Comment

Qualitative comparative analysis (QCA) has received substantial attention from qualitative scholars seeking to systematize their research. QCA has valuable methodological goals: understanding context, interactions, and causal complexity, including asymmetric causation. These goals are pursued with central attention to case knowledge. However, simulations suggest that QCA’s core analytic procedures— its algorithms—provide a weak foundation for pursuing these goals. What began as a refreshingly simple method has, counterproductively, become much more complicated. In this brief comment, I argue that QCA scholars should turn their attention to more traditional qualitative tools: case studies and process tracing. With such tools, they can pursue the important methodological goals that motivated Charles Ragin to create QCA, unencumbered by algorithms that may well be obstacles to achieving these goals. A key introductory point: These misgivings about QCA do not derive from the perspective of quantitative methodology. Conventional quantitative work has been sharply criticized from this same perspective, as have key features of experimental research.