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Simulation-Based Finite and Large Sample Tests in Multivariate Regressions

  • Dufour, J.M.
  • Khalaf, L.

In the context of multivariate linear regression (MLR) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. In this paper, we propose a general method for constructing exact tests of possibly nonlinear hypotheses on the coefficients of MLR systems.

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Paper provided by Centre interuniversitaire de recherche en économie quantitative, CIREQ in its series Cahiers de recherche with number 2000-10.

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Length: 24 pages
Date of creation: 2000
Date of revision:
Handle: RePEc:mtl:montec:2000-10
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  25. DUFOUR, Jean-Marie & FARHAT, Abdeljelil & GARDIOL, Lucien, 1998. "Simulation-Based Finite-Sample Normality Tests in Linear Regressions," Cahiers de recherche 9811, Universite de Montreal, Departement de sciences economiques.
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