Introduction: Causation, inferences, and solution types in configurational comparative methods

Abstract

This special issue addresses questions of causality and validity of different solution types in configurational comparative methods (CCMs). First, what main parameters characterize the debate about correct causal interpretation of solution types? Second, to what extent has this debate been linked to a theory of causation? The special issue contribution by Mahoney and Acosta bases qualitative comparative analysis (QCA) within a regularity theory of causation integrating type-level inferences and counterfactual cases. Swiatczak clarifies how the different algorithms underlying QCA and Coincidence Analysis (CNA) produce non-identical models. Baumgartner defines and benchmarks QCA solution types against the search target of minimal robust sufficiency. Alamos-Concha et al. identify the conservative solution as most appropriate for a multimethod design combining a counterfactual causal understanding at the cross-case level with an in-depth mechanistic explanation at the within-case level. Finally, Mahoney and Owen develop a general set-theoretic framework for the study of necessity and sufficiency in quantitative research using a counterfactual understanding of causality. Our introduction reviews the state of the art, identifies current limitations and open questions regarding the theoretical basis for causal interpretation of QCA solutions.