CONDITIONAL MOMENT RESTRICTIONS IN CENSORED AND TRUNCATED REGRESSION MODELS
研究了在分布未知的删失和截断回归模型中，能产生√n一致估计量的所有条件矩约束，推导了半参数效率界，并展示了如何构造达到该界的加权估计量。
Censored and truncated regression models with unknown distribution are important in econometrics. This paper characterizes the class of all conditional moment restrictions that lead to √ n -consistent estimators for these models. The semiparametric efficiency bound for each conditional moment restriction is derived. In the case of a nonzero bound it is shown how an estimator can be constructed and that an appropriately weighted version can attain the efficiency bound. These estimators also work when the disturbance is independent of the regressors. The paper discusses combining conditional moment restrictions for more efficient estimation in this case.