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Empirical likelihood for regression discontinuity design

Otsu, Taisuke and Xu, Ke-Li and Matsushita, Yukitoshi (2015) Empirical likelihood for regression discontinuity design. Journal of Econometrics, 186 (1). pp. 94-112. ISSN 0304-4076

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Identification Number: 10.1016/j.jeconom.2014.04.023

Abstract

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.

Item Type: Article
Official URL: http://www.journals.elsevier.com/journal-of-econom...
Additional Information: © 2014 Elsevier B.V.
Subjects: H Social Sciences > HC Economic History and Conditions
JEL classification: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C12 - Hypothesis Testing
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods
C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C21 - Cross-Sectional Models; Spatial Models; Treatment Effect Models
Sets: Collections > Economists Online
Date Deposited: 08 Aug 2014 11:21
Last Modified: 26 Jun 2016 23:00
URI: http://eprints.lse.ac.uk/id/eprint/58513

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