A Maximal Extension of the Gauss-Markov Theorem and its Nonlinear Version

Takeaki Kariya and Hiroshi Kurata

Discussion Paper Series from Institute of Economic Research, Hitotsubashi University

Abstract: In this paper, first we make a maximal extension of the well known gauss-Markov Theorem (GMT) in its linear framework. In particular, the maximal class of distributions of error term for which teh GMT holds is derived.Second, we establish a nonlinear version of the maximal GMT and describe some interesting families of distributions of error term for which the nonlinear GMT holds.

Keywords: Gauss-Markov Theorem; Nonlinear Gauss-Markov Theorem; equivariant estimator in regression; elliptically symmetric distribution. (search for similar items in EconPapers)
Date: 1998-04
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Persistent link: https://EconPapers.repec.org/RePEc:hit:hituec:a350

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