Simulation-Based Finite-and Large-sample Inference Methods in Multivariate Regressions and Seemingly Unrelated Regressions

Jean-Marie Dufour () and Lynda Khalaf ()

Cahiers de recherche from Universite de Montreal, Departement de sciences economiques

Abstract: In the context of multivariate regression (MLR) and seemingly unrelated regressions (SURE) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. in this paper, we propose finite-and large-sample likelihood-based test procedures for possibly non-linear hypotheses on the coefficients of MLR and SURE systems.

JEL-codes: C20 C21 C40 (search for similar items in EconPapers)
Date: Written 1998
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Persistent link: http://EconPapers.repec.org/RePEc:mtl:montde:9813

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