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Seemingly unrelated...
Seemingly unrelated regressions with covariance matrix of cross-equation ridge regression residuals
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- Zeebari, Zangin (författare)
- Karolinska Institutet
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- Kibria, B. M. Golam (författare)
- Department of Mathematics and Statistics, Florida International University, Miami, USA
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- Shukur, Ghazi, 1955- (författare)
- Jönköping University,Linnéuniversitetet,Institutionen för nationalekonomi och statistik (NS),Department of Economics and Statistics, Linnaeus University, Växjö, Sweden,IHH, Statistik
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(creator_code:org_t)
- 2017-11-13
- 2018
- Engelska.
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Ingår i: Communications in Statistics - Theory and Methods. - : Taylor & Francis. - 0361-0926 .- 1532-415X. ; 47:20, s. 5029-5053
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Generalized least squares estimation of a system of seemingly unrelated regressions is usually a two-stage method: (1) estimation of cross-equation covariance matrix from ordinary least squares residuals for transforming data, and (2) application of least squares on transformed data. In presence of multicollinearity problem, conventionally ridge regression is applied at stage 2. We investigate the usage of ridge residuals at stage 1, and show analytically that the covariance matrix based on the least squares residuals does not always result in more efficient estimator. A simulation study and an application to a system of firms' gross investment support our finding.
Ämnesord
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Nyckelord
- Multicollinearity
- Ridge regression
- Seemingly unrelated regressions
- Tillämpad matematik
- Applied Mathematics
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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