Data Science, Statistics, Causality, Machine Learning, Analytics.
We can get principal components out of random noise but X won’t be a good predictor of Y. Furthermore, reusing the Y’s to estimate both the instrument and causal effect is philosophically problematic and will lead to overfitting. One avenue of thought is to split the dataset into two, fit PCA on