A Linear “Microscope” for Interventions and Counterfactuals

Pearl Judea ()
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Pearl Judea: Computer Science Department, University of California, Los Angeles, CA 90095-1596, USA

Journal of Causal Inference, 2017, vol. 5, issue 1, 15

Abstract: This note illustrates, using simple examples, how causal questions of non-trivial character can be represented, analyzed and solved using linear analysis and path diagrams. By producing closed form solutions, linear analysis allows for swift assessment of how various features of the model impact the questions under investigation. We discuss conditions for identifying total and direct effects, representation and identification of counterfactual expressions, robustness to model misspecification, and generalization across populations.

Keywords: causal inference; structural equation models; counterfactuals; generalization; robustness (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:causin:v:5:y:2017:i:1:p:15:n:2

DOI: 10.1515/jci-2017-0003

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