Comparing MINQUE and IAUE estimates of variance components of a random coefficient model

Abstract

An alternative way to estimate the coefficient variance in the Swamy's RCR model has been derived using Minimum Norm Quadratic Estimation (MINQUE), and the Iteration Almost Unbiased Estimator (IAUE) methods. The estimators' performance in the RCR model are examined in Monte Carlo study. The Monte Carlo study provides some insight into how well the RCR model performs in small, medium, and large samples in the case of random, mixed, and fixed coefficient regression. We found that using MINQUE method to estimate the coefficient variance has reduce the probability of having negative variance comparing with the Swamy method. IAUE method was superior, since it gives zero percent of negative 2728 Souha K. Badr et al. variance and has a low variation and a low bias in estimation coefficient parameters, even in case of fixed coefficients.