AI 中文总结
研究针对内生回归中结构误差条件均值函数提出半参数投影（SP）方法解决内生性，适用于多种回归模型，建立识别条件和渐近性质，并用LASSO选择方法检验有限样本性能。
AI 中文摘要
本文提出对内生回归中给定回归变量的结构误差条件均值函数进行投影和扩展。由于投影过程是半参数的，我们将此过程定义为半参数投影（SP）方法，通过内部构造工具变量来解决回归模型中的内生性问题。SP方法适用于许多与内生性相关的回归模型，如线性、非线性、非参数和半参数模型。本文建立了识别条件并推导了估计量的渐近性质，还提出一种简单的LASSO选择方法，通过模拟和实际数据示例检验所提方法和既定理论的有限样本性能。
英文摘要
This paper proposes to project and expand the conditional mean function of the structural error given the regressors in an endogenous regression under consideration. As the projection process is semiparametric, we define this procedure as a semiparametric projection (SP) method to address endogeneity in regression models by internally constructed instrumental variables. The SP method is applicable to many classes of regression models associated with endogeneity, such as linear, nonlinear, and non- and semi-parametric models, and provides a simple and computationally tractable alternative to conventional instrumental variable approaches available from the existing literature. This paper establishes identification conditions and derives the asymptotic properties of the resulting estimators. It then proposes a simple LASSO selection method to examine the finite-sample performance of both the proposed method and the established theory by simulated and real data examples.
