Dustin Tingley and Marc Ratkovic: Causal Inference through the Method of Direct Estimation


Wednesday, April 26, 2017, 12:00pm to 1:30pm


CGIS Knafel Building 354

Workshop in Applied Statistics presentation by Dustin Tingley and Marc Ratkovic.


Abstract: The intersection of causal inference and machine learning is a rapidly advancing field. We propose a new approach, the method of direct estimation, that draws on both traditions in order to obtain nonparametric estimates of treatment effects. The approach focuses on estimating the effect of fluctuations in a treatment variable on an outcome. A tensor-spline implementation enables rich interactions between functional bases allowing for the approach to capture treatment/covariate interactions. We show how new innovations in Bayesian sparse modeling readily handle the proposed framework, and then document its performance in simulation and applied examples. Furthermore we show how the method of direct estimation can easily extend to structural estimators commonly used in a variety of disciplines, like instrumental variables, mediation analysis, and sequential g-estimation.

Link to paper: http://scholar.harvard.edu/dtingley/files/mde.pdf


See also: Workshops