Causal Inference

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Judea Pearl ;
Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 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.

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