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Median Regression for SUR Models with the Same Explanatory Variables in Each Equation
Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics. (Statistik / LNUC)ORCID iD: 0000-0002-3416-5896
2012 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, no 8, 1765-1779 p.Article in journal (Refereed) Published
Abstract [en]

In this paper we introduce an interesting feature of the Generalized Least Absolute Deviations (GLAD) method for Seemingly Unrelated Regression Equations (SURE) models. Contrary to the collapse of Generalized Least Squares (GLS) parameter estimations of SURE models to the Ordinary Least Squares (OLS) estimations of the individual equations when the same regressors are common between all equations, the estimations of the proposed methodology are not identical to the Least Absolute Deviations (LAD) estimations of the individual equations. This is important since contrary to the least squares methods, one can take advantage of efficiency gain due to cross-equation correlations even if the system includes the same regressors in each equation.

Place, publisher, year, edition, pages
Taylor & Francis, 2012. Vol. 39, no 8, 1765-1779 p.
National Category
Probability Theory and Statistics Economics and Business
Research subject
Statistics/Econometrics
Identifiers
URN: urn:nbn:se:lnu:diva-23175DOI: 10.1080/02664763.2012.682566Scopus ID: 2-s2.0-84862635630OAI: oai:DiVA.org:lnu-23175DiVA: diva2:580490
Available from: 2012-12-21 Created: 2012-12-21 Last updated: 2017-12-06Bibliographically approved

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Shukur, Ghazi

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