Abstract
Collider bias can cause spurious correlations when researchers condition on a variable that is caused by—or shares a common cause with—both the outcome and the exposure variable. Despite its threat to inference, empirical research in strategy and management has largely overlooked the issue of collider bias. We distinguish colliders from other threats to identification and estimation and illustrate its importance with replications of published work suggesting that having a woman CEO reduces the career outcomes (compensation and representation) of other women executives. After accounting for collider bias, we find no evidence that women CEOs damage the career outcomes of other women in their organizations. We close by providing generalizable approaches to identify and mitigate the risk of collider bias in applied research. Collider bias is a type of statistical problem that can generate misleading results in empirical research. Although research in strategy and management has given substantial attention to other types of statistical problems, the issue of collider bias has not received sufficient scrutiny. We illustrate this point with replications of published work suggesting that having a woman CEO reduces the career outcomes of other women executives. After accounting for collider bias, we find no evidence that women CEOs damage the career outcomes of other women in their organizations. We provide advice for detecting and addressing collider bias in empirical research.Research Summary
Managerial Summary
