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Treatment effect estimation with covariate measurement error

Authors: Erich Battistin and Andrew Chesher
Date: 28 February 2014
Type: Journal article, Journal of Econometrics, Vol. 178, No. 2, pp. 707--715
DOI: 10.1016/j.jeconom.2013.10.010


This paper investigates the effect that covariate measurement error has on a treatment effect analysis built on an unconfoundedness restriction in which there is conditioning on error free covariates. The approach uses small parameter asymptotic methods to obtain the approximate effects of measurement error for estimators of average treatment effects. The approximations can be estimated using data on observed outcomes, the treatment indicator and error contaminated covariates without employing additional information from validation data or instrumental variables. The results can be used in a sensitivity analysis to probe the potential effects of measurement error on the evaluation of treatment effects.

Previous version:
Erich Battistin and Andrew Chesher September 2009, Treatment effect estimation with covariate measurement error, cemmap Working Paper

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