Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts
被引:38
作者:
Jansen, W. Jos
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Minist Finance, Financial & Econ Policy Dept, POB 20201, The Hague, NetherlandsMinist Finance, Financial & Econ Policy Dept, POB 20201, The Hague, Netherlands
Jansen, W. Jos
[1
]
Jin, Xiaowen
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Univ Munich, Munich Grad Sch Econ, POB 1111, Munich, GermanyMinist Finance, Financial & Econ Policy Dept, POB 20201, The Hague, Netherlands
Jin, Xiaowen
[2
]
de Winter, Jasper M.
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Nederlandsche Bank, Econ Policy & Res Div, POB 98, NL-1000 AB Amsterdam, NetherlandsMinist Finance, Financial & Econ Policy Dept, POB 20201, The Hague, Netherlands
de Winter, Jasper M.
[3
]
机构:
[1] Minist Finance, Financial & Econ Policy Dept, POB 20201, The Hague, Netherlands
[2] Univ Munich, Munich Grad Sch Econ, POB 1111, Munich, Germany
[3] Nederlandsche Bank, Econ Policy & Res Div, POB 98, NL-1000 AB Amsterdam, Netherlands
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.