A Small-Sample Estimator for the Sample-Selection Model
提出一种基于广义最大熵的半参数估计量，用于处理样本选择过程生成的数据，在小样本和病态样本中表现良好，并与参数和半参数估计量进行了理论和抽样比较。
Abstract A semiparametric estimator for evaluating the parameters of data generated under a sample selection process is developed. This estimator is based on the generalized maximum entropy estimator and performs well for small and ill-posed samples. Theoretical and sampling comparisons with parametric and semiparametric estimators are given. This method and standard ones are applied to three small-sample empirical applications of the wage-participation model for female teenage heads of households, immigrants, and Native Americans.