The efficiency of least squares estimators of a seemingly unrelated regression model

Abstract

A measure defined by Bloomfield and Watson (1975)is applied to measure the relative performance between the ordinary least squares estmates (OLES) and Gauss-Markov estimates for a two-equation model of a seemingly unrelated regression system. Results obtained are compared with those obtained by Zellner (1963), Ravankar (1974) and Chang and Lin (1984). It can be seen that this efficeiency depends only the correlation coefficient of disturbances between two regression equations and is independent of the sample size.

Keywords:

• Least Square
• Seemingly Unrelatad Regression
• Gauss-Markov Estimate