In-depth explorations of the most important ideas, debates, and breakthroughs in causal inference. Feature stories connect theory to practice, covering causal AI, experimentation at scale, policy evaluation, and the future of evidence-based decision-making.
Feature Stories
Matrix Completion for Panel Data: Athey et al. (2021) and the Next Generation of Counterfactual Methods
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A Tale of Three Frameworks: Reconciling Potential Outcomes, Structural Equations, and Directed Acyclic Graphs
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Difference-in-Differences Meets Synthetic Control: The New Wave of Doubly Robust Hybrid Methods
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Peer Effects and the Reflection Problem: Identification in Social Interactions
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LLMs and Causal Discovery: Can Large Language Models Identify Causal Structure?
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Marginal Treatment Effects: The Bridge Between LATE, Selection Models, and Policy Analysis
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Bunching Estimators: Identifying Behavioural Responses at Kinks and Notches
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The Goodman-Bacon Decomposition: What Two-Way Fixed Effects Actually Estimates in Staggered Adoption Settings
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Instrumental Variables: The Most Powerful and Most Abused-Tool in Econometrics
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