Dynamic Factor Model with Infinite Dimensional Factor Space: Forecasting

43 Pages Posted: 18 Apr 2016

See all articles by Mario Forni

Mario Forni

Università di Modena; Centre for Economic Policy Research (CEPR)

Alessandro Giovannelli

University of Rome Tor Vergata

Marco Lippi

Dipartimento di Scienze Economiche (DiSSE); Einaudi Institute for Economics and Finance (EIEF)

Stefano Soccorsi

Department of Economics, Lancaster University Management School

Date Written: March 2016

Abstract

The paper compares the pseudo real-time forecasting performance of three Dynamic Factor Models: (i) The standard principal-component model, Stock and Watson (2002a), (ii) The model based on generalized principal components, Forni et al. (2005), (iii) The model recently proposed in Forni et al. (2015b) and Forni et al. (2015a). 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. Using a rolling window for estimation and prediction, we nd that (iii) neatly outperforms (i) and (ii) in the Great Moderation period for both Industrial Production and Inflation, and for Inflation over the full sample. However, (iii) is outperfomed by (i) and (ii) over the full sample for Industrial Production.

Suggested Citation

Forni, Mario and Giovannelli, Alessandro and Lippi, Marco and Soccorsi, Stefano, Dynamic Factor Model with Infinite Dimensional Factor Space: Forecasting (March 2016). CEPR Discussion Paper No. DP11161. Available at SSRN: https://ssrn.com/abstract=2766454

Mario Forni (Contact Author)

Università di Modena; Centre for Economic Policy Research (CEPR) ( email )

Alessandro Giovannelli

University of Rome Tor Vergata ( email )

Via di Tor Vergata
Rome, Lazio 00133
Italy

Marco Lippi

Dipartimento di Scienze Economiche (DiSSE) ( email )

14 Via Cesalpino
Rome, 00161
Italy
+39 06 4428 4202 (Phone)
+39 06 4404 572 (Fax)

Einaudi Institute for Economics and Finance (EIEF) ( email )

Via Due Macelli, 73
Rome, 00187
Italy

Stefano Soccorsi

Department of Economics, Lancaster University Management School ( email )

Lancaster, LA1 4YX
United Kingdom

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