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

In this paper, the authors propose a simple procedure for testing the existence of common roots in lag polynomials. They first show, by using a generalized Bezout property, that this hypothesis can be put under a "mixed" form that is linear with respect to the auxiliary parameters and with respect to the initial parameters. It follows that the test procedures can be implemented only by using regressions packages. Copyright 1989 by The Econometric Society.