QCA Should Set Aside the Algorithms

Abstract

Qualitative comparative analysis (QCA) has received substantial attention from qualitative scholars seeking to systematize their research. This method has valuable goals: understanding context, interactions, and causal complexity, including asymmetric causation. These objectives 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 its goals. What began as a refreshingly simple method has, counterproductively, become much more complicated. 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 objectives that motivated Charles Ragin to create QCA, unencumbered by algorithms that may well be obstacles to achieving these goals.