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Misclassification of a binary response variable and nonrandom sample selection are data issues frequently encountered by empirical researchers. For cases in which both issues feature simultaneously in a data set, we formulate a sample selection model for a misclassified binary outcome in which...
Persistent link: https://www.econbiz.de/10013355238
misclassification and, for some sampling units, neither the error-prone variable of interest nor the covariates are recorded. A model to …
Persistent link: https://www.econbiz.de/10004990273
This chapter overviews the recent progress towards the identification and the estimation of models in which some of the variables are either imperfectly measured or even entirely unobserved, with a special focus on models with nonlinear, nonparametric, nonclassical or nonseparable features....
Persistent link: https://www.econbiz.de/10014024926
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Participation in social programs is often misreported in survey data, complicating the estimation of the effects of those programs. In this paper, we propose a model to estimate treatment effects under endogenous participation and endogenous misreporting. We show that failure to account for...
Persistent link: https://www.econbiz.de/10011820585
We assess the role of measurement error in minimum wage evaluations when the treatment variable - the bite - is inferred from a survey wage distribution. We conduct Monte Carlo experiments on both simulated and empirical distributions of measurement error derived from a record linkage of survey...
Persistent link: https://www.econbiz.de/10012199458
Estimators that exploit an instrumental variable to correct for misclassification in a binary regressor typically assume that the misclassification rates are invariant across all values of the instrument. We show that this assumption is invalid in routine empirical settings. We derive a new...
Persistent link: https://www.econbiz.de/10012266298
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