Alternative Tests of the Error Components Model

Abstract

The error Components regression model is now widely applied in econometics and statistics. Given the potentially high costs of incorrectly excluding the component from the model, an error components test should have high power. In addition, if a test is to gain acceptance from practitioners, the test should be computed easily. To obtain improved critical-value approximations, we introduce a standardized Lagrange multiplier (SLM) test statistic, which is centered and scaled to have a zero mean and unit variance under the null hypothesis. We also examine the F test, which is easily computed and has a well-known exact distribution under the null hypothesis if the regression errors are normally distributed