Values of Asymptotic Efficiency in Linear Regression Models Concepts and Applications

Abstract

The purpose of this paper is to derive asymptotic efficiency formula in which an error variable ? has some probability density function in linear regression models such as normal, extreme- value for largest values and logistic distribution. The variances of the regression coefficients are estimated by ordinary least squares estimator and maximum likelihood estimator in order to obtain variance efficiencies. Some applications of asymptotic efficiency without simulation and with simulation have been done. Asymptotic efficiency values without simulation for the regression coefficient ?₁ were (1, 0.608, 0.912) for normal, extreme-value and logistic distributions respectively.