这是个有趣的问题，请参考 What is the difference between “endogeneity” and “sample selection bias”?，特别是 Model III. Endogeneity and sample selection。

好的！谢谢黄老师~

黄老师您好！我在这个帖子里也看到了相似的问题，http://www.statalist.org/forums/forum/general-stata-discussion/general/1295287-heckman-sample-selection-and-instrumental-variable-iv-or-simultaneous-equations-model?winzoom=1。根据伍德里奇的回答，可以把heckman传统的两步法进行改进：第一步使用probit模型，以所有的外生控制变量和内生变量的工具变量为解释变量，以是否工作为被解释变量来进行回归，并估计出每个个体是否工作的预测值；第二步使用该预测值计算IMR，具体等于该预测值的标准正态分布的密度函数值比累计分布函数值的相反数；第三步将IMR作为控制变量加入本来要进行的收入的回归中，并采取2SLS回归。这些步骤都没有问题，不过他提醒说The standard errors are incorrect if the coefficient on IMR is not zero (in the population). Bootstrapping the entire procedure is not very difficult。我知道直接使用系数的标准差和显著性都没有意义，他这边的处理方法我不太懂，请问您了解吗？

不知道什么原因，我看不到 Wooldridge 之回答内容，当然，他是这领域的大牛，他讲的大概是不会错的！

啊！我有时候也打不开，好像是浏览器的问题。他的回答如下：
22 May 2015, 16:43
I cover this in Section 19.6.2 in the second edition of "Econometric Analysis of Cross Section and Panel Data," MIT Press, 2010. You are on the right track, but here are the specifics.

1. Estimate a probit model for the selection indicator, I. Include all exogenous variables: Those in the equation for Y1, the instrument(s) for Y2, and the variable determining selection. To be convincing, you should argue that you have two sources of exogenous variation excluded from the equation for Y1. Call these Z2 and Z0.
Code:
probit I Xb Xc Z2 Z0
2. Obtain the inverse Mills ratios from step 1 -- say IMR.
(code omitted)
3. Estimate the structural equation by 2SLS:

Code:
ivregress 2sls Y1 Xb Xc IMR (Y2 = Z2)
Note that the IMR, depending only on exogenous variables, acts as its own IV.

The standard errors are incorrect if the coefficient on IMR is not zero (in the population). Bootstrapping the entire procedure is not very difficult.

I hope this helps. JW

我想请教的是他所说的Bootstrapping the entire procedure ，就是简单的在回归后面加上 vce(bootstrap)或类似的处理吗？