Read this before running QCA

Thinking of using QCA in your work? Read these two papers, and make up your own mind:

Achen, Christopher H. 2005. “Two Cheers for Charles Ragin.” Studies in Comparative International Development 40 (1): 27–32. doi:10.1007/BF02686285.

Achen summarizes the three claims by Ragin: (1) case studies have their own methodology. Nobody disputes this (first cheer). (2) Often quantitative analyses do not match social reality (assumptions, linearity assumptions, etc.). Yes (second cheer), but that’s a question of applying the existing tools appropriately, not a problem with the tools. (3) That statistical analysis cannot cope with social reality. That’s not true, or only true if quantitative methods are applied in a poor way (no cheer here). Achen then outlines nicely that each step in QCA has an equivalent in long-established quantitative analysis, to which many have contributed.

Lucas, Samuel R., and Alisa Szatrowski. 2014. “Qualitative Comparative Analysis in Critical Perspective.” Sociological Methodology 44 (1): 1–79. doi:10.1177/0081175014532763.

Lucas and Szatrowski wanted to know whether QCA is any good. To find out, they used computer simulations where the true causal path was known (the programmed it). Their conclusions are quite clear: QCA correctly identifies only 3 out of 70 causal paths correctly. They are critical of the epistemological underpinnings, too.

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