Keywords

This study applies a “mixed methods approach to grounded theory” (MM-GT) and combines qualitative and quantitative elements in several phases of the research process (i.e. data collection, analysis, inference). Such an approach serves to achieve “broad purposes of breadth and depth of understanding and corroboration” (Johnson, Onwuegbuzie, & Turner as cited in Schoonenboom & Johnson, 2017, p. 108).

Equally, MM-GT works well for research questions focusing on why and how the investigated phenomena function (including their qualitative and quantitative aspects). Consequently, MM-GT is appropriate here, since it concerns “meanings and processes or explanatory relationships” (and thus also causation) (Johnson et al., 2010, p. 72).

Mixed methods, such as those applied here, have proven useful for studying religious and secular milieus. One of their main advantages is that they ensure an increased validity of descriptions and explanations (Stolz, 2017).

This study is driven by an equal-status mixed methods research approach (Johnson, 2016). Thus, qualitative and quantitative components have equal value and weight. Figure 14.1 presents the research design:

Fig. 14.1
A flowchart presents historical and complex approaches. It starts with the research question or hypotheses and ends with the result, which includes synthesis, analysis, and conclusions.

Research design (Source: Author’s)

Full size image

This flowchart also shows the integrated sequential methods used in this research: each method informs the application of the other methods.

As will be explained, different research components, each corresponding to different yet complementary epistemological approaches, provide complementary results at different levels of analysis. In other words:

  • The “macro” approach is that quantitative component that exhibits general trends for countries and variables at a continental scale with minimum inferencing of causal relations. Correlations are used to test whether variables are related at a cross-country level (i.e. whether a population’s religious affiliation is linked to corruption).

  • QCA is the “meso” approach used to analyse both quantitative and qualitative data, and thus enabling inferences about causality. QCA clusters countries into groups of affinity and is used here to trace causal mechanisms (i.e. whether the adoption of Protestantism as a state religion is a necessary and sufficient condition for high levels of prosperity and transparency). QCA also allows briefly explaining each country situation in the dataset (around 60 countries). QCA analysis includes four case studies (the same cases are analysed in the “micro approach”—i.e. the next method).

  • The most detailed approach (“micro”) used in this study corresponds to the qualitative case studies on four selected countries for the purpose of specific analysis aimed at substantiating causal explanations. Case studies facilitate understanding differences and similarities, as well as causal mechanisms, from a qualitative perspective. This book includes four case studies on countries with (1) diverse geographical backgrounds, (2) different composition and dominance of Christian denominations, and (3) legal systems rooted in different origins.

In sum, the regression analysis of this study quantitatively explores the relations among factors/variables. QCA adds causality considerations and bridges quantitative relations and qualitative analysis. The four case studies are purely qualitative.