Robust time series models with trend and seasonal components

• Michele Caivano ^[3] ; Andrew Harvey ^[1] ; Alessandra Luati ^[2]
  1. [1] University of Cambridge

     University of Cambridge

     Cambridge District, Reino Unido

     
  2. [2] University of Bologna

     University of Bologna

     Bolonia, Italia

     
  3. [3] Bank of Italy

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• Localización: SERIEs : Journal of the Spanish Economic Association, ISSN 1869-4195, Vol. 7, Nº. 1, 2016 (Ejemplar dedicado a: Special Issue in Honor of Agustín Maravall), págs. 99-120
• Idioma: inglés
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• Resumen

  • We describe observation driven time series models for Student-t and EGB2 conditional distributions in which the signal is a linear function of past values of the score of the conditional distribution. These specifications produce models that are easy to implement and deal with outliers by what amounts to a soft form of trimming in the case of t and a soft form of Winsorizing in the case of EGB2. We show how a model with trend and seasonal components can be used as the basis for a seasonal adjustment procedure. The methods are illustrated with US and Spanish data.