CONSISTENT MOMENT ESTIMATORS OF REGRESSION-COEFFICIENTS IN THE PRESENCE OF ERRORS IN VARIABLES
CONSISTENT MOMENT ESTIMATORS OF REGRESSION-COEFFICIENTS IN THE PRESENCE OF ERRORS IN VARIABLES
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DOI：
10.1016/0304-4076(80)90032-9
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发表时间：
1980-01-01
影响因子：
6.3
通讯作者：
PAL, M
中科院分区：
文献类型：
--
作者：
PAL, M
本文研究Geary（1942）等[Scott（1950）和Drion（1951）]提出的变量含误差问题中回归系数矩估计的可能性。这种方法基于三阶或更高阶的单变量和双变量矩（或累积量）产生回归系数的一致估计。这些方法在计算上很简单，并且需要比标准方法更温和的假设，ML和IV估计。在回顾过去的调查，本文提出了新的矩估计，并比较了六个估计的渐近效率提出之前或这里和OLS估计。真实回归量服从对数正态分布的情况在本文中受到了相当大的关注。
This paper examines the possibilities of moment estimators of regression coefficients in the errors-in-variables problem suggested by Geary (1942) and others [Scott (1950) and Drion (1951)]. This approach yields consistent estimators of regression coefficients based on uni- and bi-variate moments (or cumulants) of third or higher order. These are computationally simple and need milder assumptions than the standard techniques, viz., ML and IV estimation. After a review of past investigations, this paper proposes new moment estimators and compares the asymptotic efficiencies of six estimators proposed earlier or here and of the OLS estimator. The case where the true regressor is lognormally distributed receives considerable attention in this communication.