Explaining causal modellingOR

What a causal model ought to explain

Federica RussoUniversité catholique de

Louvain

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Overview What is a causal model

Explanatory vocabulary in causal modelling

Modelling causal mechanisms

Causal-model explanations

Causal modelling vs. other models

What is a causal model

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X1Economic

development

X2Social

development

X3Sanitary

infrastructures

X4Use of

sanitary infrastructure

sX5

Age structure

YMortality

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31133

21122

14422

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XXY

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Causal models

Rest on a number of assumptions

Model causal relations statisticallystatistically

Uncover stable variational relations

Explanatory vocabulary in causal modelling

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Explanation in structural equations

Y=X+X, Y : explanatory and response variables

Xs explain Y

Intuitively:Xs explain Y

Xs account for Y

Xs are relevant causal factors in the causal mechanism

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CM explains variability in YY=X+

Variations in X explain variations in Y

How is explanation ‘quantified’?

r2 represents the fraction of variability in Y explained by X

r2 indicates how much variability in Y is accounted for by the regression function

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But … r2 measures the goodness of fit,

not the validity of the model

r2 doesn’t give any theoretical reason for the accounted variability

r2 depends on the correctness of assumptions

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The philosophical answer

Explanatory import is given by:

Covariate sufficiency

No-confounding

Background knowledge

Modelling causal mechanisms

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Causal models model mechanisms

Most widespread conception:Mechanisms are made of physical processes, interactions, …, assembled to behave like a gear

But:What if we have

socio-economic-demographic variables?social and biological variables?

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A mixed mechanism

TreatmentPrevention

Socioeconomicdeterminants

Maternalfactors

Environmental contamination

Nutrientdeficiency

Injury

Healthy Sick

Personal illness control

Growthfaltering

Mortality

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The causal model incorporates social and biological variables

Modelling the mechanism gives the causal model explanatory power

Causal-models explanations

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Causal modelling is a model of explanation

The formal structure of explanation is given

by the methodology of causal modelling:

Formulate the causal hypothesis

Build the statistical model

Draw consequences to conclude to empirical validity/invalidity of the hypothesis

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CM explanations are flexible:

they allow a va et viens between established theories and establishing theories

they participate in establishing new theories

negative results may trigger further research

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CM explanations allow control:

1) statisticalr2 measures amount of variability explained

2) epistemicCM requires coherence of resultswith background knowledge

3) metaphysicalCM requires ontological homogeneitybetween variables in the mechanism

Causal modellingvs

other models of explanation

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CM vs deductive-nomological model well known problems with laws not all explanations involve deduction

CM vs statistical-relevance model S-R is too narrow in scope

CM vs causal-mechanical model it cannot account for mixed mechanisms

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CM vs manipulationist modelWoodward (2003)

A theory of causal explanation

Causal generalisations are change-relating

Change-relating relations are explanatory:they are invariant under a large class of interventions or environmental changes

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Generalisations show:(i) that the explanandum was to be expected(ii) how the explanandum would change

if initial conditions had changed

What-if-things-had-been-different questions

Relevant counterfactuals describe outcomes of interventions

Explanatory power is tested by means of counterfactual questions

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However …The manipulationist account:

Overlooks the role of background knowledge

Neglects the causal role of non-manipulable factors

Takes for granted what the causes are

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To sum upCausal modelling

Aims at explaining social phenomena

Makes essential use of explanatory vocabulary

Has explanatory power insofar as it models mechanism

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To concludeCausal modelling is a model of explanation

Among its virtues, over and above alternative models:

FlexibilityControl