Why High-order Polynomials Should not be Used in Regression Discontinuity Designs
It is common in regression discontinuity analysis to control for high order (third, fourth, or higher) polynomials of the forcing variable. We argue that estimators for causal effects based on such methods can be misleading, and we recommend researchers do not use them, and instead use estimators based on local linear or quadratic polynomials or other smooth functions.
We thank Jennifer Hill and Joseph Cummins for helpful comments and the National Science Foundation and Institute for Education Sciences for partial support of this work. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
We thank the Institute for Education Sciences and the National Science Foundation for partial support of this research.
Andrew Gelman & Guido Imbens (2017) Why high-order polynomials should not be used in regression discontinuity designs, Journal of Business & Economic Statistics, DOI: 10.1080/07350015.2017.1366909 citation courtesy of