IDENTIFICATION OF THE BINARY CHOICE MODEL WITH MISCLASSIFICATION
证明了当因变量存在误分类时，即使误分类概率以未知方式依赖于协变量且误差分布未知，二元选择模型仍可被半参数识别。
Misclassification in binary choice (binomial response) models occurs when the 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 identified, even when the probabilities of misclassification depend in unknown ways on model covariates and the distribution of the errors is unknown.