9 Treatment Effect Heterogeneity

Readings

Estimating Treatment Effects with Causal Forests: An Application

Lecture

Lecture slides are available here.

Lab

The objective of the lab is to identify treatment effect heterogeneity using a causal forest, combining the DHS data we’ve been working with and this file containing (simulated) data on treatment assignments (W) and outcomes (Y). Examples illustrating causal forests in simulated data are here in R and in Python. The templates for the lab are available here (for R) and here (for Python).