Estimating Models with Sample Selection Bias: A Survey
综述了估计存在样本选择偏差的模型的方法，从Heckman（1979）的完全参数模型出发，探讨放松分布假设的半参数方法，以及处理不同选择规则和面板数据扩展。
This paper surveys the available methods for estimating models with sample selection bias. I initially examine the fully parameterized model proposed by Heckman (1979) before investigating departures in two directions. First, I consider the relaxation of distributional assumptions. In doing so I present the available semi-parametric procedures. Second, I investigate the ability to tackle different selection rules generating the selection bias. Finally, I discuss how the estimation procedures applied in the cross-sectional case can be extended to panel data.