Robust time series models with trend and seasonal components

Michele Caivano, Andrew Harvey and Alessandra Luati
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Alessandra Luati: University of Bologna

SERIEs: Journal of the Spanish Economic Association, 2016, vol. 7, issue 1, No 4, 99-120

Abstract: Abstract 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.

Keywords: Fat tails; EGB2; Score; Robustness; Student’s t; Trimming; Winsorizing (search for similar items in EconPapers)
JEL-codes: C22 G17 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:series:v:7:y:2016:i:1:d:10.1007_s13209-015-0134-1

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DOI: 10.1007/s13209-015-0134-1

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