SEMIPARAMETRIC ESTIMATION WITH GENERATED COVARIATES
SEMIPARAMETRIC ESTIMATION WITH GENERATED COVARIATES
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DOI：
10.1017/s0266466615000134
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发表时间：
2015-06
影响因子：
0.8
通讯作者：
E. Mammen;C. Rothe;M. Schienle
中科院分区：
文献类型：
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作者：
E. Mammen;C. Rothe;M. Schienle
我们研究了一般类的半参数估计时，无限维的滋扰参数包括一个条件期望函数，已估计非参数使用生成的协变量。这种估计器经常用于例如，当使用控制变量技术实现识别时，估计具有内生协变量的非线性模型。我们研究了这类估计的渐近性质，这是一个非标准的问题，由于生成的协变量的存在。我们给出的条件下，估计是根-n一致的和渐近正态的，推导出一个一般公式的渐近方差，并显示如何建立有效的自助。
We study a general class of semiparametric estimators when the infinite-dimensional nuisance parameters include a conditional expectation function that has been estimated nonparametrically using generated covariates. Such estimators are used frequently to e.g., estimate nonlinear models with endogenous covariates when identification is achieved using control variable techniques. We study the asymptotic properties of estimators in this class, which is a nonstandard problem due to the presence of generated covariates. We give conditions under which estimators are root-n consistent and asymptotically normal, derive a general formula for the asymptotic variance, and show how to establish validity of the bootstrap.