Selecting the Best when Selection is Hard

Mikhail Drugov, Margaret Meyer and Marc Moeller ()
Additional contact information
Marc Moeller: University of Bern
Authors registered in the RePEc Author Service: Marc Möller ()

No w0290, Working Papers from New Economic School (NES)

Abstract: In dynamic promotion contests, where performance measurement is noisy and ordinal, selection can be improved by biasing later stages in favor of early leaders. Even in the worst-case scenario, where noise swamps ability differences in determining relative performance, optimal bias is i) strictly positive; ii) locally insensitive to changes in the heterogeneity-to-noise ratio. A close relationship with expected optimal bias under cardinal information helps explain this surprising result. Properties i) and ii) imply that 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.

Keywords: Dynamic Contests; Selective Efficiency; Bias; Learning; Promotions JEL Classifications: D21, D82, D83, M51 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2022-08
New Economics Papers: this item is included in nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nes.ru/files/Preprints-resh/WP290.pdf (application/pdf)

Related works:
Working Paper: Selecting the Best when Selection is Hard (2022)
Working Paper: Selecting the best when selection is hard (2022)
Working Paper: Selecting the Best when Selection is Hard (2022)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:abo:neswpt:w0290

Access Statistics for this paper

More papers in Working Papers from New Economic School (NES) Contact information at EDIRC.
Bibliographic data for series maintained by Vladimir Ivanyukhin ( this e-mail address is bad, please contact ).