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One-sided tests for independence of seemingly unrelated regression equations


  • Kurata, Hiroshi


In 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.

Suggested Citation

  • Kurata, Hiroshi, 2004. "One-sided tests for independence of seemingly unrelated regression equations," Journal of Multivariate Analysis, Elsevier, vol. 90(2), pages 393-406, August.
  • Handle: RePEc:eee:jmvana:v:90:y:2004:i:2:p:393-406

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    References listed on IDEAS

    1. Maxwell King & Ping Wu, 1997. "Locally optimal one-sided tests for multiparameter hypotheses," Econometric Reviews, Taylor & Francis Journals, vol. 16(2), pages 131-156.
    2. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," Review of Economic Studies, Oxford University Press, vol. 47(1), pages 239-253.
    3. 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.
    4. 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.
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