On the median regression for SURE models with applications to 3-generation immigrants data in Sweden
AbstractIn this paper we generalize the median regression method to be applicable to system of regression equations, in particular SURE models. Giving the existence of proper system wise medians of the residuals from different equations, we apply the weighted median regression with the weights obtained from the covariance matrix of the equations obtained from ordinary SURE method. The benefit of this model in our case is that the SURE estimators utilise the information present in the cross regression (or equations) error correlation and hence more efficient than other estimation methods like the OLS method. The Seemingly Unrelated Median Regression Equations (SUMRE) models produce results that are more robust than the usual SURE or single equations OLS estimation when the distributions of the dependent variables are not normally distributed or the data are associated with outliers. Moreover, the results are also more efficient than is the cases of single equations median regressions when the residuals from the different equations are correlated. A theorem is derived and indicates that even if there is no statistically significant correlation between the equations, using SUMRE model instead of SURE models will not damage the estimation of parameters.
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Bibliographic InfoArticle provided by Elsevier in its journal Economic Modelling.
Volume (Year): 28 (2011)
Issue (Month): 6 ()
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Web page: http://www.elsevier.com/locate/inca/30411
Median regression; SURE models; Robustness; Efficiency;
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
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- Zeebari, Zangin & Shukur, Ghazi, 2012. "On the Least Absolute Deviations Method for Ridge Estimation of SURE Models," HUI Working Papers 69, HUI Research.
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