Nowcasting Norway

Nowcasting Norway
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Nowcasting Norway
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Matteo Luciani
Lorenzo Ricci
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Matteo Luciani
Lorenzo Ricci
Abstract
We produce predictions of the previous, the current, and the next quarter of NorwegianGDP. To this end, we estimate a Bayesian Dynamic Factor model on a panel of 14variables (all followed closely by market operators) ranging from 1990 to 2011. By meansof a real time forecasting exercise we show that the Bayesian Dynamic Factor Model outperformsa standard benchmark model, while it performs equally well than the BloombergSurvey. Additionally, we use our model to produce annual GDP growth rate nowcast. Weshow that our annual nowcast outperform the Norges Bank’s projections of current yearGDP.
Suggested Citation
Matteo Luciani & Lorenzo Ricci, 2013.
Nowcasting Norway
,"
Working Papers ECARES
ECARES 2013-10, ULB -- Universite Libre de Bruxelles.
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RePEc:eca:wpaper:2013/139866
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Other versions of this item:
Matteo Luciani & Lorenzo Ricci, 2014.
Nowcasting Norway
,"
International Journal of Central Banking
, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
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More about this item
Keywords
JEL
classification:
C32
- Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
C53
- Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
E37
- Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
NEP fields
This paper has been announced in the following
NEP Reports
NEP-FOR-2013-02-08
(Forecasting)
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