Ghazi Shukur () and Zangin Zeebari ()
Additional contact information
Ghazi Shukur: Jönköping International Business School, Postal: Department of Economics, Finance and Statistics, Jönköping International Business School, P.O. Box 1026, SE-55111 Jönköping , Sweden
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
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
20 pages, October 18, 2011
Full text files
cesiswp258.pdf
Questions (including download problems) about the papers in this series should be directed to Vardan Hovsepyan ()
Report other problems with accessing this service to Sune Karlsson ().
RePEc:hhs:cesisp:0258This page generated on 2024-09-13 22:14:26.