Control Function Methods in Applied Econometrics
综述了控制函数方法在线性和非线性模型中解决内生解释变量问题的应用，相比最大似然法假设更少、计算更简单，并讨论了处理离散内生变量的近似方法。
This paper provides an overview of control function (CF) methods for solving the problem of endogenous explanatory variables (EEVs) in linear and nonlinear models. CF methods often can be justified in situations where “plug-in” approaches are known to produce inconsistent estimators of parameters and partial effects. Usually, CF approaches require fewer assumptions than maximum likelihood, and CF methods are computationally simpler. The recent focus on estimating average partial effects, along with theoretical results on nonparametric identification, suggests some simple, flexible parametric CF strategies. The CF approach for handling discrete EEVs in nonlinear models is more controversial but approximate solutions are available.