Distribution-Free Maximum Likelihood Estimator of the Binary Choice Model
提出一种无需假设分布函数形式的二元选择模型参数估计方法，证明估计量的一致性，并同时一致估计分布函数，适用于外生变量与未知参数的系统效用差建模。
is a given function of the exogenous variables z and unknown parameters 9, representing the systematic component of the utility difference, and F is the distribution function of the random component of the utility difference. This paper describes a method of estimating the parameters 9 without assuming any functional form for the distribution function F, and proves that this estimator is consistent. F is also consistently estimated. The method uses maximum likelihood estimation in which the likelihood is maximized not only over the parameter 9 but also over a space which contains all distribution functions.