Semiparametric Analysis Of Random Effects Linear Models From Binary Panel Data
证明，在二元面板数据中，即使扰动项仅满足时间平稳且支撑无界，只要解释变量随时间充分变化，仍可通过条件最大得分估计量一致估计随机效应线性模型的参数（至多相差一个比例常数）。
Andersen (1970) considered the problem of inference on random effects linear models from binary response panel data. He showed that inference is possible if the disturbances for each panel member are known to be white noise with the logistic distribution and if the observed explanatory variables vary over time. A conditional maximum likelihood estimator consistently estimates the model parameters up to scale. The present note shows that inference remains possible if the disturbances for each panel member are known only to be time-stationary with unbounded support and if the explanatory variables vary enough over time. A conditional version of the maximum score estimator (Manski, 1975, 1985) consistently estimates the model parameters up to scale.