Open AccessPerformance‐maximizing large contests
Author(s) -
Olszewski Wojciech,
Siegel Ron
Publication year - 2020
Publication title -
theoretical economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.404
H-Index - 32
eISSN - 1555-7561
pISSN - 1933-6837
DOI - 10.3982/te3588
Subject(s) - contest , ranking (information retrieval) , computer science , ex ante , microeconomics , mathematical economics , economics , regular polygon , operations research , mathematical optimization , econometrics , mathematics , artificial intelligence , geometry , political science , law , macroeconomics
Many sales, sports, and research contests are put in place to maximize contestants' performance. We investigate and provide a complete characterization of the prize structures that achieve this objective in settings with many contestants. The contestants may be ex ante asymmetric in their abilities and prize valuations, and there may be complete or incomplete information about these parameters. The prize valuations and performance costs may be linear, concave, or convex. A main novel takeaway is that awarding numerous different prizes whose values gradually decline with contestants' ranking is optimal in the typical case of contestants with convex performance costs and concave prize valuations. This suggests that many real‐world contests can be improved by increasing the number of prizes and making them more heterogeneous. The techniques we develop can also be used to formulate and solve other contest design questions that have so far proven intractable.