Causal Inference
Judea Pearl; JMLR W&CP 6:39-58,
2010.
Abstract
This paper reviews a theory of causal inference based on the Structural Causal Model (SCM) described in Pearl (2000a).
The theory unifies the graphical, potential-outcome (Neyman-Rubin), decision analytical, and structural equation approaches to causation,
and provides both a mathematical foundation and a friendly calculus for the analysis of causes and counterfactuals.
In particular, the paper establishes a methodology for inferring (from a combination of data and assumptions) the answers to
three types of causal queries: (1) queries about the effect of potential interventions, (2) queries about counterfactuals,
and (3) queries about the direct (or indirect) effect of one event on another.
