This paper examines the role of education as causal channel through which growing up poor affects the economic outcomes in adulthood in the European Union. We apply a potential outcomes approach to quantify those impacts and we provide a sensitivity analysis on possible unobserved confounders,...

Abstract In randomized trials in which two treatment arms are compared with a binary outcome, the causal effect can be identified by assuming that the two treatment arms are exchangeable. In trials with an ordinal outcome, which is categorized as more than two, the causal effect can be...

Abstract We develop a mathematical and interpretative foundation for the enterprise of decision-theoretic (DT) statistical causality, which is a straightforward way of representing and addressing causal questions. DT reframes causal inference as “assisted decision-making” and aims to...

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...

In this paper we perform inference on the effect of a treatment on survival times in studies where the treatment assignment is not randomized and the assignment time is not known in advance. Two such studies are discussed: a heart transplant program and a study of Swedish unemployed eligible for...

This paper examines the role of education as causal channel through which growing up poor affects the economic outcomes in adulthood in the European Union. We apply a potential outcomes approach to quantify those impacts and we provide a sensitivity analysis on possible unobserved confounders,...

In this paper we perform inference on the effect of a treatment on survival times in studies where the treatment assignment is not randomized and the assignment time is not known in advance. Two such studies are discussed: a heart transplant program and a study of Swedish unemployed eligible for...