This paper reviews the empirical methods used in the accounting literature to draw causal inferences. Similar to other social science disciplines, recent years have seen a burgeoning growth in the use of methods that seek to provide as-if random variation in observational settings — i.e., “quasi-experiments.” We provide a synthesis of the major assumptions of these methods, discuss several practical considerations for such methods, and provide a framework for thinking about whether and when quasi-experimental and non-experimental methods are well-suited for drawing causal inferences. We caution against the idea that one should restrict attention to only those causal questions for which there are quasi-experiments. We encourage researchers seeking to answer causal questions to triangulate inferences across multiple methods, research designs, and settings.