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

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.

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Year of publication:	1998
Authors:	DUFOUR, Jean-Marie ; KHALAF, Lynda
Institutions:	Département de Sciences Économiques, Université de Montréal

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Extent:	application/pdf
Series:	Cahiers de recherche.
Type of publication:	Book / Working Paper
Notes:	32 pages
Classification:	C20 - Econometric Methods: Single Equation Models. General ; C21 - Cross-Sectional Models; Spatial Models ; C40 - Econometric and Statistical Methods: Special Topics. General
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005729768