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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, Luiz Hotta, Pedro Valls Pereira () and Marc Hallin ()

No 2019-32, Working Papers ECARES from ULB -- Universite Libre de Bruxelles

Abstract: 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.
Date: 2019-12
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-ore
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Handle: RePEc:eca:wpaper:2013/298201