Third order asymptotic properties of maximum likelihood estimators for Gaussian ARMA processes

In this paper we investigate various third-order asymptotic properties of maximum likelihood estimators for Gaussian ARMA processes by the third-order Edgeworth expansions of the sampling distributions. We define a third-order asymptotic efficiency by the highest probability concentration around the true value with respect to the third-order Edgeworth expansion. Then we show that the maximum likelihood estimator is not always third-order asymptotically efficient in the class A3 of third-order asymptotically median unbiased estimators. But, if we confine our discussions to an appropriate class D ([subset of] A3) of estimators, we can show that appropriately modified maximum likelihood estimator is always third-order asymptotically efficient in D.