ESTIMATION OF THE COVARIANCE-MATRIX OF THE LEAST-SQUARES REGRESSION-COEFFICIENTS WHEN THE DISTURBANCE COVARIANCE-MATRIX IS OF UNKNOWN FORM

被引：15

作者：

KEENER, RW ^{[1
]}

KMENTA, J ^{[1
]}

WEBER, NC ^{[1
]}

机构：

[1] UNIV SYDNEY,SYDNEY,NSW 2006,AUSTRALIA

来源：

ECONOMETRIC THEORY | 1991年 / 7卷 / 01期

关键词：

D O I：

10.1017/S0266466600004229

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper deals with the problem of estimating the covariance matrix of the least-squares regression coefficients under heteroskedasticity and/or autocorrelation of unknown form. We consider an estimator proposed by White [17] and give a relatively simple proof of its consistency. Our proof is based on more easily verifiable conditions than those of White. An alternative estimator with improved small sample properties is also presented. © 1991, Cambridge University Press. All rights reserved.

引用

页码：22 / 45

页数：24

共 19 条

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[2]

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[3]

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[4] MORE EFFICIENT ESTIMATION IN THE PRESENCE OF HETEROSCEDASTICITY OF UNKNOWN FORM [J].