On the robustness of the general dynamic factor model with inﬁnite-dimensional space: identiﬁcation, estimation, and forecasting
Carlos Cesar Trucios-Maza,
João H. G Mazzeu,
Pedro Valls Pereira () and
Marc Hallin ()
No 2019-32, Working Papers ECARES from ULB -- Universite Libre de Bruxelles
General dynamic factor models have demonstrated their capacity to circumvent the curse of dimensionality in time series and have been successfully applied in many economic and ﬁnancial applications. However, their performance in the presence of outliers has not been analysed yet. In this paper, we study the impact of additive outliers on the identiﬁcation, estimation and forecasting performance of general dynamic factor models. Based on our ﬁndings, we propose robust identiﬁcation, estimation and forecasting procedures. Our proposal is evaluated via Monte Carlo experiments and in empirical data.
Keywords: Dimension reduction; Forecast; Jumps; Large panels (search for similar items in EconPapers)
Pages: 40 p.
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:eca:wpaper:2013/298201
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