Unbiased Least-Squares Modelling

Marta Gatto and Fabio Marcuzzi
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Marta Gatto: Department of Mathematics, “Tullio Levi Civita”, University of Padova, Via Trieste 63, 35131 Padova, Italy
Fabio Marcuzzi: Department of Mathematics, “Tullio Levi Civita”, University of Padova, Via Trieste 63, 35131 Padova, Italy

Mathematics, 2020, vol. 8, issue 6, 1-19

Abstract: In this paper we analyze the bias in a general linear least-squares parameter estimation problem, when it is caused by deterministic variables that have not been included in the model. We propose a method to substantially reduce this bias, under the hypothesis that some a-priori information on the magnitude of the modelled and unmodelled components of the model is known. We call this method Unbiased Least-Squares (ULS) parameter estimation and present here its essential properties and some numerical results on an applied example.

Keywords: parameter estimation; physical modelling; oblique decomposition; least-squares (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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