Semiparametric Estimation of the Intercept of a Sample Selection Model
提出一种半参数样本选择模型中截距项的一致且渐近正态估计量，该估计量随样本量增大仅使用递减的小部分观测值，对估计工资差距、分解社会经济群体差异及评估社会项目净收益有重要应用。
This paper provides a consistent and asymptotically normal estimator for the intercept of a semiparametrically estimated sample selection model. The estimator uses a decreasingly small fraction of all observations as the sample size goes to infinity, as in Heckman (1990). In the semiparametrics literature, estimation of the intercept has typically been subsumed in the nonparametric sample selection bias correction term. The estimation of the intercept, however, is important from an economic perspective. For instance, it permits one to determine the "wage gap" between unionized and nonunionized workers, decompose the wage differential between different socioeconomic groups (e.g. male-female and black-white), and evaluate the net benefits of a social programme.