Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs
It is common in regression discontinuity analysis to control for third, fourth, or higher-degree polynomials of the forcing variable. There appears to be a perception that such methods are theoretically justified, even though they can lead to evidently nonsensical results. We argue that controlling...
Main Authors: | Gelman, A. (Author), Imbens, G. (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
American Statistical Association
2019
|
Subjects: | |
Online Access: | View Fulltext in Publisher |
Similar Items
-
Using the Chow Test to Analyze Regression Discontinuities
by: Howard H. Lee
Published: (2008-09-01) -
Probing the Effective Treatment Thresholds for Alteplase in Acute Ischemic Stroke With Regression Discontinuity Designs
by: Andrew M. Naidech, et al.
Published: (2020-09-01) -
Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs
by: Qu, Z., et al.
Published: (2019) -
Analysis of Policies Based on the Multi-Fuzzy Regression Discontinuity, in Terms of the Number of Deaths in the Coronavirus Epidemic
by: Xianghui Wang, et al.
Published: (2021-01-01) -
Polynomial Regressions and Nonsense Inference
by: Daniel Ventosa-Santaulària, et al.
Published: (2013-11-01)