QCA, 25 Years after "The Comparative Method": Mapping, Challenges, and Innovations-Mini-Symposium

This paper introduces the mini-symposium on Qualitative Comparative Analysis (QCA) and set-theoretic methods, both crisp sets and fuzzy sets, and situates the different contributions in a wider methodological debate concerning cross-case analysis. The paper argues that QCA is not just a set of techniques, but a distinctive research approach, with its own goals and set of assumptions. Concerning the wide methodological debate, special attention is paid to the added value of QCA and specific innovations introduced in the mini-symposium. This essay contrasts the conventional template for conducting social inquiry and the alternate template provided by configurational, case-oriented analytic methods, first formalized in The Comparative Method. The essential contrasts address the fundamental building blocks of social research, ranging from the definition of relevant cases to the understanding of social causation. The alternate template described in this essay provides a much stronger basis for the articulation of within-case and cross-case analysis than is offered by the conventional template. This article provides a first systematic mapping of QCA applications, building upon a database of 313 peer-reviewed journal articles. We find out that the number of QCA applications has dramatically increased during the past few years. The mapping also reveals that csQCA remains the most frequently used technique, that political science, sociology, and management are the core disciplines of application, that macrolevel analyses, medium-N designs, and a mono-method use of QCA remain predominant. A particular focus is also laid on the ratio between the number of cases and number of conditions and the compliance to benchmarks in this respect. QCA's ability of addressing complex theoretical expectations and taking account of configurational relationships is rarely fully exploited. Assessing comparative welfare-state research, which has employed QCA, we find that only about half of the studies reviewed have expressed complex theoretical propositions in set-theoretical terms, revisited cases subsequent to the formal analysis, or subjected findings to robustness checks. We discuss the relevance of each of these three aspects and argue that carefully considering these will improve the quality of QCA applications. Contrasting insights that can be gained from large-N QCA and econometric analysis, we outline two novel ways to integrate both modes of inquiry. The first introduces QCA solutions into a regression model, while the second draws on recent work in lattice theory to integrate a QCA approach with a regression framework. These approaches allow researchers to test QCA solutions for robustness, address concerns regarding possible omitted variables, establish effect sizes, and test whether causal conditions are complements or substitutes, suggesting that an important way forward for set-theoretic analysis lies in an increased dialogue that explores complementarities with existing econometric approaches. This paper discusses five strategies to deal with five types of errors in Qualitative Comparative Analysis (QCA): condition errors, systematic errors, random errors, calibration errors, and deviant case errors. These strategies are the comparative inspection of complex, intermediary, and parsimonious solutions; the use of an adjustment factor, the use of probabilistic criteria, the test of the robustness of calibration parameters, and the use of a frequency threshold for observed combinations of conditions. The strategies are systematically reviewed, assessed, and evaluated as regards their applicability, advantages, limitations, and complementarities. Current standard practices put sufficiency at the core of Qualitative Comparative Analysis (QCA), while the analysis of necessity is limited to the test for necessary conditions. Here, we argue that the possibilities of QCA in the latter domain are much greater. In particular, it can be used to empirically confront theories centered on necessary relations and that involved various conditions. A new operation, labeled the "systematic necessity assessment," is therefore introduced. To show its added value, a published QCA study that confronts theories centered on necessary relations but using the regular minimization is replicated. Limited diversity is among the most understudied methodological challenges. QCA allows for a more conscious treatment of logical remainders than most other comparative methods. The current state of the art is the Standard Analysis (Ragin 2008; Ragin and Sonnett 2004). We discuss two of its pitfalls, both rooted in the primacy given to parsimony. First, the Standard Analysis is no safeguard against untenable assumptions. As a remedy, we propose the Enhanced Standard Analysis (ESA). Second, researchers should consider including theoretically sound counterfactual claims even if they do not contribute to parsimony. We label this Theory-Guided Enhanced Standard Analysis (TESA). This paper aims at strengthening causal inference in necessary condition research. We demonstrate how process tracing based on purposefully selected cases can complement findings on cross-case patterns identified with Qualitative Comparative Analysis (QCA). Using an empirical example, we discuss the meaning of typical and deviant cases in analyses of necessity, develop formulas for identifying the most typical and most deviant cases, and detail the implications of so-called SUIN conditions for meaningful case selection. In addition, we clarify various viable variants of comparative process tracing and formulas for identifying the best-matching pairs of cases.