The Forecasting Performance of Dynamic Factor Models with Vintage Data

Luca Di Bonaventura, Mario Forni and Francesco Pattarin ()

Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) from Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi"

Abstract: We present a comparative analysis of the forecasting performance of two dynamic factor models, the Stock and Watson (2002a, b) model and the Forni, Hallin, Lippi and Reichlin (2005) model, based on vintage data. Our dataset that contains 107 monthly US “first release” macroeconomic and financial vintage time series, spanning the 1996:12 to 2017:6 period with monthly periodicity, extracted from the Bloomberg database†. We compute real-time one-month-ahead forecasts with both models for four key macroeconomic variables: the month-on-month change in industrial production, the unemployment rate, the core consumer price index and the ISM Purchasing Managers’ Index. First, we find that both the Stock and Watson and the Forni, Hallin, Lippi and Reichlin models outperform simple autoregressions for industrial production, unemployment rate and consumer prices, but that only the first model does so for the PMI. Second, we find that neither models always outperform the other. While Forni, Hallin, Lippi and Reichlin’s beats Stock and Watson’s in forecasting industrial production and consumer prices, the opposite happens for the unemployment rate and the PMI.

Keywords: Dynamic factor models; Forecasting; Forecasting Performance; Vintage data; First release data (search for similar items in EconPapers)
JEL-codes: C01 C32 C52 C53 E27 E37 (search for similar items in EconPapers)
Pages: pages 46
Date: 2018-07
New Economics Papers: this item is included in nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

Downloads: (external link)
http://155.185.68.2/CefinPaper/CEFIN-WP70.pdf (application/pdf)

Related works:
Working Paper: The Forcasting Performance of Dynamic Factor Models with Vintage Data (2018)
Working Paper: The Forecasting Performance of Dynamic Factor Models with Vintage Data (2018)
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:mod:wcefin:0070

Access Statistics for this paper

More papers in Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) from Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi" Contact information at EDIRC.
Bibliographic data for series maintained by Giuseppe Marotta ().