Identification of the binary choice model with misclassification

Misclassification in binary choice (binomial response) models occurs when t he dependent variable is measured with error, that is, when an actual "one" response is sometimes recorded as a zero and vice versa. This paper shows that binary response models with misclassification are semiparametrically i dentified, even when the probabilities of misclassification depend in unkno wn ways on model covariates and the distribution of the errors is unknown.