Causality in the Social Sciences: a structural modelling framework
Quality & Quantity
https://doi.org/10.1007/S11135-019-00872-YAbstract
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.
References (22)
- Fagiolo, G., Moneta, A., Windrum, P.: A critical guide to empirical validation of agent-based models in eco- nomics: methodologies, procedures, and open problems. Comput. Econ. 30, 195-226 (2007)
- Gourbin, C., Wunsch, G., Moreau, L., Guillaume, A.: Direct and indirect paths leading to contraceptive use in urban Africa. An application to Burkina Faso, Ghana, Morocco and Senegal. Rev. Quetelet/Quetelet J. 5(1), 33-70 (2017)
- Hood, W.C., Koopmans, T.C. (eds.): Studies in econometric methods, Cowles Foundation Monograph 14. Wiley, New-York (1953)
- Illari, P., Russo, F.: Causality: philosophical theory meets scientific practice. Oxford University Press, Oxford (2014)
- Johnson, R.B., Russo, F., Schoonenboom, J.: Causation in mixed methods research: the meeting of philoso- phy, science, and practice. J. Mixed Methods Res. (2017). https ://doi.org/10.1177/15586 89817 71961 0
- Koopmans, T.C.: Measurement without theory. Rev. Econ. Stat. 29, 161-173 (1947)
- Koopmans, T.C. (ed.): Statistical inference in dynamic economic models, Cowles Foundation Monograph 10. Wiley, New York (1950)
- Little, D.: Levels of the social. In: Risjord, M., Turner, S. (eds.) Philosophy of anthropology and sociology, pp. 343-371. Elsevier Science, Amsterdam (2006)
- Mackie, J.L.: Causes and conditions. Am. Philos. Q. 2(4), 245-264 (1965)
- Morgan, S.L., Winship, C.: Counterfactuals and causal inference. Cambridge University Press, Cambridge (2007)
- Mouchart, M., Orsi, R.: Building a structural model: parameterization and structurality. Econometrics 4, 23 (2016). https ://doi.org/10.3390/econo metri cs402 0023
- Mouchart, M., Russo, F.: Causal explanation: recursive decompositions and mechanisms, chap. 15. In: McKay Illari, P., Russo, F., Williamson, J. (eds.) Causality in the sciences, pp. 317-337. Oxford Uni- versity Press, Oxford (2011)
- Mouchart, M., Russo, F., Wunsch, G.: Structural modelling, exogeneity, and causality, Chapter 4. In: Engel- hardt, H., Kohler, H.-P., Fürnkranz-Prskawetz, A. (eds.) Causal analysis in population studies: con- cepts, methods, applications, pp. 59-82. Springer, Dordrecht (2009)
- Mouchart, M., Russo, F., Wunsch, G.: Inferring causal relations by modelling structures. Statistica LXX(4), 411-432 (2010)
- Mouchart, M., Wunsch, G., Russo, F.: Controlling variables in social systems: a structural modelling approach. Bull. Sociol. Methodol. 132, 5-25 (2016)
- Pearl, J.: Causality. Models, reasoning, and inference. Cambridge University Press, Cambridge (2000). (revised and enlarged in 2009)
- Russo, F.: Causality and causal modelling in the social sciences: measuring variations, Methodos Series, vol. 5. Springer, Berlin (2009)
- Russo, F., Wunsch, G., Mouchart, M.: Inferring causality through counterfactuals in observational studies. Some epistemological issues. Bull. Sociol. Methodol. 111, 43-64 (2011)
- Wold, H.O.: Causality and econometrics. Econometrica 22(2), 162-177 (1954)
- Wunsch, G., Mouchart, M., Russo, F.: Functions and mechanisms in structural-modelling explanations. J. Gen. Philos. Sci. 45(1), 187-208 (2014)
- Wunsch, G., Mouchart, M., Russo, F.: Causal attribution in block-recursive systems: a structural modelling perspective. Methodol. Innov. (2018). https ://doi.org/10.1177/20597 99118 76841 5
- Wunsch, G., Russo, F., Mouchart, M.: Do we necessarily need longitudinal data to infer causal relations? Bull. Sociol. Methodol. 106, 5-18 (2010)