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Real-Time Probabilistic Nowcasts of UK Quarterly GDP Growth Using a Mixed-Frequency Bottom-Up Approach
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Authors
External Authors
Lopresto, A
Related Themes
Macro-Economic Modelling and ForecastingJEL Code
C53; E32
Journal
National Institute Economic Review
Publisher
Cambridge University Press
External Resources
Issue
254
We propose a nowcasting system to obtain real-time predictive intervals for the first-release of UK quarterly GDP growth that can be implemented in a menu-driven econometric software. We design a bottom-up approach: forecasts for GDP components (from the output and the expenditure approaches) are inputs into the computation of probabilistic forecasts for GDP growth. For each GDP component considered, mixed-data-sampling regressions are applied to extract predictive content from monthly and quarterly indicators. We find that predictions from the nowcasting system are accurate, in particular when nowcasts are computed using monthly indicators 30 days before the GDP release. The system is also able to provide well-calibrated predictive intervals.
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