非参数统计
估计员
计量经济学
参数统计
控制功能
非线性系统
鉴定(生物学)
数学优化
简单(哲学)
似然函数
数学
控制(管理)
统计
计算机科学
应用数学
功能(生物学)
估计理论
人工智能
物理
哲学
植物
量子力学
认识论
进化生物学
生物
摘要
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.
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