Causal Inference with Multiple Simultaneous Treatments: Extending Double Machine Learning

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

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

Regression Discontinuity with Multiple Running Variables: Frontier Designs and Identification

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

Regression Discontinuity with Distribution-Valued Outcomes

Dynamic Causal Effects Beyond Linearity: Local Projections in Nonlinear Settings

The Generalised Propensity Score: Causal Inference with Continuous Treatments

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

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

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

Regression Kink Design: Identifying Causal Effects at Policy Kinks

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

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

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

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

Double Machine Learning: Debiased Estimation with High-Dimensional Controls

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