Clear, accessible explanations of new research, methods, and tools in causal inference and experimentation. We break down complex ideas without losing rigor.

Causal Inference with Multiple Simultaneous Treatments: Extending Double Machine Learning

Causal Inference with Multiple Simultaneous Treatments: Extending Double Machine Learning

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Bayesian Regression Discontinuity: Gaussian Process Priors and Flexible Inference at the Threshold

Bayesian Regression Discontinuity: Gaussian Process Priors and Flexible Inference at the Threshold

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The Borusyak-Jaravel-Spiess Imputation Estimator: Efficient DiD for Staggered Adoption Settings

The Borusyak-Jaravel-Spiess Imputation Estimator: Efficient DiD for Staggered Adoption Settings

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Regression Discontinuity with Multiple Running Variables: Frontier Designs and Identification

Regression Discontinuity with Multiple Running Variables: Frontier Designs and Identification

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Doubly Robust Difference-in-Differences: Sant'Anna and Zhao (2020)

Doubly Robust Difference-in-Differences: Sant'Anna and Zhao (2020)

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Regression Discontinuity with Distribution-Valued Outcomes

Regression Discontinuity with Distribution-Valued Outcomes

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Dynamic Causal Effects Beyond Linearity: Local Projections in Nonlinear Settings

Dynamic Causal Effects Beyond Linearity: Local Projections in Nonlinear Settings

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The Generalised Propensity Score: Causal Inference with Continuous Treatments

The Generalised Propensity Score: Causal Inference with Continuous Treatments

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Local Projections: Jordà (2005) and the LP-IV Method for Dynamic Causal Effects

Local Projections: Jordà (2005) and the LP-IV Method for Dynamic Causal Effects

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Sensitivity Analysis for Observational Studies: Rosenbaum Bounds and Oster's Delta

Sensitivity Analysis for Observational Studies: Rosenbaum Bounds and Oster's Delta

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Partial Identification and Manski Bounds: How Much Can We Learn Without Strong Assumptions?

Partial Identification and Manski Bounds: How Much Can We Learn Without Strong Assumptions?

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Regression Kink Design: Identifying Causal Effects at Policy Kinks

Regression Kink Design: Identifying Causal Effects at Policy Kinks

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Recent Results: Education, Development, and Long-Run Outcomes (2022-2025)

Recent Results: Education, Development, and Long-Run Outcomes (2022-2025)

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Honest DiD: Sensitivity Analysis for Pre-Trend Violations Rambachan and Roth (2023) and the HonestDiD Package

Honest DiD: Sensitivity Analysis for Pre-Trend Violations Rambachan and Roth (2023) and the HonestDiD Package

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Two-Way Fixed Effects with Heterogeneous Treatment Effects: The de Chaisemartin-D'Haultfoeuille (2020) Critique and the DID_M Estimator

Two-Way Fixed Effects with Heterogeneous Treatment Effects: The de Chaisemartin-D'Haultfoeuille (2020) Critique and the DID_M Estimator

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Synthetic Difference-in-Differences: Arkhangelsky et al. (2021)

Synthetic Difference-in-Differences: Arkhangelsky et al. (2021)

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Regression Discontinuity Design: Sharp, Fuzzy, and the Calonico-Cattaneo-Titiunik Bandwidth

Regression Discontinuity Design: Sharp, Fuzzy, and the Calonico-Cattaneo-Titiunik Bandwidth

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Double Machine Learning: Debiased Estimation with High-Dimensional Controls

Double Machine Learning: Debiased Estimation with High-Dimensional Controls

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Callaway–Sant’Anna DiD: Staggered Adoption and Group-Time ATTs

Callaway–Sant’Anna DiD: Staggered Adoption and Group-Time ATTs

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