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


  • Markus A. Fitza

    Corresponding author
    1. Department of Management, Mays Business School, Texas A&M University, College Station, Texas, U.S.A.
    2. Faculty of Business and Law, The University of Newcastle, Callaghan, New South Wales, Australia
    • Correspondence to: Markus A. Fitza, Texas A&M University, Mays Business School, Department of Management, 420 Wehner Building, College Station, Texas 77843-4221, U.S.A. E-mail:

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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.