We establish identifying assumptions and estimation procedures for the ATT in a Difference-in-Differences setting with staggered treatment adoption in the presence of spillovers. We show that the ATT can be estimated by a simple TWFE method that extends the approach of Wooldridge [2022]’s...

We develop a method to identify the individual latent propensity to select into treatment and marginal treatment effects. Identification is achieved with survey data on individuals' subjective expectations of their treatment propensity and of their treatmentcontingent outcomes. We use the method...

When drawing causal inferences from observational data, researchers often model the propensity score. To date, the literature on the estimation of propensity scores is vast, and includes covariate selection algorithms as well as super learners and model averaging procedures. The latter often...