Component 1 (Macro): Quantitative (Regression) Analysis

This chapter corresponds to the macro-quantitative component. It discusses how competitiveness and corruption were modelled, how the methods were applied in the correlation analysis and which empirical results were achieved. Regression analysis is used to test the relationship between variables of some prominent prosperity/corruption theories. This part does not seek to prove causation, but instead empirically explores whether competitiveness/transparency are related to indicators such as state religion or a population’s religious affiliation. Consistent results of the models on competitiveness (GCI) are: (1) a positive influence of EPI on GCI; (2) a positive influence of a German legal origin (or German language) on GCI; (3) a negative influence of an Orthodox population on GCI; and (4) a negative influence of a Roman Catholic population (or Roman Catholic State Religion) on GCI. These results are also consistent with the predictions in the theory chapters (Chaps. 6 – 11 ). The corruption model applied here tests the interrelations between GDP, political liberties (democracy proxy), and language and ethnic fractionalisation. The results of the models on corruption are entirely compatible with theory. The results confirm my hypothesis that transparency levels are directly (i.e. positively) related to the proportion of Protestants in countries in Europe and the Americas.