Measuring variations Causality and causal modelling in the social sciences Federica Russo Philosophy, Louvain & Kent

2 Overview Locate this work: Metaphysics, epistemology, methodology of causality Domain; interest; objective The guiding question Rationale (vs. definition) Methodology of research and types of arguments A taste of methodological arguments Structural equations A taste of possible objections Regularity; Invariance; Homogenous populations

3 Philosophy of causality Metaphysics What causality/cause is Epistemology How do we know about causal relations Methodology Develop/implement methods for discovery/confirmation of causal relations

4 This work Epistemology of causality Domain quantitative social science Interest causal reasoning in causal modelling Objective dig out a neglected notion variation in the philosophy of causality: variation

5 The guiding question When we reason about cause-effect relations in causal modelling, notion what notion guides this reasoning? Regularity? Invariance? Production?... rationale Hunting for a rationale

6 Rationale vs. definition Rationale: a principle/notion/concept underlying decision/reasoning/modelling Definition: A description of a thing by means of its properties or if its function Here: hunt for the notion underlying model building and model testing: rationale, not definition

7 Methodology of research Bottom-up rather than top-down A philosophical investigation that starts starts from the scientific practice, within within the scientific practice raises methodological and epistemological issues, for for the scientific practice points to the path forward

8 The answer Causal modelling is regimented by a rationale of variation

9 Arguments Empirical: Look at informal reasoning in case studies Methodological: Look at rationale of model building & testing in various causal models Philosophical: Look at arguments given by other philosophers Foundational: Look at forefathers of causal modelling Compatibility: Look at various established philosophical accounts

10 A taste of methodological arguments Consider a structural equation Y =  X+  Are there meaningful co-variations between X and Y? Are those variations chancy or causal? hypothesis testing; invariance; exogeneity

11 Therefore… Variation is a precondition with respect to other notions E.g.: regularity, invariance Any role left to those? Yes – constraints: Regularity: often enough Invariance: stability of parameters Rule out accidental and spurious variations, Grant causal interpretation of variations

12 A taste of objections Regularity Mine is just a reformulation of regularity theory Only partly true Regularity is more basic. Not quite: regularity of what? Invariance Invariance is more basic. Not quite: invariance of what? Homogenous populations No variations in homogenous populations. That’s the point: to make variations emerge

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