Causal Inference

My causal inference research develops tools for evaluating methods for estimating the effects of policies and interventions using observational data. I have conducted simulation studies comparing the performance of different causal inference approaches—including synthetic control methods, difference-in-differences, and time-varying treatment models—under various confounding scenarios. I also develop tools to help researchers select appropriate methods for policy evaluation. This work is particularly focused on state-level policy evaluations where randomized experiments are infeasible.