VALIDITY OF SUBSAMPLING AND "PLUG-IN ASYMPTOTIC" INFERENCE FOR PARAMETERS DEFINED BY MOMENT INEQUALITIES

被引:99
作者
Andrews, Donald W. K. [1 ]
Guggenberger, Patrik [2 ]
机构
[1] Yale Univ, Dept Econ, Cowles Fdn Res Econ, New Haven, CT 06520 USA
[2] Univ Calif Los Angeles, Los Angeles, CA 90024 USA
基金
美国国家科学基金会;
关键词
EMPIRICAL LIKELIHOOD ESTIMATORS; PARTIALLY IDENTIFIED PARAMETERS; CONFIDENCE-REGIONS; ECONOMETRIC-MODELS; GENERALIZED-METHOD; DYNAMIC-MODELS; SELECTION; SETS;
D O I
10.1017/S0266466608090257
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper considers inference for parameters defined by moment inequalities and equalities. The parameters need not be identified. Fora specified class of test statistics, this paper establishes the uniform asymptotic validity Of subsampling, m out of n bootstrap, and "plug-in asymptotic" tests and confidence intervals for such parameters. Establishing uniform asymptotic validity is crucial ill moment inequality problems because the pointwise asymptotic distributions of the test statistics of interest have discontinuities as functions of the true distribution that generates the observations. The size results are quite general because they hold without specifying the particular form of the moment conditions-only 2 + delta moments finite are required. The results allow for independent and identically distributed (i.i.d.) and dependent observations and for preliminary consistent estimation of identified parameters.
引用
收藏
页码:669 / 709
页数:41
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