A GENERALIZED LEAST SQUARES ESTIMATION METHOD FOR VARMA MODELS*

Authors: RAFAEL FLORES DE FRUTOS; GREGORIO SERRANO

Source: Statistics, Volume 36, Number 4, 2002 , pp. 303-316(14)

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Abstract:

In this paper a new generalized least squares procedure for estimating VARMA models is proposed. This method differs from existing ones in explicitly considering the stochastic structure of the approximation error that arises when lagged innovations are replaced with lagged residuals obtained from a long VAR. Simulation results indicate that this method performs better than the Double Regression method and similar to Mauricio's (1995) exact maximum likelihood estimation procedure.

Keywords: VARMA models estimation; Generalized least squares; Model specification

Document Type: Research article

DOI: http://dx.doi.org/10.1080/02331880213193

Publication date: 2002-01-01