Estimators for Seemingly Unrelated Regression Equations: Some Exact Finite Sample Results
作者:
Arnold Zellner,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1963)
卷期:
Volume 58,
issue 304
页码: 977-992
ISSN:0162-1459
年代: 1963
DOI:10.1080/01621459.1963.10480681
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
The finite sample properties of an asymptotically efficient technique (JASA, June, 1962) for estimating coefficients in certain generally encountered sets of regression equations are studied in this paper. In particular, exact first and second moments of the asymptotically efficient coefficient estimator are derived and compared with those of the usual least squares estimator. Further, the exact probability density function of the new estimator is derived and studied as a function of sample size. It is found that the approach to asymptotic normality is fairly rapid and that for a wide range of conditions an appreciable part of the asymptotic gain in efficiency is realized in samples of finite size.
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