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Motivational Ratings

Author

Listed:
  • Johannes Hörner

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CNRS - Centre National de la Recherche Scientifique)

  • Nicolas Lambert
Abstract
Performance evaluation (\rating") systems not only provide information to users but also motivate the rated worker. This paper solves for the optimal(effort-maximizing) rating within the standard career concerns framework. We prove that this rating is a linear function of past observations. The rating, however, is not a Markov process, but rather the sum of two Markov processes. We show how it combines information of different types and vintages. An increase in effort may adversely affect some (but not all) future ratings.

Suggested Citation

  • Johannes Hörner & Nicolas Lambert, 2021. "Motivational Ratings," Working Papers hal-03187510, HAL.
    • Handle: RePEc:hal:wpaper:hal-03187510
    Note: View the original document on HAL open archive server: https://hal.science/hal-03187510
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    References listed on IDEAS

    as
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    Cited by:

    1. Dirk Bergemann & Marco Ottaviani, 2021. "Information Markets and Nonmarkets," Cowles Foundation Discussion Papers 2296, Cowles Foundation for Research in Economics, Yale University.
    2. Hakenes, Hendrik & Katolnik, Svetlana, 2017. "On the incentive effects of job rotation," European Economic Review, Elsevier, vol. 98(C), pages 424-441.
    3. Kaya, Ayça & Roy, Santanu, 2022. "Market screening with limited records," Games and Economic Behavior, Elsevier, vol. 132(C), pages 106-132.
    4. Sergey Kovbasyuk & Giancarlo Spagnolo, 2024. "Memory and Markets," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(3), pages 1775-1806.
    5. Tan, Teck Yong, 2023. "Optimal transparency of monitoring capability," Journal of Economic Theory, Elsevier, vol. 209(C).
    6. Yasui, Yuta, 2021. "Controlling Fake Reviews," MPRA Paper 108177, University Library of Munich, Germany.

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    More about this item

    Keywords

    Career Concerns; Mechanism Design; Ratings.;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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