A Non-Parametric Test of Exogeneity
提出一种外生性检验方法，不需要辅助假设，基于条件矩约束识别非参数函数g，并检验g是否等于Y给定X的条件均值，通过蒙特卡洛实验和消费者扩展路径应用展示其有效性。
This paper presents a test for exogeneity of explanatory variables that minimizes the need for auxiliary assumptions that are not required by the definition of exogeneity. It concerns inference about a non-parametric function g that is identified by a conditional moment restriction involving instrumental variables (IV). A test of the hypothesis that g is the mean of a random variable Y conditional on a covariate X is developed that is not subject to the ill-posed inverse problem of non-parametric IV estimation. The test is consistent whenever g differs from E (Y ∣ X) on a set of non-zero probability. The usefulness of this new exogeneity test is displayed through Monte Carlo experiments and an application to estimation of non-parametric consumer expansion paths. Copyright 2007, Wiley-Blackwell.