DSci Happy Hour with David Hirshberg

"Inference based on imagined randomization" Statistical analysis requires that something be random, e.g. random sampling from a population or randomized assignment of treatment. But in panel data — repeated observations of the same units over time — it’s often unclear what, if anything, is actually random. Whatever statistical claims we make are based on a random mechanism we’re imagining. This talk is about basing our analysis on imagined randomization of treatment: what assignment mechanisms we might want to imagine, what we can conclude if we buy into what we’re imagining, and how we might interpret those conclusions with a little more skepticism. The main example will be an analysis of synthetic control methods having imagined that units select treatment independently with unknown unit-specific probabilities (Arkhangelsky & Hirshberg, arXiv:2311.13575).