X-Learner – a step further

In this section, we’ll introduce X-Learner – a meta-learner built to make better use of the information available in the data. We’ll learn how X-Learner works and implement the model using our familiar DoWhy pipeline.

Finally, we’ll compute the effect estimates on the full earnings dataset and compare the results with S- and T-Learners. We’ll close this section with a set of recommendations on when using X-Learner can be beneficial and a summary of all three sections about meta-learners.

Let’s start!

Squeezing the lemon

Have you noticed something?

Every time we built a meta-learner so far, we estimated two potential outcomes separately (using a single model in the case of S-Learner, and two models in the case of T-Learner) and then subtracted them in order to obtain CATE.

In a sense, we never tried to use our estimators to actually estimate CATE. We were rather estimating both potential outcomes...