ON THE PROBLEM OF OPTIMAL INFERENCE IN THE SIMPLE ERROR COMPONENT MODEL FOR PANEL DATA

Abstract

For data consisting of cross sections of units observed over time, the Error Component Regression (ECR) model, with random intercept and constant slope, may sometimes be adequate. While most interest has been focused on pOint estimation of the slope parameter S, little attention has been paid to the problem of making confidence statements and tests about S. In this paper, the performance of some estimators of S and the corresponding test statistics are investigated. In consideration of bias, efficiency and power of tests, it is shown that the Maximum Likelihood estimator with the cqrresponding test statistic is outstanding in large samples. But, in the small sample case there are hardly any reasons for the Maximum Likelihood approach. In the latter case, the use of estimators and test statistics based on within- or between group comparisons is suggested. The results, together with tools for a proper application of the ECR model, are demonstrated on data from a medical follow-up study.