Survey data as coincident or leading indicators

Cecilia Frale, Massimiliano Marcellino, Gian Luigi Mazzi and Tommaso Proietti
Additional contact information
Cecilia Frale: Ministry of the Economy and Finance, Rome, Italy, Postal: Ministry of the Economy and Finance, Rome, Italy
Gian Luigi Mazzi: Eurostat, Luxembourg, Postal: Eurostat, Luxembourg

Journal of Forecasting, 2010, vol. 29, issue 1-2, 109-131

Abstract: In this paper we propose a monthly measure for the euro area gross domestic product (GDP) based on a small-scale factor model for mixed-frequency data, featuring two factors: the first is driven by hard data, whereas the second captures the contribution of survey variables as coincident indicators. Within this framework we evaluate both the in-sample contribution of the second survey-based factor, and the short-term forecasting performance of the model in a pseudo-real-time experiment. We find that the survey-based factor plays a significant role for two components of GDP: industrial value added and exports. Moreover, the two-factor model outperforms in terms of out-of-sample forecasting accuracy the traditional autoregressive distributed lags (ADL) specifications and the single-factor model, with few exceptions. Copyright © 2009 John Wiley & Sons, Ltd.

Date: 2010
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Citations: View citations in EconPapers (39)

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Related works:
Working Paper: Survey Data as Coicident or Leading Indicators (2009)
Working Paper: Survey Data as Coincident or Leading Indicators
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Persistent link: https://EconPapers.repec.org/RePEc:jof:jforec:v:29:y:2010:i:1-2:p:109-131

DOI: 10.1002/for.1142

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