Changes-in-Changes: Difference-in-Differences Without the Additive Straitjacket

Proximal Causal Inference: Identifying Effects When You Cannot Measure the Confounder

Causal Discovery: Learning Causal Structure from Data

Leniency Designs: A Practitioner's Guide to Judge and Examiner Instruments

Open Problems at the Frontier of Causal Inference: A 2025 Survey

Causal Inference with Abundant Data: Opportunities and Pitfalls in the Large-n World

Matrix Completion for Panel Data: Athey et al. (2021) and the Next Generation of Counterfactual Methods

A Tale of Three Frameworks: Reconciling Potential Outcomes, Structural Equations, and Directed Acyclic Graphs

Difference-in-Differences Meets Synthetic Control: The New Wave of Doubly Robust Hybrid Methods

Peer Effects and the Reflection Problem: Identification in Social Interactions

Causal Inference with Administrative Data: Opportunities and Pitfalls

Shift-Share Instruments: Design-Based vs Model-Based Identification

LLMs and Causal Discovery: Can Large Language Models Identify Causal Structure?

Beyond Binary: Difference-in-Differences with a Continuous Treatment

The Rise of Causal Inference in Economics: A Meta-Science Perspective

Marginal Treatment Effects: The Bridge Between LATE, Selection Models, and Policy Analysis

Bunching Estimators: Identifying Behavioural Responses at Kinks and Notches

Interference and Spillovers: When SUTVA Fails and What To Do About It

The Synthetic Control Method: Building Counterfactuals from Data

The Goodman-Bacon Decomposition: What Two-Way Fixed Effects Actually Estimates in Staggered Adoption Settings

Instrumental Variables: The Most Powerful and Most Abused-Tool in Econometrics

Natural Experiments: Finding Causal Evidence Without Randomisation

Heterogeneous Treatment Effects: Beyond the Average

The Credibility Revolution in Econometrics: Thirty Years On