Comparative Policy Studies Conceptual and Methodological Challenges
In the first volume of its kind, a collection of top policy scholars combine empirical and methodological analysis in the field of comparative policy studies to provide compelling insights into the formulation, implementation and evaluation of policies ac
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Intermediate-N Comparison: Configurational Comparative Methods Isabelle Engeli, Benoît Rihoux and Christine Rothmayr Allison
Introduction Configurational Comparative Methods (CCMs), also called ‘set-theoretic’ methods, is a broad and encompassing label that embraces crisp-set and fuzzy-set Qualitative Comparative Analysis (QCA) as well as some alternative techniques. All CCM-related techniques conceive cases as configurations of attributes and are geared towards systematic cross-case analysis. QCA represents both a distinctive research approach, with its own aims and set of assumptions, and an umbrella term for specific techniques such as fuzzy-set QCA (fsQCA), which will be the focus of this chapter (Ragin, 2000, 2008a; Rihoux and Ragin, 2009; Schneider and Wagemann, 2012; Thiem and Dusa, 2013). In Ragin’s seminal book (1987), the CCM approach was launched by the development of a new technique in which investigation was based on grouping dichotomous cases, crisp-set QCA (csQCA). It was later developed into fsQCA and other related techniques. The comparative essence of QCA stems from the fact that it was initially geared towards the analysis of multiple cases in a small- and intermediate-N research design (Marx et al., 2013). Ragin’s motivation (1987, 1997) was to develop a ‘synthetic strategy’ as a middle way between the case-oriented (or ‘qualitative’) and the variable-oriented (or ‘quantitative’) approaches. According to Ragin, this middle way would ‘integrate the best features of the case-oriented approach with the best features of the variable-oriented approach’ (Ragin, 1987: p. 84). On the one hand, QCA aims at contextualizing explanations by gathering in-depth within-case knowledge and capturing the complexity of cases. On the other hand, if the ability of QCA to approximate ‘the best features’ of regression analysis approaches is contested (see, for instance, Lieberson, 2004; Seawright, 2005; Hug, 2012), QCA nevertheless provides some systematic tools for comparing 85
10.1057/9781137314154.0010 - Intermediate-N Comparison, Isabelle Engeli, Benoît Rihoux and Christine Rothmayr Allison
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Comparative Policy Studies
an often limited number of policies that are available for investigation. QCA concentrates on producing some level of parsimony across cases and, thereby, facilitates limited forms of middle-range or ‘contingent’ generalization for medium-N analysis in comparative public policy (Ragin, 1987; Blatter and Blume, 2008;
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