causal inference

A hands-on guide to the fwlplot package in R --- from understanding the Frisch-Waugh-Lovell theorem through simulated confounding to visualizing fixed effects in real panel data --- showing what "controlling for" looks like as a scatter plot.

A hands-on guide to the scatterfit package in Stata --- from understanding the Frisch-Waugh-Lovell theorem through simulated confounding to visualizing fixed effects in real panel data --- showing what "controlling for" looks like as a scatter plot.

A guide to Difference-in-Differences with staggered treatment --- from TWFE pitfalls through Callaway-Sant'Anna group-time ATTs, doubly robust estimation, and HonestDiD sensitivity analysis --- applied to minimum wage effects on teen employment.

Assess how robust difference-in-differences results are to violations of parallel trends using the honestdid package in Stata, progressing from a simple 2x2 DiD to multi-period event studies with relative magnitudes and smoothness restrictions

Evaluate the causal effect of a cash transfer program on household consumption using regression adjustment, inverse probability weighting, doubly robust, and difference-in-differences methods in Stata

Estimating causal treatment effects using Difference-in-Differences with the diff-diff package, from the classic 2x2 design through staggered adoption with Callaway-Sant'Anna and HonestDiD sensitivity analysis

Understanding the Frisch-Waugh-Lovell theorem to isolate causal relationships by partialling-out confounders in a simulated retail store dataset

Computing causal bounds under unmeasured confounding using Manski and Tian-Pearl bounds with the CausalBoundingEngine package in Python

Estimating the causal effect of a job training program on earnings using DoWhy's four-step causal inference framework with the Lalonde dataset

Estimating the causal effect of a cash bonus on unemployment duration using Double Machine Learning with the Pennsylvania Bonus Experiment