The paper compares the pseudo real-time forecasting performance of three dynamic factor models: (i) the standard principal component model introduced by Stock and Watson in 2002; (ii) the model based on generalized principal components, introduced by Forni, Hallin, Lippi, and Reichlin in 2005; (iii) the model recently proposed by Forni, Hallin, Lippi, and Zaffaroni in 2015. We employ a large monthly dataset of macroeconomic and financial time series for the US economy, which includes the Great Moderation, the Great Recession and the subsequent recovery (an update of the so-called Stock and Watson dataset). Using a rolling window for estimation and prediction, we find that model (iii) significantly outperforms models (i) and (ii) in the Great Moderation period for both industrial production and inflation, and that model (iii) is also the best method for inflation over the full sample. However, model (iii) is outperformed by models (ii) and (i) over the full sample for industrial production.

Dynamic factor model with infinite-dimensional factor space: Forecasting / Forni, Mario; Giovannelli, Alessandro; Lippi, Marco; Soccorsi, Stefano. - In: JOURNAL OF APPLIED ECONOMETRICS. - ISSN 0883-7252. - 33:5(2018), pp. 625-642. [10.1002/jae.2634]

Dynamic factor model with infinite-dimensional factor space: Forecasting

Forni, Mario;
2018

Abstract

The paper compares the pseudo real-time forecasting performance of three dynamic factor models: (i) the standard principal component model introduced by Stock and Watson in 2002; (ii) the model based on generalized principal components, introduced by Forni, Hallin, Lippi, and Reichlin in 2005; (iii) the model recently proposed by Forni, Hallin, Lippi, and Zaffaroni in 2015. We employ a large monthly dataset of macroeconomic and financial time series for the US economy, which includes the Great Moderation, the Great Recession and the subsequent recovery (an update of the so-called Stock and Watson dataset). Using a rolling window for estimation and prediction, we find that model (iii) significantly outperforms models (i) and (ii) in the Great Moderation period for both industrial production and inflation, and that model (iii) is also the best method for inflation over the full sample. However, model (iii) is outperformed by models (ii) and (i) over the full sample for industrial production.
2018
33
5
625
642
Dynamic factor model with infinite-dimensional factor space: Forecasting / Forni, Mario; Giovannelli, Alessandro; Lippi, Marco; Soccorsi, Stefano. - In: JOURNAL OF APPLIED ECONOMETRICS. - ISSN 0883-7252. - 33:5(2018), pp. 625-642. [10.1002/jae.2634]
Forni, Mario; Giovannelli, Alessandro; Lippi, Marco; Soccorsi, Stefano
File in questo prodotto:
File Dimensione Formato  
jae.2634.pdf

Accesso riservato

Tipologia: Versione pubblicata dall'editore
Dimensione 1.59 MB
Formato Adobe PDF
1.59 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1165676
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 19
  • ???jsp.display-item.citation.isi??? 18
social impact