Estimation of Average Treatment Effects With Misclassification

By Arthur Lewbel. 2007

202 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/207cc9ef56e5ff924da95b2ae689e7a12962e7d6

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In Statistics and Probability

Citations in the corpus

Two-Constraints Models of Consumer Demand: An Application to the Demand for Agritourism in the United States (2006, background): “Also, Lewbel (2007) has shown that measurement error in binary regressors (dummy variables) causes attenuation bias, analogous to the attenuation bias of classically mismeasured variables in linear regression models.”
Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution (2008, unknown): “Kane et al. (1999) and Lewbel (2007) also use instruments to solve misclassification in treatment effect models.”
In a Small Moment: Class Size and Moral Hazard in the Italian Mezzogiorno (2016, unknown): “Similar results for the consequences of classification error under the same assumptions appear in Kane et al. (1999), Mahajan (2006), and Lewbel (2007), among others, though our work focuses on the consequences for the coefficient on a variable subject to error rather than implications for other…”
A local generalized method of moments estimator (2007, background): “Another application is Lewbel (2006), who provides examples of a treatment model that generates conditional moments in the form of equation (1).”
Imputation Rules to Improve the Education Variable in the IAB Employment Subsample (2005, background): “Lewbel (2003) gives necessary assumptions to estimate average treatment effects when treatment is misclassified. Again, these conditions are unlikely to hold in our context. Multiple imputation methods are concerned with the problem of missing data.(1) Gartner and Rässler (2005) apply multiple imput”
The Elephant in the Corner: A Cautionary Tale About Measurement Error in Treatment Effects Models (2010, background): “Point identi cation is possible in a Generalized Method of Moments (GMM) framework, as discussed in Black et al. (2000), Bound et al. (2001), and Lewbel (2007).”
On the estimation of treatment effects with endogenous misreporting (2016, unknown): “1 While earlier papers (Aigner, 1973; Lewbel, 2007) show that exogenous misreporting leads to attenuation bias, we demonstrate that the effects of endogenous misreporting aremuch more severe.”