Skip to main content

Search NYU Steinhardt

Causal Inference

Course provides students with a basic knowledge of both how to perform analyses and critique the use of some more advanced statistical methods useful in answering policy questions. While randomized experiments will be discussed, the primary focus will be the challenge of answering causal questions using data that do not meet such standards. Several approaches for observational data including propensity score methods, instrumental variables, difference in differences, fixed effects models and regression discontinuity designs will be discussed. Examples from real public policy studies will be used to illustrate key ideas and methods.

Course #
APSTA-GE 2012
Units
3
Term
Fall
Department

Professors

Jennifer Hill

Director of PRIISM; Professor of Applied Statistics

jlh17@nyu.edu