Treatment effect estimation with covariate measurement error

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 measureme...

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Veröffentlicht in:Journal of econometrics 2014-02, Vol.178 (2), p.707-715
Hauptverfasser: Battistin, Erich, Chesher, Andrew
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description 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.
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source Elsevier ScienceDirect Journals Complete - AutoHoldings
subjects Approximation
Asymptotic methods
Econometrics
Measurement error
Measurement errors
Parameter asymptotics
Potential outcomes
Sensitivity analysis
Studies
Treatment effects
title Treatment effect estimation with covariate measurement error
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