Abstract In a recent issue of this journal, Philip Dawid (2021) proposes a framework for causal inference that is based on statistical decision theory and that is, in many aspects, compatible with the familiar framework of causal graphs (e.g., Directed Acyclic Graphs (DAGs)). This editorial...

Capital structure theories are often formulated as causal narratives to explain which factors drive financing choices. These narratives are usually examined by estimating cross-sectional relations between leverage and its determinants. However, the limitations of causal inference from...

Abstract The structural interpretation of counterfactuals as formulated in Balke and Pearl (1994a,b) [ 1 , 2 ] excludes disjunctive conditionals, such as “had $X$ been $x_1~\mbox{or}~x_2$ ,” as well as disjunctive actions such as $do(X=x_1~\mbox{or}~X=x_2)$ . In contrast, the closest-world...