10.1093/jeea/jvab017
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    Cited by:

    1. Tsakas, Elias & Tsakas, Nikolas, 2021. "Noisy persuasion," Games and Economic Behavior, Elsevier, vol. 130(C), pages 44-61.
    2. Christopher A. Hennessy & Charles A. E. Goodhart, 2023. "Goodhart'S Law And Machine Learning: A Structural Perspective," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 1075-1086, August.
    3. Tan, Teck Yong, 2023. "Optimal transparency of monitoring capability," Journal of Economic Theory, Elsevier, vol. 209(C).
    4. John W. Patty & Elizabeth Maggie Penn, 2022. "Algorithmic Fairness and Statistical Discrimination," Papers 2208.08341, arXiv.org.
    5. Christa Gibbs & Benedict Guttman-Kenney & Donghoon Lee & Scott Nelson & Wilbert van der Klaauw & Jialan Wang, 2025. "Consumer Credit Reporting Data," Journal of Economic Literature, American Economic Association, vol. 63(2), pages 598-636, June.
    6. John W. Patty & Elizabeth Maggie Penn, 2023. "Algorithmic Fairness with Feedback," Papers 2312.03155, arXiv.org.
    7. Jordan Adamson & Lucas Rentschler, 2023. "Criminal justice from a public choice perspective: an introduction to the special issue," Public Choice, Springer, vol. 196(3), pages 223-227, September.
    8. Silvia Martinez-Gorricho & Carlos Oyarzun, 2024. "Testing under information manipulation," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 77(3), pages 849-890, May.
    9. Eduardo Perez‐Richet & Vasiliki Skreta, 2022. "Test Design Under Falsification," Econometrica, Econometric Society, vol. 90(3), pages 1109-1142, May.
    10. Jeanne Hagenbach & Aurélien Salas, 2025. "Strategic Information Disclosure to Classification Algorithms: An Experiment," Post-Print hal-05464751, HAL.
    11. Jiadong Gu, 2024. "Data Trade and Consumer Privacy," Papers 2406.12457, arXiv.org, revised Jan 2026.
    12. Lichtig, Avi & Weksler, Ran, 2023. "Information transmission in voluntary disclosure games," Journal of Economic Theory, Elsevier, vol. 210(C).

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