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Local Polynomial Order in Regression Discontinuity Designs
Title / Series / Name
Journal of Business and Economic Statistics
Publication Volume
40
Publication Issue
3
Pages
Editors
Keywords
Local polynomial estimation
Polynomial order
Regression discontinuity design
Regression kink design
Statistics and Probability
Social Sciences (miscellaneous)
Economics and Econometrics
Statistics, Probability and Uncertainty
Polynomial order
Regression discontinuity design
Regression kink design
Statistics and Probability
Social Sciences (miscellaneous)
Economics and Econometrics
Statistics, Probability and Uncertainty
URI
https://hdl.handle.net/20.500.14018/28179
Abstract
Treatment effect estimates in regression discontinuity (RD) designs are often sensitive to the choice of bandwidth and polynomial order, the two important ingredients of widely used local regression methods. While Imbens and Kalyanaraman and Calonico, Cattaneo, and Titiunik provided guidance on bandwidth, the sensitivity to polynomial order still poses a conundrum to RD practitioners. It is understood in the econometric literature that applying the argument of bias reduction does not help resolve this conundrum, since it would always lead to preferring higher orders. We therefore extend the frameworks of Imbens and Kalyanaraman and Calonico, Cattaneo, and Titiunik and use the asymptotic mean squared error of the local regression RD estimator as the criterion to guide polynomial order selection. We show in Monte Carlo simulations that the proposed order selection procedure performs well, particularly in large sample sizes typically found in empirical RD applications. This procedure extends easily to fuzzy regression discontinuity and regression kink designs.
Topic
Publisher
Place of Publication
Type
Journal article
Date
2022
Language
ISBN
Identifiers
10.1080/07350015.2021.1920961