marketing analytics

Difference-in-Differences With a Continuous Treatment in R: The Dose Coefficient Is Not Marginal ROI

Put spend on the right-hand side of a fixed effects regression and the coefficient looks like marginal return. On simulated data with randomly assigned dose, it overstates the true marginal return by 31%. Here is why, and how the new contdid package fixes it.

If You Roll Out Market by Market, Your Lift Estimate Is Probably Too Low

The two-way fixed effects regression is the default for staggered geo rollouts. On simulated data where the true lift is known, it understates the effect by 41%. Here is why, and the estimator that fixes it, in R and Python.