Qualitative Comparative Analysis (QCA)

QCA is a comparative case-study method. It uses Boolean algebra and formal logic to identify cross-case regularities. These regularities are substantively interpreted into causal mechanisms on the basis of case-based, contextual and theoretical knowledge. That is, contrary to statistical, variable-based methods empirically observed regularities in QCA do not evidence causality. They are merely indicative of underlying causal mechanisms that need to be interpreted by ‘going back to the cases’. This makes QCA essentially a critical realist method because it distinguished between epistemological knowledge (empirically observed regularities) and ontological knowledge (causal mechanisms).

Causal mechanism in QCA further connect to critical realism because they are emergent, not generative. The presence of conditions makes is possible for agents (the case) to achieve the outcome but does not determine that it will. That is, uncertainty in QCA is possibilistic rather than probabilistic. The uncertainty concerns whether putative causes actually make it possible for the outcome to occur. My methodological work on QCA focuses on: i) Explaining how crisp-set QCA and fuzzy-set QCA follow different logics of causality and why crisp-set QCA connects much better to the critical realist, possibilistic understanding of causality, and ii) Developing robustness tests for large-N QCA studies that force researchers to look beyond their empirically observed regularities and to engage with case-based and substantive knowledge to interpret to regularities into causal mechanisms.