SEMIPARAMETRIC EFFICIENCY FOR CENSORED LINEAR REGRESSION MODELS WITH HETEROSKEDASTIC ERRORS
利用Severini和Tripathi（2001）的简化方法，计算了异方差误差下删失线性回归模型有限维参数的半参数效率界，并基于Lewbel和Linton（2002）的结果提出了一个有效估计量，还扩展到了删失部分线性单指标模型。
Using a simplified approach developed by Severini and Tripathi (2001), we calculate the semiparametric efficiency bound for the finite-dimensional parameters of censored linear regression models with heteroskedastic errors. Under an additional identification at infinity type assumption, we propose an efficient estimator based on a novel result from Lewbel and Linton (2002). An extension to censored partially linear single-index models is also presented.