Convergence results for maximum likelihood type estimators in multivariable ARMA models II

Rainer Dahlhaus () and Benedikt Pötscher

Journal of Multivariate Analysis, 1989, vol. 30, issue 2, 241-244

Abstract: The consistency proof for the (Gaussian quasi) maximum likelihood estimator in multivariable ARMA models as given in Dunsmuir and Hannan (1976, Adv, in Appl. Probab. 8, 339-364) rests on a certain property of the underlying parameter space, called B6 in their paper. It is not known whether the usual parameter spaces like the manifold M(n) or the parameter spaces corresponding to echelon forms satisfy condition B6, since the argument given by Dunsmuir and Hannan to establish this fact is inconclusive. In Pötscher (1987, J. Multivariate Anal. 21 29-52) it was shown how consistency can be proved without relying on B6 if the data generating process is Gaussian. In this note we show that the Gaussianity assumption can be replaced by ergodicity thus restoring Dunsmuir and Hannan's consistency proof to its full generality and extending it to parameter spaces which do not satisfy condition B6.

Keywords: ARMA; model; likelihood; function; consistency; zeroes; of; spectral; density (search for similar items in EconPapers)
Date: 1989
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Journal Article: Convergence results for maximum likelihood type estimators in multivariable ARMA models (1987)
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