The use of variance decomposition in the investigation of CEO effects: How large must the CEO effect be to rule out chance?

Abstract

Variance decomposition analysis is often used to examine the degree to which CEOs influence their companies' performance (the so-called CEO effect). Such studies play an important role in a body of literature that investigates the effect of leadership on organizations. In this paper, I argue that these previous studies have an important underlying flaw. Empirically, these studies wrongly attribute the performance effect of randomness—of chance—to the CEO. I demonstrate how randomness can affect the measured effects in a variance decomposition analysis, and I show that this is especially problematic for the measurement of CEO effects. I demonstrate how this results in a greatly inflated CEO effect and develop an approach to correct for it. Copyright © 2013 John Wiley & Sons, Ltd.