Dynamic Causal Inference with Unobserved Discrete Confounders

• In Event: Advances in Causal Inference

Brief Overview

We propose scholars use changepoint modelling for dynamic regression to make dynamic inferences robust to unobserved, discrete confounding variables. We demonstrate our approach via simulation and an empirical example.

Authors

• Garrett N. Vande Kamp, University of Georgia

• Soren Jordan, Texas A&M University

• Reshi Rajan, Texas A & M University, College Station