Identifying and Analyzing Extremes: Illustrated by CEOs’ Pay and Performance
提出统计方法识别样本中的极端值并分析两个变量极端值之间的关联，以50位薪酬最高的CEO为例，发现薪酬与绩效的极端值之间存在负相关，而非极端值之间无关联。
This article presents statistical methods for identifying outcomes in a given sample that can be inferred as plausible extreme and whether the extremes on two variables are associated. Applications to CEO pay and performance of 50 top-paid CEOs illustrate these methodologies. Thresholds between extremes and nonextremes are found using high probability intervals under the probability distributions that govern sampling variations of the sample extremes. A Bayesian approach is used to compute odds on the association between the extremes of the two variables. The extreme pay—performance analysis of 50 top-paid CEOs reveals astonishing odds in favor of a company being extreme high only on one of the two versus on both variables. The result is considered decisive evidence for a negative association between extreme on CEO pay and extreme on performance among such top-paid CEOs. By contrast, analysis of the nonextreme CEOs yielded no evidence of any association between CEO pay and performance.