The UBC Statistics Department Colloquium Series features talks that are broad, accessible, and engaging—and open to everyone!
Our second talk of the series will take place on Tuesday, April 21st. We’re excited to welcome Dr. Edward Kennedy, Associate Professor in the Department of Statistics and Data Science at Carnegie Mellon University.
Date: Tuesday, April 21, 206
Time: 11 AM - 12 PM
Location: ESB 5104/5106
Title: Nonparametrics in causal inference: densities, heterogeneity, & beyond
Abstract: Much work in causal inference focuses on finite-dimensional targets like average treatment effects. However, many substantively important causal questions involve inherently infinite-dimensional objects, such as counterfactual outcome distributions, heterogeneous treatment effect surfaces, and continuous treatment curves. These targets occupy a hybrid space between classical parameter estimation and nonparametric function estimation. In this talk, I survey some recent work involving these infinite-dimensional causal estimands, highlighting both model-based and model-free nonparametric approaches. I discuss how, despite the impossibility of root-n-rate estimation, ideas from semiparametric theory (like double robustness) continue to play a central role. Throughout I emphasize the relevance of these methods in applications in social sciences and medicine.
This colloquium series is sponsored in part by the Constance van Eeden Endowment.
Future talks in this colloquium series:
Monday, June 8
Speaker: Dr. Stephanie Hicks (Johns Hopkins University)
Time: 3–4 PM
Location: ESB 5104/5106