论文标题
带有生成回归器的半参数模型的自举规范测试
A Bootstrap Specification Test for Semiparametric Models with Generated Regressors
论文作者
论文摘要
本文为具有非参数生成的回归变量的半参数模型提供了规范测试。研究人员未观察到这样的变量，而是非参数鉴定和可估计的。该测试的应用包括具有通过控制功能确定的内源回归器，半参数样品选择模型或带有不完整信息的二元游戏的模型。该统计量是由半参数模型的残差构建的。显示出一种新型的野生引导程序可提供有效的临界值。我们考虑具有自动偏置校正的非参数估计器，该估计器可实现该测试而无需平滑。在模拟中，测试表现出良好的样本表现，对妇女劳动力参与决策的应用显示了其在实际数据上下文中的实施。
This paper provides a specification test for semiparametric models with nonparametrically generated regressors. Such variables are not observed by the researcher but are nonparametrically identified and estimable. Applications of the test include models with endogenous regressors identified by control functions, semiparametric sample selection models, or binary games with incomplete information. The statistic is built from the residuals of the semiparametric model. A novel wild bootstrap procedure is shown to provide valid critical values. We consider nonparametric estimators with an automatic bias correction that makes the test implementable without undersmoothing. In simulations the test exhibits good small sample performances, and an application to women's labor force participation decisions shows its implementation in a real data context.
