Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-24T18:17:56.220Z Has data issue: false hasContentIssue false

The Efficiency of OLS in a Seemingly Unrelated Regressions Model

Published online by Cambridge University Press:  18 October 2010

Abstract

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Other
Copyright
Copyright © Cambridge University Press 1988 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Kruskal, W. When are Gauss–Markov and least-squares estimators identical? A coordinate-free approach. The Annals of Mathematical Statistics 39 (1968): 7075.Google Scholar
2. Milliken, G.A. & Albohali, M.. On necessary and sufficient conditions for ordinary least-squares estimators to be best linear unbiased estimators. The American Statistician 38 (1984): 298299.Google Scholar
3. Phillips, P.C.B. Comment: On university education in econometrics. Econometric Reviews 2 (1983): 307315.Google Scholar
4. Zellner, A. An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of the American Statistical Association 57 (1962): 348368.10.1080/01621459.1962.10480664Google Scholar
5. Zyskind, G. On canonical forms, nonnegative covariance matrices and best simple least-squares linear estimators in linear models. The Annals of Mathematical Statistics 30 (1967): 10921109.10.1214/aoms/1177698779Google Scholar