Empirical likelihood for regression discontinuity design

Taisuke Otsu, Ke Li Xu, Yukitoshi Matsushita

研究成果: Article査読

13 被引用数 (Scopus)

抄録

This paper proposes empirical likelihood based inference methods for causal effects identified from regression discontinuity designs. We consider both the sharp and fuzzy regression discontinuity designs and treat the regression functions as nonparametric. The proposed inference procedures do not require asymptotic variance estimation and the confidence sets have natural shapes, unlike the conventional Wald-type method. These features are illustrated by simulations and an empirical example which evaluates the effect of class size on pupils' scholastic achievements. Furthermore, for the sharp regression discontinuity design, we show that the empirical likelihood statistic admits a higher-order refinement, so-called the Bartlett correction. Bandwidth selection methods are also discussed.

本文言語English
ページ(範囲)94-112
ページ数19
ジャーナルJournal of Econometrics
186
1
DOI
出版ステータスPublished - 2015 5 1
外部発表はい

ASJC Scopus subject areas

  • Economics and Econometrics

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