Where data meets decisions
The Causal Review

Rigorous causal thinking for researchers, policymakers, and practitioners worldwide.

Three decades of methodological progress have fundamentally changed how we establish cause and effect in social science.

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A rare look inside one of tech's most sophisticated causal inference programs and what it found.

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The Chernozhukov-Demirer-Duflo method is reshaping how economists handle high-dimensional controls.

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The most fundamental concept in causal inference explained without equations.

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From DoubleML to CausalML, we benchmark the leading open-source packages for applied causal work.

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Are randomized trials the gold standard, or an overrated benchmark in a world of messy real-world constraints?

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The Causal Review exists to make causal inference clearer, more accessible, and more relevant. We translate rigorous research into clear, engaging stories connecting theory to practice.

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Annual Recognition

The Causal50 is our annual editorially curated recognition of the 50 most influential causal scientists in the world, spanning academia, industry, and public policy.

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