This work proves that inferences on parameter vectors based on moment inequalities typically used in linear models with outcome censoring are sharp, i.e., they exhaust all the information in the data and the model. This holds for fixed and randomly censored linear models under median...

We observe a dependent variable and some regressors, including a mismeasured binary regressor. We provide identification of the nonparametric regression model containing this misclassified dichotomous regressor. We obtain identification without parameterizations or instruments, by assuming the...