On the calculation of the information matrix test in the normal linear regression model

Abstract

In this paper we propose a simplified method of a calculating the information matrix test in the normal linear regression model. A simulation study demonstrates that our test has considerably better size properties than the Chesher (1983)-Lancaster (1984) version of this test. Our test converges to its asymptotic distribution by n = 600, whereas for the same model Taylor (1987) reports the Chesher-Lancaster test statistic has not converged to its asymptotic distribution by n = 8000.