A Note on Generalized Empirical Likelihood Estimation of Semiparametric Conditional Moment Restriction Models
A Note on Generalized Empirical Likelihood Estimation of Semiparametric Conditional Moment Restriction Models
复制标题
关于半参数条件矩限制模型的广义经验似然估计的注解
DOI：
10.1017/s0266466616000360
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发表时间：
2017
影响因子：
0.8
通讯作者：
Naoya Sueishi
中科院分区：
文献类型：
--
作者：
Ｊunya Hamaaki;Masahiro Hori and Keiko Murata;Keiko Murata;Naoya Sueishi
针对含有有限维未知参数和未知函数的半参数条件矩约束模型，提出了一种基于经验似然的估计方法。我们扩展了Donald，Imbens和Newey（2003，Journal of Econometrics 117，55-93）的结果，允许未知函数包含在条件矩限制中。我们用筛法逼近未知函数，并联合估计有限维参数和未知函数。我们建立了一致性，并推导出估计的收敛速度。我们还证明了有限维参数的估计是相合的，渐近正态分布的，渐近有效的。
This paper proposes an empirical likelihood-based estimation method for semiparametric conditional moment restriction models, which contain finite dimensional unknown parameters and unknown functions. We extend the results of Donald, Imbens, and Newey (2003, Journal of Econometrics 117, 55–93) by allowing unknown functions to be included in the conditional moment restrictions. We approximate unknown functions by a sieve method and estimate the finite dimensional parameters and unknown functions jointly. We establish consistency and derive the convergence rate of the estimator. We also show that the estimator of the finite dimensional parameters is -consistent, asymptotically normally distributed, and asymptotically efficient.