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A new liu type of estimator for the restricted SUR estimator
Jönköping University, Jönköping International Business School, JIBS, Statistics.ORCID iD: 0000-0002-4535-3630
Florida International University, Miami, FL, United States.
Linnæus University, Växjö, Sweden.
2019 (English)In: Journal of Modern Applied Statistical Methods, ISSN 1538-9472, Vol. 18, no 1, article id 9340Article 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
Wayne State University Press, 2019. Vol. 18, no 1, article id 9340
Keywords [en]
Estimation, Liu, MSE, Multicollinearity, Simulation, SUR
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:hj:diva-50233DOI: 10.22237/JMASM/1556669340Scopus ID: 2-s2.0-85087077190Local ID: POA;intsam;1458226OAI: oai:DiVA.org:hj-50233DiVA, id: diva2:1458226
Available from: 2020-08-14 Created: 2020-08-14 Last updated: 2021-02-26Bibliographically approved

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Månsson, Kristofer

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