One-sided tests for independence of seemingly unrelated regression equations
AbstractIn a seemingly unrelated regression model with p([greater-or-equal, slanted]2) equations, this paper considers the problem of testing independence of equations against a one-sided alternative hypothesis. The power functions of invariant tests are evaluated and the locally most mean powerful invariant test is obtained.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Multivariate Analysis.
Volume (Year): 90 (2004)
Issue (Month): 2 (August)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Kurata, Hiroshi, 1999. "On the Efficiencies of Several Generalized Least Squares Estimators in a Seemingly Unrelated Regression Model and a Heteroscedastic Model," Journal of Multivariate Analysis, Elsevier, vol. 70(1), pages 86-94, July.
- Breusch, T S & Pagan, A R, 1980. "The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 239-53, January.
- Maxwell King & Ping Wu, 1997. "Locally optimal one-sided tests for multiparameter hypotheses," Econometric Reviews, Taylor and Francis Journals, vol. 16(2), pages 131-156.
- Kariya, Takeaki & Fujikoshi, Yasunori & Krishnaiah, P. R., 1984. "Tests for independence of two multivariate regression equations with different design matrices," Journal of Multivariate Analysis, Elsevier, vol. 15(3), pages 383-407, December.
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