Median Regression for SUR Models with the Same Explanatory Varia
AbstractIn 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies in its series Working Paper Series in Economics and Institutions of Innovation with number 258.
Length: 20 pages
Date of creation: 18 Oct 2011
Date of revision:
Contact details of provider:
Postal: CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology, SE-100 44 Stockholm, Sweden
Phone: +46 8 790 95 63
Web page: http://www.infra.kth.se/cesis/
More information through EDIRC
Median Regression; Robustness; Efficiency; SURE Models; Innovation Investment;
Find related papers by JEL classification:
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Vardan Hovsepyan).
If references are entirely missing, you can add them using this form.