Fast estimation methods for time series models in state-space form

  1. Jerez Méndez, Miguel
  2. Garcia-Hiernaux, Alfredo
  3. Casals Carro, José
Revista:
Documentos de Trabajo (ICAE)

ISSN: 2341-2356

Año de publicación: 2005

Número: 4

Tipo: Documento de Trabajo

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Otras publicaciones en: Documentos de Trabajo (ICAE)

Resumen

We propose two fast, stable and consistent methods to estimate time series models expressed in their equivalent state-space form. They are useful both, to obtain adequate initial conditions for a maximum-likelihood iteration, or to provide final estimates when maximum-likelihood is considered inadequate or costly. The state-space foundation of these procedures implies that they can estimate any linear fixed-coefficients model, such as ARIMA, VARMAX or structural time series models. The computational and finitesample performance of both methods is very good, as a simulation exercise shows.

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