An MCA of QCA

An increasing number of analyses in various subelds of political science employ boolean algebra as proposed in Ragin’s (1987) qualitative comparative analysis (QCA). This type of analysis is perfectly well adapted if the goal is to test deterministic hypotheses under the assumption of error-free measures of the employed variables. My contention is that in very few research areas our theories are suciently advanced to yield deterministic hypotheses and given the nature of our objects of study error-free measures are largely an illusion. Hence, it cannot surprise that many studies employ QCA inductively and gloss over possible measurement errors. In this paper I address these issues and demonstrate the consequences of these problems with a simple empirical example. In a Monte Carlo analysis (MCA) I show that using boolean algebra in an exploratory fashion with error-prone measures may lead to dramatically erroneous inferences. I suggest two remedies

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