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Survey data as coincident or leading indicators

Author

Listed:
  • Cecilia Frale

    (Ministry of the Economy and Finance, Rome, Italy)

  • Massimiliano Marcellino
  • Gian Luigi Mazzi

    (Eurostat, Luxembourg)

  • Tommaso Proietti

    (Università di Roma 'Tor Vergata', Rome, Italy)

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.

Suggested Citation

  • Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2010. "Survey data as coincident or leading indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 109-131.
  • Handle: RePEc:jof:jforec:v:29:y:2010:i:1-2:p:109-131
    DOI: 10.1002/for.1142
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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