Estimating Stationary ARMA Models Efficiently
AbstractThis paper discusses the asymptotic and finite-sample properties of the Efficient Method of Moments (EMM) when applied to estimating stationary ARMA models. Issues such of identification, model selection, and testing are also discussed. The properties of these estimators are compared to those of Maximum Likelihood (ML) by means of Monte Carlo experiments for bot invertible and non-invertible ARMA models.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 1999 with number 1333.
Date of creation: 01 Mar 1999
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