テクニカルレポート Inference on Local Average Treatment Effects for Misclassified Treatment

YANAGI, Takahide

2017-02-21 , Graduate School of Economics, Hitotsubashi University
内容記述
This version: February 21, 2017 First version: January 27, 2017
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.
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http://hermes-ir.lib.hit-u.ac.jp/rs/bitstream/10086/28337/1/070econDP17-02.pdf

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