Component 2 (Meso): Qualitative Comparative Analysis (QCA)

Jason García Portilla
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Jason García Portilla: University of St. Gallen

Chapter Chapter 16 in Ye Shall Know Them by Their Fruits, 2022, pp 233-255 from Springer

Abstract: Abstract This chapter contains the meso component (Qualitative Comparative Analysis, QCA). It discusses the QCA research model, the QCA methodology, and the analysis of the QCA results. QCA is used to analyse both quantitative and qualitative data, thus enabling causal inferences. However, QCA is not a statistical technique that focuses on the likelihood of the relations among variables. Instead, it is a method based on Boolean logic, rooted in set theory, and founded on the notions of sufficiency, the necessity of conditions, and conjunctural causation. QCA results indicate, among others, that for high competitiveness, high EPI suffices if Concordats with the Vatican are low and if the Roman Catholic and Orthodox population is low. No State Religion positively affects competitiveness. Having Concordats with the Vatican negatively influences competitiveness. Additionally, factors like German, English, and Scandinavian legal origin help to increase competitiveness. Oppositely, QCA results for high corruption indicate that Concordats in combination with Roman Catholic religion adherence increase corruption. Orthodox religion has a similar negative effect. Most countries with high corruption are of French legal origin and have high Concordats. This trend is robust. Colombia and Switzerland (the two extreme cases) exhibited several consistent QCA results. The other two cases (Cuba and Uruguay) only revealed one or two consistent outcomes.

Keywords: Qualitative comparative analysis; Competitiveness; Corruption; Environment Performance Index (EPI); Roman Catholic population and state religion; Concordats; Protestants; Languages; Ethnicities; Legal origin (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:conchp:978-3-030-78498-0_16

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DOI: 10.1007/978-3-030-78498-0_16

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