Measuring variations Causality and causal modelling in the social sciences

1. Measuring variationsCausality and causal modellingin 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 in the philosophy of causality:variation

5. The guiding question When we reason about cause-effect relations in causal modelling, what notion guides this reasoning? Regularity? Invariance? Production? ... 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 startsfrom the scientific practice, withinthe scientific practice raises methodological and epistemological issues, forthe 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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