We study the design of grading contests between agents with private information about their abilities under the assumption that the value of a grade is determined by the information it reveals about the agent's productivity. Towards the goal of identifying the effort-maximizing grading contest, we study the effect of increasing prizes and increasing competition on effort and find that the effects depend qualitatively on the distribution of abilities in the population. Consequently, while the optimal grading contest always uniquely identifies the best performing agent, it may want to pool or separate the remaining agents depending upon the distribution. We identify sufficient conditions under which a rank-revealing grading contest, a leaderboard-with-cutoff type grading contest, and a coarse grading contest with at most three grades are optimal. In the process, we also identify distributions under which there is a monotonic relationship between the informativeness of a grading scheme and the effort induced by it.

翻译：本文研究了在假设等级价值由其揭示的个体生产力信息决定的前提下，具有私人能力信息的代理人之间的分级竞赛设计问题。为识别出最大化努力水平的分级竞赛，我们分析了提高奖励和增强竞争对努力的影响，发现这种影响在性质上取决于人口中能力的分布。因此，尽管最优分级竞赛始终能唯一确定表现最佳的代理人，但根据分布情况，它可能倾向于对剩余代理人进行合并或分离。我们识别了以下情况的充分条件：当排名揭示型分级竞赛、具有截止线的排行榜型分级竞赛以及最多三个等级的粗粒度分级竞赛达到最优时。在此过程中，我们还识别了某些分布，在这些分布下，分级方案的信息量与由此激发的努力之间存在单调关系。