Double Machine Learning in Practice: The DoubleML Package (R and Python)

Causal Forests in R: The grf Package

fixest in R: Fast Fixed Effects, Event Studies, and Sun-Abraham DiD

rdrobust in R: Optimal Bandwidth and Robust Inference for Regression Discontinuity Designs

fixest in R: Fast Fixed Effects, Event Studies, and Sun–Abraham DiD

fixest is the fastest fixed-effects estimator in R—and it handles staggered DiD, event studies, and two-way clustering with ease.

rdrobust in R: Optimal Bandwidth and Robust Inference for RDD

A practical walkthrough of the rdrobust package: bias-corrected confidence intervals, bandwidth selection, and the McCrary density test.

The `augsynth` Package in R: Synthetic Control and ASCM

A step-by-step guide to the augsynth package: ridge-augmented synthetic control, bias correction for imperfect pre-treatment fit, and staggered adoption via multisynth—all with replicable R code.

The `did` Package in R: A Complete Workflow

The definitive workflow for the did package in R: estimating group-time ATTs, building event study plots, aggregating effects, and running sensitivity analysis under staggered treatment adoption.