Causality in the Social Sciences: a structural modelling framework
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| Publication date | 09-2019 |
| Journal | Quality and Quantity |
| Volume | Issue number | 53 | 5 |
| Pages (from-to) | 2575-2588 |
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| Abstract |
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.
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| Document type | Article |
| Note | In special issue: New challenges for Services Quality Evaluation. |
| Language | English |
| Published at | https://doi.org/10.1007/s11135-019-00872-y |
| Downloads |
Russo2019_Article_CausalityInTheSocialSciencesAS
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