Toward a Unified Theory of Causality

Abstract

In comparative research, analysts conceptualize causation in contrasting ways when they pursue explanation in particular cases (case-oriented research) versus large populations (population-oriented research). With case-oriented research, they understand causation in terms of necessary, sufficient, INUS, and SUIN causes. With population-oriented research, by contrast, they understand causation as mean causal effects. This article explores whether it is possible to translate the kind of causal language that is used in case-oriented research into the kind of causal language that is used in population-oriented research (and vice versa). The article suggests that such translation is possible, because certain types of INUS causes manifest themselves as variables that exhibit partial effects when studied in population-oriented research. The article concludes that the conception of causation adopted in case-oriented research is appropriate for the population level, whereas the conception of causation used in population-oriented research is valuable for making predictions in the face of uncertainty.