Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/266509 
Year of Publication: 
2022
Series/Report no.: 
Discussion Papers No. 22-04
Publisher: 
University of Bern, Department of Economics, Bern
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.
Subjects: 
Dynamic Contests
Selective Efficiency
Bias
Learning
Promotions
JEL: 
D21
D82
D83
M51
Creative Commons License: 
cc-by Logo
Document Type: 
Working Paper

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