Large sample properties of parameter least squares estimates for time‐varying arma models

Christian Francq () and Antony Gautier
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Christian Francq: CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique, IP Paris - Institut Polytechnique de Paris

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Abstract: Abstract. This paper considers estimation of ARMA models with time‐varying coefficients. The ARMA parameters belong to d different regimes. The changes in regime occur at irregular time intervals. Consistency and asymptotic normality of least squares and quasi‐generalized least squares estimators are shown.

Date: 2004-07-27
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Published in Journal of Time Series Analysis, 2004, 25 (5), pp.765-783. ⟨10.1111/j.1467-9892.2004.02003.x⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05431374

DOI: 10.1111/j.1467-9892.2004.02003.x

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