The representation of women in national parliaments is one of the central questions in gender-sensitive political science and can be analyzed with many different methodological tools and perspectives. In the proposed paper, we combine fuzzy set Qualitative Comparative Analysis (QCA) and regression analysis to explain the occurrence of high and low proportions of women in parliaments.
So far, QCA is often compared to standard quantitative techniques. In a recent article on women’s legislative representation, e.g. Stockemer (2013) compares “the value of qualitative comparative analysis (fsQCA) versus regression analysis”. He concludes that “OLS regression analysis performs somewhat better than fsQCA” (ibid p. 86) as the latter a) suggests complex configurations with low coverage instead of two statistically significant variables and b) shows a high sensitivity to coding.
In our paper we, firstly, show that these results arise a) from a non-understanding of the set theoretic foundation of QCA, namely the principles of conjunctural causation, equifinality and asymmetry, and b) from a non-informed use of QCA. Thus we, secondly, apply both fsQCA and regression analysis to the original data used by Stockemer and address the importance of an informed calibration procedure avoiding the allocation of the 0.5-anchor as the point of maximum ambiguity. Finally, we discuss shortcomings of stand-alone fsQCA and regression analysis in the study of women’s legislative representation. We conclude that comparing the value of these fundamentally different approaches is rather arbitrary and identify ways how to overcome the shortcomings in a mixed method design.
