Daniel Millimet and Marc F. Bellemare work on an interesting paper on the feasibility of assuming that fixed effects are fixed over long periods in causal inference models. They highlight an overlooked reality that fixed effects may fail to control for unobserved heterogeneity over long periods of time.
One lesson for causal identification using long panels is to think twice before assuming that fixed effects will take care of unobserved heterogeneity.
More on this is in our short post with Duygu Dagli at Data Duets. She uses rapid gentrification as an example. The short format is a new idea to post more often.