Robustness and the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting
João H. G. Mazzeu,
Pedro Valls Pereira () and
Marc Hallin ()
No 521, Textos para discussão from FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil)
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.
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Journal Article: Robustness and the general dynamic factor model with infinite-dimensional space: Identification, estimation, and forecasting (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:fgv:eesptd:521
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