Further results on testing Ar (1) against MA (1) disturbances in the linear regression model

Maxwell L. King, Michael McAleer

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This paper examines testing for AR(1) disturbances against MA(1) disturbances in the linear regression model. A Monte Carlo experiment compares the small-sample properties of the Cox test, some linearized Cox tests, and an approximate point optimal test, as well as a Lagrange multiplier test of AR (1) disturbances against ARMA (1, 1) disturbances. The main findings are that the true sizes of the asymptotic non-nested tests can differ considerably from their nominal sizes, the Lagrange multiplier test’s sizes are reasonably accurate and the point optimal test is generally more powerful than the other tests when appropriate critical values are used. When sizes are controlled at an arbitrary value of the AR (1) parameter, the relative power of the Cox test is increased substantially.

Original languageEnglish
Pages (from-to)649-663
Number of pages15
JournalReview of Economic Studies
Issue number4
Publication statusPublished - Oct 1987

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