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ABSTRACT
Crisp-set qualitative comparative analysis (csQCA), a research approach developed by Charles Ragin in the 1980s, aims to combine qualitative and quantitative research strategies. Applications of the method have appeared in numerous journals. Recently, csQCA has been criticized concerning the validity of the models it generates as a result of the fact that it is unable to distinguish real from random data. It is argued that csQCA always identifi es an explanatory model, even on the basis of random data. The paper addresses this hypothesis via a simulation. It uses randomly created datamatrices to show that csQCA can make a distinction between real and random data when model specifi cation parameters are taken into account. First of all, the proportion of explanatory conditions on cases should be below a certain threshold, which differs as a function of the combination of conditions on cases. Secondly, there is an upper-limit to the number of explanatory conditions which can be used in a csQCA-analysis. The importance of the design parameters are the result of the problem of uniqueness which is a consequence of the use of Boolean algebra. Five implications for comparative case research-design and csQCA are discussed.
Keywords: qualitative comparative analysis, model specifi cation, qualitative, quantitative, comparative case research
INTRODUCTION
Qualitative Comparative Analysis (QCA) is a comparative case-oriented research technique, based on Boolean algebra, which was developed by Charles C Ragin in the 1980s and 1990s. Ragin's aim was to develop a new research approach which combined some strengths of qualitative and quantitative research methods. QCA aims to develop descriptive or even explanatory models on the basis of a systematic comparison of a small number of cases. QCA has been applied in numerous studies in sociology, political science, policy analysis, organizational studies and other fi elds (for an overview see Table 4). As noted by Gerring (2001) QCA is one of the few genuine methodological innovations of the last few decades. In an era of doubts on macro-quantitative approaches (Ebbinghaus, 2005; Kittel, 2006) and increased attention to case studies in many social sciences (Bates et al., 1998; Box-Steffensmeier, Brady, & Collier, 2008; Brady & Collier, 2004; George & Bennett, 2005; Mahoney & Rueschemeyer, 2003; Rihoux & Ragin, 2009; Rodrick, 2003) QCA holds the potential to...