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A New Liu Type of Estimators for the Restricted SUR Estimator
Jönköping University, Sweden.
Florida International University, USA.
Linnaeus University, School of Business and Economics, Department of Economics and Statistics. (Statistik)ORCID iD: 0000-0002-3416-5896
2019 (English)In: Journal of Modern Applied Statistical Methods, ISSN 1538-9472, Vol. 18, no 1, p. 1-11, article id eP2758Article in journal (Refereed) Published
Abstract [en]

A new Liu type of estimator for the seemingly unrelated regression (SUR) models is proposed that may be used when estimating the parameters vector in the presence of multicollinearity if the it is suspected to belong to a linear subspace. The dispersion matrices and the mean squared error (MSE) are derived. The new estimator may have a lower MSE than the traditional estimators. It was shown using simulation techniques the new shrinkage estimator outperforms the commonly used estimators in the presence of multicollinearity.

Place, publisher, year, edition, pages
JMASM Inc. , 2019. Vol. 18, no 1, p. 1-11, article id eP2758
National Category
Probability Theory and Statistics
Research subject
Economy, Economics; Statistics/Econometrics
Identifiers
URN: urn:nbn:se:lnu:diva-71217DOI: 10.22237/jmasm/1556669340ISI: 000605728200011Scopus ID: 2-s2.0-85087077190OAI: oai:DiVA.org:lnu-71217DiVA, id: diva2:1186961
Available from: 2018-03-01 Created: 2018-03-01 Last updated: 2021-02-02Bibliographically approved

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Shukur, Ghazi

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