IDSS Distinguished Seminar Series, Nov. 5, 2018 | ROCIO TITIUNIK

Title:
The Regression Discontinuity Design: Methods and Applications
Abstract:
The Regression Discontinuity (RD) design is one of the most widely used non-experimental strategies for the study of treatment effects in the social, behavioral, biomedical, and statistical sciences. In this design, units are assigned a score and a treatment is offered if the value of that score exceeds a known threshold-and withheld otherwise. In this talk, I will discuss the assumptions under which the RD design can be used to learn about treatment effects, and how to make valid inferences about them based on modern theoretical results in nonparametrics that emphasize the importance of extrapolation of regression functions and misspecification biases near the RD cutoff. I will also discuss the common approach of augmenting nonparametric regression models using predetermined covariates in RD setups, and how this affects nonparametric identification of as well as statistical inference about the RD parameter. If time permits, I will also discuss a more general version of the RD design based on multiple cutoffs, which expands the generalizability of the standard RD design by allowing researchers to test richer hypotheses regarding the heterogeneity of the treatment effect and, under additional assumptions, to extrapolate the treatment effect to score values far from the cutoff.