Why High-order Polynomials Should not be Used in Regression Discontinuity Designs

Andrew Gelman and Guido Imbens

No 20405, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: C01 C1 (search for similar items in EconPapers)
Date: 2014-08
New Economics Papers: this item is included in nep-ecm and nep-ore
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Published as 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

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Journal Article: Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs (2019)
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