CONDITIONAL INFERENCE WITH A FUNCTIONAL NUISANCE PARAMETER

被引:29
作者
Andrews, Isaiah [1 ]
Mikusheva, Anna [2 ]
机构
[1] Harvard Univ, Dept Econ, Littauer Ctr 124, Cambridge, MA 02138 USA
[2] MIT, Dept Econ, 50 Mem Dr,E52-526, Cambridge, MA 02142 USA
关键词
Weak identification; similar test; conditional inference; INSTRUMENTAL VARIABLES REGRESSION; WEAK INSTRUMENTS; QUANTILE REGRESSION; MODELS; TESTS; IDENTIFICATION; GMM; INTEGRATION; ESTIMATORS; SIMULATION;
D O I
10.3982/ECTA12868
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper shows that the problem of testing hypotheses in moment condition models without any assumptions about identification may be considered as a problem of testing with an infinite-dimensional nuisance parameter. We introduce a sufficient statistic for this nuisance parameter in a Gaussian problem and propose conditional tests. These conditional tests have uniformly correct asymptotic size for a large class of models and test statistics. We apply our approach to construct tests based on quasi-likelihood ratio statistics, which we show are efficient in strongly identified models and perform well relative to existing alternatives in two examples.
引用
收藏
页码:1571 / 1612
页数:42
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