Maximal Invariant Likelihood Based Testing of Semi-Linear Models

Maxwell King and Jahar L. Bhowmik

No 245, Econometric Society 2004 Australasian Meetings from Econometric Society

Abstract: In this paper, we use a maximal invariant likelihood (MIL) to construct two likelihood ratio (LR) tests. The first involves testing for the inclusion of a non-linear regressor and the second involves testing of a linear regressor against the alternative of a non-linear regressor. We report the results of a Monte Carlo experiment that compares the size and power properties of the traditional LR tests with those of our proposed MIL based LR tests. Our simulation results show that in both cases the MIL based tests have more accurate asymptotic critical values and better behaved (i.e., better centred) power curves than their classical counterparts

Keywords: Likelihood ratio test; non-linear regressor; monte carlo experiment; asymptotic critical value (search for similar items in EconPapers)
JEL-codes: C12 C2 (search for similar items in EconPapers)
Date: 2004-08-11
New Economics Papers: this item is included in nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:ecm:ausm04:245

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