Optimal grading contests

TL;DR

This paper analyzes how different grading schemes influence effort levels in contests, showing that informativeness and prize manipulation can either motivate or demotivate effort depending on ability distributions.

Contribution

It introduces a model linking grading scheme informativeness and effort, providing conditions under which these schemes incentivize effort based on ability distributions.

Findings

More informative grading schemes can increase effort among moderate-ability agents.

Manipulating prizes affects effort depending on ability distribution and cost functions.

Effort incentives vary with the likelihood of moderate-ability agents.

Abstract

We study the design of effort-maximizing grading schemes between agents with private abilities. Assuming agents derive value from the information their grade reveals about their ability, we find that more informative grading schemes induce more competitive contests. In the contest framework, we investigate the effect of manipulating individual prizes and increasing competition on expected effort, identifying conditions on ability distributions and cost functions under which these transformations may encourage or discourage effort. Our results suggest that more informative grading schemes encourage effort when agents of moderate ability are highly likely, and discourage effort when such agents are unlikely.