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Qualitative Comparative Analysis (QCA) and Set Theory  

Claudius Wagemann

Qualitative Comparative Analysis (QCA) is a method, developed by the American social scientist Charles C. Ragin since the 1980s, which has had since then great and ever-increasing success in research applications in various political science subdisciplines and teaching programs. It counts as a broadly recognized addition to the methodological spectrum of political science. QCA is based on set theory. Set theory models “if … then” hypotheses in a way that they can be interpreted as sufficient or necessary conditions. QCA differentiates between crisp sets in which cases can only be full members or not, while fuzzy sets allow for degrees of membership. With fuzzy sets it is, for example, possible to distinguish highly developed democracies from less developed democracies that, nevertheless, are rather democracies than not. This means that fuzzy sets account for differences in degree without giving up the differences in kind. In the end, QCA produces configurational statements that acknowledge that conditions usually appear in conjunction and that there can be more than one conjunction that implies an outcome (equifinality). There is a strong emphasis on a case-oriented perspective. QCA is usually (but not exclusively) applied in y-centered research designs. A standardized algorithm has been developed and implemented in various software packages that takes into account the complexity of the social world surrounding us, also acknowledging the fact that not every theoretically possible variation of explanatory factors also exists empirically. Parameters of fit, such as consistency and coverage, help to evaluate how well the chosen explanatory factors account for the outcome to be explained. There is also a range of graphical tools that help to illustrate the results of a QCA. Set theory goes well beyond an application in QCA, but QCA is certainly its most prominent variant. There is a very lively QCA community that currently deals with the following aspects: the establishment of a code of standards for QCA applications; QCA as part of mixed-methods designs, such as combinations of QCA and statistical analyses, or a sequence of QCA and (comparative) case studies (via, e.g., process tracing); the inclusion of time aspects into QCA; Coincidence Analysis (CNA, where an a priori decision on which is the explanatory factor and which the condition is not taken) as an alternative to the use of the Quine-McCluskey algorithm; the stability of results; the software development; and the more general question whether QCA development activities should rather target research design or technical issues. From this, a methodological agenda can be derived that asks for the relationship between QCA and quantitative techniques, case study methods, and interpretive methods, but also for increased efforts in reaching a shared understanding of the mission of QCA.

Article

Qualitative Comparative Analysis (QCA) in Public Administration  

Eva Thomann and Jörn Ege

Qualitative Comparative Analysis (QCA) is increasingly establishing itself as a method in social research. QCA is a set-theoretic, truth-table-based method that identifies complex combinations of conditions (configurations) that are necessary and/or sufficient for an outcome. An advantage of QCA is that it models the complexity of social phenomena by accounting for conjunctural, asymmetric, and equifinal patterns. Accordingly, the method does not assume isolated net effects of single variables but recognizes that the effect of a single condition (that is, an explanatory factor) often unfolds only in combination with other conditions. Moreover, QCA acknowledges that the occurrence of a phenomenon can have a different explanation from its non-occurrence. Finally, QCA allows for different, mutually non-exclusive explanations of the same phenomenon. QCA is not only a technique; there is a diversity of approaches to how it can be implemented before, during and after the “technical moment,” depending on the analytic goals related to contributing to theory, engaging with cases, and the approach to explanation. Particularly since 2012, an increasing number of scholars have turned to using QCA to investigate public administrations. Even though the boundaries of Public Administration (PA) as an academic discipline are difficult to determine, it can be defined as an intellectual forum for those who want to understand both public administrations as organizations and their relationships to political, economic, and societal actors—especially in the adoption and implementation of public policies. Owing to its fragmented nature, there has been a long-lasting debate about the methodological sophistication and appropriateness of different comparative methods. In particular, the high complexity and strong context dependencies of causal patterns challenge theory-building and empirical analysis in Public Administration. Moreover, administrative settings are often characterized by relatively low numbers of cases for comparison, as well as strongly multilevel empirical settings. QCA as a technique allows for context-sensitive analyses that take into account this complexity. Against this background, it is not surprising that applications of QCA have become more widespread among scholars of Public Administration. A systematic review of articles using QCA published in the major Public Administration journals shows that the use of QCA started in mid-2000s and then grew exponentially. The review shows that, especially in two thematic areas, QCA has high analytical value and may (alongside traditional methodological approaches) help improve theories and methods of PA. The first area is the study of organizational decision-making and the role of bureaucrats during the adoption and implementation of public policies and service delivery. The second area where QCA has great merits is in explaining different features of public organizations. Especially in evaluation research where the aim is to investigate performance of various kinds (especially effectiveness in terms of both policy and management), QCA is a useful analytical tool to model these highly context-dependent relationships. The QCA method is constantly evolving. The development of good practices for different QCA approaches as well as several methodological innovations and software improvements increases its potential benefits for the future of Public Administration research.