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Scoring Strategic Agents

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  • Ian Ball

Abstract

I introduce a model of predictive scoring. A receiver wants to predict a sender's quality. An intermediary observes multiple features of the sender and aggregates them into a score. Based on the score, the receiver makes a decision. The sender prefers "higher" decisions, and she can distort each feature at a privately known cost. I characterize the scoring rule that maximizes decision accuracy. This rule underweights some features to deter sender distortion, and overweights other features so that the score is correct on average. The receiver prefers this scoring rule to full disclosure because it mitigates his commitment problem.

Suggested Citation

  • Ian Ball, 2019. "Scoring Strategic Agents," Papers 1909.01888, arXiv.org, revised May 2024.
    • Handle: RePEc:arx:papers:1909.01888
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    References listed on IDEAS

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    Cited by:

    1. Dessein, Wouter & Frankel, Alexander & Kartik, Navin, 2023. "Test-Optional Admissions," CEPR Discussion Papers 18090, C.E.P.R. Discussion Papers.
    2. Frances Xu Lee & Wing Suen, 2023. "Gaming A Selective Admissions System," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(1), pages 413-443, February.
    3. Yingkai Li & Boli Xu, 2024. "Falsifiable Test Design in Coordination Games," Papers 2405.18521, arXiv.org.
    4. Christa N. Gibbs & Benedict Guttman-Kenney & Donghoon Lee & Scott T. Nelson & Wilbert H. van der Klaauw & Jialan Wang, 2024. "Consumer Credit Reporting Data," NBER Working Papers 32791, National Bureau of Economic Research, Inc.
    5. 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.
    6. Yasui, Yuta, 2021. "Controlling Fake Reviews," MPRA Paper 108177, University Library of Munich, Germany.

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