Abstract
This section explains how to perform QCA using fuzzy sets, commonly referred to as fsQCA. Since the publication of Ragin (2000), fsQCA has become increasingly popular because continuous base variables need not be dichotomized. After a short theoretical introduction to the concept of fuzzy-set calibration, we introduce the two most popular calibration methods: direct assignment and transformational assignment. While the former is quickly dealt with, more time will be spent on the latter as its mechanisms and implications have so far received little attention. In the remainder of the chapter, the results from the study by Emmenegger (2011) on job-security regulations in Western democracies are replicated.
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