Median Regression for SUR Models with the Same Explanatory Varia

Ghazi Shukur and Zangin Zeebari ()
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Zangin Zeebari: Jönköping International Business School, Postal: Department of Economics, Finance and Statistics, Jönköping International Business School, P.O. Box 1026, SE-55111 Jönköping , Sweden

No 258, Working Paper Series in Economics and Institutions of Innovation from Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies

Abstract: 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. This kind of methodology is useful say when estimating the factors that affect firms’ innovation investments across European countries.

Keywords: Median Regression; Robustness; Efficiency; SURE Models; Innovation Investment (search for similar items in EconPapers)
JEL-codes: C30 C31 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2011-10-18
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:cesisp:0258

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