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Modified Ridge Parameters for Seemingly Unrelated Regression Model
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.ORCID iD: 0000-0003-2733-4441
Department of Mathematics and Statistics, Florida International University, Miami, USA.
2012 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 41, no 9, p. 1675-1691Article in journal (Refereed) Published
Abstract [en]

In this article, we modify a number of new biased estimators of seemingly unrelated regression (SUR) parameters which are developed by Alkhamisi and Shukur (2008), AS, when the explanatory variables are affected by multicollinearity. Nine estimators of the ridge parameters have been modified and compared in terms of the trace mean squared error (TMSE) and (PR) criterion. The results from this extended study are the also compared with those founded by AS. A simulation study has been conducted to compare the performance of the modified estimators of the ridge parameters. The results showed that under certain conditions the performance of the multivariate ridge regression estimators based on SUR ridge R MSmax is superior to other estimators in terms of TMSE and PR criterion. In large samples and when the collinearity between the explanatory variables is not high, the unbiased SUR, estimator produces a smaller TMSEs.

Place, publisher, year, edition, pages
2012. Vol. 41, no 9, p. 1675-1691
Keywords [en]
Multicollinearity; modified SUR ridge regression; Monte Carlo simulations; TMSE
National Category
Economics
Identifiers
URN: urn:nbn:se:hj:diva-13964DOI: 10.1080/03610926.2010.549281ISI: 000304526400013Scopus ID: 2-s2.0-84862896200Local ID: IHHEFSISOAI: oai:DiVA.org:hj-13964DiVA, id: diva2:378579
Available from: 2010-12-15 Created: 2010-12-15 Last updated: 2019-02-22Bibliographically approved

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Shukur, GhaziZeebari, Zangin

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