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Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts

Author

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  • Jos Jansen, W.
  • Jin, Xiaowen
  • Winter, Jasper M. de

Abstract

We conduct a systematic comparison of the short-term forecasting abilities of twelve statistical models and professional analysts in a pseudo-real-time setting, using a large set of monthly indicators. Our analysis covers the euro area and its five largest countries over the years 1996-2011. We find summarizing the available monthly information in a few factors to be a more promising forecasting strategy than averaging a large number of single-indicator-based forecasts. Moreover, it is important to make use of all available monthly observations. The dynamic factor model is the best model overall, particularly for nowcasting and backcasting, due to its ability to incorporate more information (factors). Judgmental forecasts by professional analysts often embody valuable information that could be used to enhance the forecasts derived from purely mechanical procedures. (C) 2015 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Suggested Citation

  • Jos Jansen, W. & Jin, Xiaowen & Winter, Jasper M. de, 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," Munich Reprints in Economics 43488, University of Munich, Department of Economics.
    • Handle: RePEc:lmu:muenar:43488
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    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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