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Selecting the Best when Selection is Hard

Author

Listed:
  • Drugov, Mikhail
  • Meyer, Margaret
  • Möller, Marc
Abstract
In dynamic promotion contests, where performance measurement is noisy and constrained to be ordinal, selection of the most able agent can be improved by biasing later stages in favor of early performers. We show that even in the worst-case scenario, where external random factors swamp the difference in agents' abilities in determining their relative performance, optimal bias is (i) strictly positive and (ii) locally insensitive to changes in the ratio of heterogeneity to noise. To explain these, arguably surprising, limiting results, we demonstrate a close relationship in the limit between optimal bias under ordinal information and the expected optimal bias when bias can be conditioned on cardinal information about relative performance. As a consequence of these two limiting properties, the simple rule of setting bias as if in the worst-case scenario achieves most of the potential gains in selective efficiency from biasing dynamic rank-order contests.

Suggested Citation

  • Drugov, Mikhail & Meyer, Margaret & Möller, Marc, 2022. "Selecting the Best when Selection is Hard," CEPR Discussion Papers 17484, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:17484
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    References listed on IDEAS

    as
    1. Margaret A. Meyer, 1991. "Learning from Coarse Information: Biased Contests and Career Profiles," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(1), pages 15-41.
    2. Andrew Schotter & Keith Weigelt, 1992. "Asymmetric Tournaments, Equal Opportunity Laws, and Affirmative Action: Some Experimental Results," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(2), pages 511-539.
    3. James Fain, 2009. "Affirmative Action Can Increase Effort," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 30(2), pages 168-175, June.
    4. repec:adr:anecst:y:1992:i:25-26:p:08 is not listed on IDEAS
    5. Drugov, Mikhail & Ryvkin, Dmitry, 2017. "Biased contests for symmetric players," Games and Economic Behavior, Elsevier, vol. 103(C), pages 116-144.
    6. Margaret A. Meyer, 1992. "Biased Contests and Moral Hazard: Implications for Career Profiles," Annals of Economics and Statistics, GENES, issue 25-26, pages 165-187.
    7. Jörg Franke & Christian Kanzow & Wolfgang Leininger & Alexandra Schwartz, 2013. "Effort maximization in asymmetric contest games with heterogeneous contestants," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 52(2), pages 589-630, March.
    8. Kawamura, Kohei & Moreno de Barreda, Inés, 2014. "Biasing selection contests with ex-ante identical agents," Economics Letters, Elsevier, vol. 123(2), pages 240-243.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Penghuan Yan, 2024. "Balancing Selection Efficiency and Societal Costs in Selective Contests," Papers 2409.09768, arXiv.org, revised Oct 2024.

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    More about this item

    Keywords

    Dynamic contests; Selective efficiency; Bias; Learning; Promotions;
    All these keywords.

    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • M51 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Firm Employment Decisions; Promotions

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