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Identifier to cite or link to this item: https://hdl.handle.net/10086/28337

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Title
Inference on Local Average Treatment Effects for Misclassified Treatment
Creator
Creator Name
YANAGI, Takahide YANAGI, Takahide
柳, 貴英 柳, 貴英
Affiliation
Affiliation Name
Hitotsubashi University
Key Word
misclassification
instrumental variable
non-differential measurement error
nonparametric method
causal inference
JEL
C14
C21
C25
Abstract (distribution restricted)
We develop point-identification and inference methods for the local average treatment effect when the binary treatment contains a measurement error. The standard instrumental variable estimator is inconsistent for the parameter since the measurement error is non-classical by construction. Our proposed analysis corrects the problem by identifying the distribution of the measurement error based on the use of an exogenous variable such as a covariate or instrument. The moment conditions derived from the identification lead to the generalized method of moments estimation with asymptotically valid inferences. Monte Carlo simulations demonstrate the desirable finite sample performance of the proposed procedure.
Description
This version: February 21, 2017 First version: January 27, 2017
Publisher
Graduate School of Economics, Hitotsubashi University
Issued Date
2017-02-21
Language
English(eng)
Resource Type
technical report
Version Type
VoR
Is Part OfRelation -
Related Title
Discussion papers ; No. 2017-02
Number of Pages
39
Appears in Collections
Discussion papers / Graduate School of Economics, Hitotsubashi University
URL
https://hdl.handle.net/10086/28337