Inference on Local Average Treatment Effects for Misclassified Treatment

Takahide Yanagi

Papers from arXiv.org

Abstract: We develop point-identification 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. We correct the problem by identifying the distribution of the measurement error based on the use of an exogenous variable that can even be a binary covariate. The moment conditions derived from the identification lead to generalized method of moments estimation with asymptotically valid inferences. Monte Carlo simulations and an empirical illustration demonstrate the usefulness of the proposed procedure.

Date: 2018-04
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Related works:
Journal Article: Inference on local average treatment effects for misclassified treatment (2019)
Working Paper: Inference on Local Average Treatment Effects for Misclassified Treatment (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1804.03349

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