研究传统预测竞赛中选手为何会撒谎，发现长期未必诚实
Hedging and Approximate Truthfulness in Traditional Forecasting Competitions
- 分析传统评分机制下选手的激励问题，发现即使事件很多也可能故意保守预测
- 当双方对彼此水平和结果不确定时，预测接近真实
- 适用于评估真实竞赛中的策略行为，对设计公平机制有启发
在预测竞赛中，传统机制根据每位参赛者对每个事件的预测与实际结果对比打分，总分最高者获胜。尽管已有文献指出该机制存在激励缺陷，但学界普遍认为随着事件数量增加，参赛者将趋于诚实。然而，此前缺乏对此机制的正式分析。本文首次进行系统分析，证明所谓“长期诚实”是错误的：即便事件数量任意多，最优预测者仍可能通过适度调整预测来提高胜率。但另一方面，当双方对对手实力及事件结果均存在足够不确定性时，两人预测将趋于近似真实。这一情形在实践中可能真实存在。
原文摘要 · Abstract (English)
In forecasting competitions, the traditional mechanism scores the predictions of each contestant against the outcome of each event, and the contestant with the highest total score wins. While it is well-known that this traditional mechanism can suffer from incentive issues, it is folklore that contestants will still be roughly truthful as the number of events grows. Yet thus far the literature lacks a formal analysis of this traditional mechanism. This paper gives the first such analysis. We first demonstrate that the ''long-run truthfulness'' folklore is false: even for arbitrary numbers of events, the best forecaster can have an incentive to hedge, reporting more moderate beliefs to increase their win probability. On the positive side, however, we show that two contestants will be approximately truthful when they have sufficient uncertainty over the relative quality of their opponent and the outcomes of the events, a case which may arise in practice.
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