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Weaker MSE criteria and tests for linear restrictions in regression models with non-spherical disturbances

Publication ,  Journal Article
McElroy, MB
Published in: Journal of Econometrics
January 1, 1977

This paper extend, in an asymptotic sense, the strong and the weaker mean square error criteria and corresponding tests to linear models with non-spherical disturbances where the error covariance matrix is unknown but a consistent estimator for it is available. The mean square error tests of Toro-Vizcorrondo and Wallace (1968) and Wallace (1972) test for the superiority of restricted over unrestricted linear estimators in a least squares context. This generalization of these tests makes them available for use with GLS, Zellner's SUR, 2SLS, 3SLS, tests of over identification, and so forth. © 1977.

Duke Scholars

Published In

Journal of Econometrics

DOI

ISSN

0304-4076

Publication Date

January 1, 1977

Volume

6

Issue

3

Start / End Page

389 / 394

Related Subject Headings

  • Econometrics
  • 1403 Econometrics
  • 1402 Applied Economics
  • 0104 Statistics
 

Citation

APA
Chicago
ICMJE
MLA
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McElroy, M. B. (1977). Weaker MSE criteria and tests for linear restrictions in regression models with non-spherical disturbances. Journal of Econometrics, 6(3), 389–394. https://doi.org/10.1016/0304-4076(77)90009-4
McElroy, M. B. “Weaker MSE criteria and tests for linear restrictions in regression models with non-spherical disturbances.” Journal of Econometrics 6, no. 3 (January 1, 1977): 389–94. https://doi.org/10.1016/0304-4076(77)90009-4.
McElroy, M. B. “Weaker MSE criteria and tests for linear restrictions in regression models with non-spherical disturbances.” Journal of Econometrics, vol. 6, no. 3, Jan. 1977, pp. 389–94. Scopus, doi:10.1016/0304-4076(77)90009-4.
Journal cover image

Published In

Journal of Econometrics

DOI

ISSN

0304-4076

Publication Date

January 1, 1977

Volume

6

Issue

3

Start / End Page

389 / 394

Related Subject Headings

  • Econometrics
  • 1403 Econometrics
  • 1402 Applied Economics
  • 0104 Statistics