SEMIPARAMETRIC ESTIMATION WITH GENERATED COVARIATES

被引:25
|
作者
Mammen, Enno [1 ,2 ]
Rothe, Christoph [3 ]
Schienle, Melanie [4 ]
机构
[1] Heidelberg Univ, Bergheimer Str 58, D-69115 Heidelberg, Germany
[2] Natl Res Univ, Higher Sch Econ, Moscow, Russia
[3] Columbia Univ, New York, NY 10027 USA
[4] Karlsruhe Inst Technol, D-76021 Karlsruhe, Germany
关键词
PROPENSITY SCORE; NONPARAMETRIC-ESTIMATION; EFFICIENT ESTIMATION; ASYMPTOTIC VARIANCE; UNIFORM-CONVERGENCE; ECONOMETRIC-MODELS; SERIES ESTIMATORS; DEPENDENT DATA; REGRESSORS; VARIABLES;
D O I
10.1017/S0266466615000134
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
收藏
页码:1140 / 1177
页数:38
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