Weak Identification in Fuzzy Regression Discontinuity Designs

Donna Feir, Thomas Lemieux and Vadim Marmer ()

Microeconomics.ca working papers from Vancouver School of Economics

Abstract: In fuzzy regression discontinuity (FRD) designs, the treatment effect is identified through a discontinuity in the conditional probability of treatment assignment. We show that when identification is weak (i.e. when the discontinuity is of a small magnitude) the usual t-test based on the FRD estimator and its standard error suffers from asymptotic size distortions as in a standard instrumental variables setting. This problem can be especially severe in the FRD setting since only observations close to the discontinuity are useful for estimating the treatment effect. To eliminate those size distortions, we propose a modified t-statistic that uses a null-restricted version of the standard error of the FRD estimator. Simple and asymptotically valid confidence sets for the treatment effect can be also constructed using this null-restricted standard error. An extension to testing for constancy of the regression discontinuity effect across covariates is also discussed.

Keywords: Nonparametric inference; treatment effect; size distortions; Anderson-Rubin test; robust confidence set; class size effect (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 (search for similar items in EconPapers)
Pages: 50 pages
Date: 2010-05-15, Revised 2016-04-17
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (47)

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Journal Article: Weak Identification in Fuzzy Regression Discontinuity Designs (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:ubc:pmicro:vadim_marmer-2010-19

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