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Optimal Rating Design under Moral Hazard

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  • Maryam Saeedi
  • Ali Shourideh

Abstract

We examine the design of optimal rating systems in the presence of moral hazard. First, an intermediary commits to a rating scheme. Then, a decision-maker chooses an action that generates value for the buyer. The intermediary then observes a noisy signal of the decision-maker's choice and sends the buyer a signal consistent with the rating scheme. Here we fully characterize the set of allocations that can arise in equilibrium under any arbitrary rating system. We use this characterization to study various design aspects of optimal rating systems. Specifically, we study the properties of optimal ratings when the decision-maker's effort is productive and when the decision-maker can manipulate the intermediary's signal with a noise. With manipulation, rating uncertainty is a fairly robust feature of optimal rating systems.

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  • Maryam Saeedi & Ali Shourideh, 2020. "Optimal Rating Design under Moral Hazard," Papers 2008.09529, arXiv.org, revised Jul 2023.
    • Handle: RePEc:arx:papers:2008.09529
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    References listed on IDEAS

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    Cited by:

    1. Jacopo Bizzotto & Alessandro De Chiara, 2022. "Frequent audits and honest audits," Working Papers 202202, Oslo Metropolitan University, Oslo Business School.
    2. Jacopo Bizzotto & Adrien Vigier, 2022. "A Case for Tiered School Systems," Working Papers 202205, Oslo Metropolitan University, Oslo Business School.
    3. Onuchic, Paula & Ray, Debraj, 2023. "Conveying value via categories," Theoretical Economics, Econometric Society, vol. 18(4), November.
    4. Tan, Teck Yong, 2023. "Optimal transparency of monitoring capability," Journal of Economic Theory, Elsevier, vol. 209(C).
    5. Andreas Kleiner & Benny Moldovanu & Philipp Strack, 2021. "Extreme Points and Majorization: Economic Applications," Econometrica, Econometric Society, vol. 89(4), pages 1557-1593, July.
    6. Jacopo Bizzotto & Adrien Vigier, 2022. "Sorting and Grading," Papers 2208.10894, arXiv.org, revised Feb 2024.
    7. Yasui, Yuta, 2021. "Controlling Fake Reviews," MPRA Paper 108177, University Library of Munich, Germany.

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