Machine Learning, Causal Inference, Data Science, Deep Dives, Notes From Industry.
auxiliary models on the first half, residualize the second half, and infer elasticity. After repeating with the two halves swapped, I take the mean of the two estimates, to obtain a robust causal estimate (assuming I was able to capture the relevant confounders). The final output looks like this: