Main Article Content
Abstract
This article is concerned with the estimation problem of multicollinearity in two seemingly unrelated regression (SUR) equations with linear restrictions. We propose a restricted feasible SUR estimates of the regression coefficients of this model and compare with feasible generalized least squares (FGLS) estimator and the estimator proposed by Revankar (1974) in the matrix mean square error sense. The ideas in the article are evaluated using Monte Carlo simulation.
Keywords
Restricted feasible estimator
Seemingly unrelated regressions
Two-stage estimator
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following License
CC BY: This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
How to Cite
Erdugan, F., & Akdeniz, F. (2016). Restricted estimator in two seemingly unrelated regression model. Pakistan Journal of Statistics and Operation Research, 12(4), 579-588. https://doi.org/10.18187/pjsor.v12i4.1381
