A NEW PROJECTION-TYPE SPLIT-SAMPLE SCORE TEST IN LINEAR INSTRUMENTAL VARIABLES REGRESSION
提出一种新的投影型推断方法，用于线性工具变量回归模型中结构系数子集的两阶段最小二乘分裂样本推断，既能防止过度拒绝真实参数值，又能减少传统投影方法的保守性。
In this paper we introduce a new method of projection-type inference and describe it in the context of two stage least squares–based split-sample inference on subsets of structural coefficients in a linear instrumental variables regression model. The use of the new method not only guards against the uncontrolled overrejection of the true value of the parameters of interest but also reduces the conservativeness of the usual method of projection proposed by Dufour and his coauthors (Dufour, 1997, Econometrica 65, 1365–1388; Dufour and Jasiak, 2001, International Economic Review 41, 815–843; Dufour and Taamouti, 2005, discussion paper; Dufour and Taamouti, 2005, Econometrica 73, 1351–1365; Dufour and Taamouti, 2007, Journal of Econometrics 139, 133–153).