Machine Learning, Causal Inference, Meta Learning, Instruments, Observational Studies.
] = h(X,W) , so that the expected value of Y depends on (T, X, and W). This is known as the exclusion restriction. We assume that the conditional distribution F ( T | X, W, Z ) varies with Z . This is known as the relevant condition. The heterogeneous treatment effects are what we want to learn: