- Shunsuke Sato
This chapter discusses counterfactual analysis. Counterfactual inference has been a major topic in methodological discussions in many disciplines such as political science, history, psychology, philosophy, and others. When social scientists attempt to assess hypotheses about the causes of phenomena, counterfactual propositions generally play an important role. Particularly in qualitative small-N research designs, counterfactuals are indispensable tools for causal analysis because all causal statements imply some kind of counterfactual. The theoretical statement ‘X causes Y’ implies that if X’s value were different, outcome Y would be different. Essentially, when scholars explain why a particular outcome Y occurred, they need to explain why Y happened, rather than other possible outcomes. When scholars make a proposition that includes necessary conditions, they clarify counterfactual implications: a logical format of necessary conditions — ‘if not X, then not Y’ — directly expresses a counterfactual’s consequent. Therefore, most social scientists inevitably use counterfactual analysis for various purposes. The chapter then looks at the criteria for evaluating counterfactual analysis.