Apart from the well established and ever evolving quantitative research methods, a relatively new method begins to gain momentum. Political sciences, and more generally macro- comparative sociological studies work with a small number of cases (usually countries), and that renders standard statistics as sometimes unsuitable. This new methodology, called QCA - Qualitative Comparative Analysis (Ragin, 1987, 2000, 2008) is able to detect configurational patterns even for these small-N scenarios, but perhaps more interestingly it is fundamentally different from conventional statistics due to its asymmetric nature, inherited from its set theoretical nature. Conventional correlations are symmetric (more x, more y, or less x, less y), and the same explanatory model is responsible with both ends of the dependent variable’s continuum. By contrast, set theory is inherently asymmetric: a case belongs to a set or it does not, an outcome is either produced or it is not, and more importantly the configuration of causal factors that produce the outcome is most of the times different from the configuration responsible with the absence of the outcome. Both necessity and sufficiency can be determined by exploiting the set theoretic nature of the social science concepts, where their asymmetric nature becomes obvious: what is necessary for an outcome might not be necessary for its absence, and while necessary it might not always be sufficient. The other way round, what is sufficient for an outcome might not always be necessary, a fact that signals what is called ‘equifinality’, which posits the same outcome can be produced by multiple configurational patterns.