This article evaluates the relative strengths and weaknesses of fuzzy-set analysis and regression analysis for explaining the “great reversal” in Spanish America. From 1750 to 1900, the most marginal colonial territories often became the region’s wealthiest countries, whereas the most central colonial territories often became the region’s poorest countries. To explain this reversal, five competing hypotheses are tested using both regression and fuzzy-set methods. The fuzzy-set analysis reaches substantively important conclusions, finding that strong liberal factions are probabilistically necessary for economic development and that dense indigenous populations are probabilistically necessary for social underdevelopment. By contrast, the regression analysis generates findings that are not meaningful. The article concludes that fuzzy-set analysis and regression analysis operate in different “causal universes” and that greater attention should be granted to the causal universe occupied by fuzzy-set analysis.
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