Identification and Estimation of Dichotomous Latent Variables Models Using Panel Data
探讨了二元选择测量误差模型的识别条件，给出了解释变量无界时最大似然估计的一致性和渐近正态性条件，并提出了简化计算的两步或三步估计法。
Identification conditions for binary choice errors-in-variables models are explored. Conditions for the consistency and asymptotic normality of the maximum likelihood estimators of binary choice models with unbounded explanatory variables are given. Two- or three-step estimators to simplify computation are also suggested.