heterogeneous treatment effects

Causal Machine Learning and the Resource Curse with Python EconML

Estimate heterogeneous causal effects of mining and mineral prices on economic development using EconML's CausalForestDML with Double Machine Learning, applied to simulated resource curse data

Causal Machine Learning and the Resource Curse with Stata 19

Estimate heterogeneous causal effects of mining and mineral prices on economic development using Stata 19's cate command with multi-valued treatment via pairwise binary comparisons, applied to a simulated resource curse panel dataset

Conditional Average Treatment Effects (CATE) with Stata 19

Estimate how the effect of 401(k) eligibility on household assets varies across households using Stata 19's new cate command, with PO, AIPW, GATE, GATES, and nonparametric series estimators applied to the canonical assets3 dataset