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Identifying and Analyzing Extremes: Illustrated by CEOs’ Pay and Performance

^* To whom correspondence should be addressed. E-mail: nystrom{at}uwm.edu.

	Abstract

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.

First published on August 19, 2009, doi:10.1177/1094428109342899
A more recent version of this article appeared on November 9, 2009


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