Causality in the Social Sciences: a structural modelling framework

  • Federica Russo
  • Guillaume Wunsch
  • Michel MouchartEmail author


There is no unified theory of causality in the sciences and in philosophy. In this paper, we focus on a particular framework, called structural causal modelling (SCM), as one possible perspective in quantitative social science research. We explain how this methodology provides a fruitful basis for causal analysis in social research, for hypothesising, modelling, and testing explanatory mechanisms. This framework is not based on a system of equations, but on an analysis of multivariate distributions. In particular, the modelling stage is essentially distribution-free. Adopting an SCM approach means endorsing a particular view on modelling in general (the hypothetico-deductive methodology), and a specific stance on exogeneity (namely as a condition of separability of inference), on the one hand, and in interpreting marginal–conditional decompositions (namely as mechanisms), on the other hand.


Structural causal modelling Recursive decomposition Mechanisms Causality - Causal modelling 



Comments, in particular by Catherine Gourbin, Renzo Orsi, and Frans Willekens, on former versions of this paper, are gratefully acknowledged.


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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of PhilosophyUniversity of AmsterdamAmsterdamThe Netherlands
  2. 2.Center for Demographic ResearchUniversity of Louvain (UCLouvain)Louvain-la-NeuveBelgium
  3. 3.Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)University of Louvain (UCLouvain)Louvain-la-NeuveBelgium

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