EconPapers    
Economics at your fingertips  
 

On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting

Carlos Trucíos (), 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
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published by:

Downloads: (external link)
https://dipot.ulb.ac.be/dspace/bitstream/2013/2982 ... ALLIN-robustness.pdf Full text for the whole work, or for a work part (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eca:wpaper:2013/298201

Ordering information: This working paper can be ordered from
http://hdl.handle.ne ... lb.ac.be:2013/298201

Access Statistics for this paper

More papers in Working Papers ECARES from ULB -- Universite Libre de Bruxelles Contact information at EDIRC.
Bibliographic data for series maintained by Benoit Pauwels ().

 
Page updated 2025-03-30
Handle: RePEc:eca:wpaper:2013/298201