Robust Regression Discontinuity Extrapolation

Music City Center 

This paper studies identification and estimation of regression discontinuity (RD) extrapolation processes that measure policy effects away from the running variable cutoff. Our proposed semi-parametric identification strategy uses weaker assumptions than those previously adopted in the literature and, at the same time, enjoys a new robustness property of reducing to classic nonparametric RD identification when the magnitude of extrapolation goes to zero. For estimation and inference, we propose a doubly-robust two-step procedure that provides first-step bias-correction as well as valid inference. We applied our proposed method to extend the empirical analysis in Lindo, Sanders, and Oreopoulos (2010) on college academic probation. Our method allows us to estimate the effect of academic probation for students not exactly at the probation GPA cutoff.

Regression Discontinuity; Extrapolation; Estimation; Inference