The objective of this paper is to present a short overview of the Structural Causal Modelling (SCM) framework developed by the present authors in a series of articles spanning the last decade or so. The text is based on a presentation given at Statistics Netherlands in Heerlen on December 4, 2018 (Russo, Wunsch, Mouchart, 2019). The purpose is to explain how the SCM framework provides the tools to hypothesize, model, and test explanatory mechanisms. Our framework proves particularly useful in social science contexts, since it allows us to adopt an explicit causal perspective even when analyzing observational data. Social science experiments are notoriously difficult to carry out for ethical or practical reasons, and our approach allows social scientists to go beyond mere description and to propose a causal explanation even in the absence of experiments and interventions.
Wunsch, G., Mouchart, M., & Russo, F. (2019). Examining Cause-Effect Relations in the Social Sciences A Structural Causal Modelling Approach. STAtOR, 3(September), 18-22. https://hdl.handle.net/2078.5/124506 (Original work published 2019)