Micro foundations of multi-prize lottery contests: A perspective of noisy performance ranking

Abstract

This article proposes a multi-prize noisy-ranking contest model. Contestants are ranked in descending order based on their perceived performance, which is subject to random perturbation, and they are rewarded based on their ranks. Under plausible conditions, we establish that our noisy performance ranking model is stochastically equivalent to the family of multi-prize lottery contests built upon ratio-form contest success functions. We further establish the equivalence of our model to a contest model that ranks contestants by their best performance out of multiple independent attempts. These results therefore shed light on the micro-foundations of the popularly adopted lottery contest models. The "best-shot ranking rule" reveals a common thread that connects a broad class of seemingly disparate competitive activities (such as rent-seeking contests, patent races, research tournaments), and unifies them through a common performance evaluation mechanism. © 2011 Springer-Verlag.