Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/298506 
Year of Publication: 
2023
Series/Report no.: 
Staff Memo No. 13/2023
Publisher: 
Norges Bank, Oslo
Abstract: 
This paper presents a framework for quantifying uncertainty around point forecasts for GDP, inflation and house prices in Norway. The framework combines quantile regressions using a broad set of uncertainty indicators with a skewed t-distribution, allowing for time-variation and asymmetry in the uncertainty forecasts. This approach helps provide deeper insights into the macroeconomic uncertainty surrounding forecasts than more traditional time-series models, where uncertainty is usually symmetric and with limited time-variation. Formal tests, such as the log score and the Continuous Ranked Probability Score (CRPS), show that using informative indicators tend to improve density forecasts, particularity in the medium run.
Subjects: 
GDP
house prices
inflation
forecasting
quantile regressions
Growth-at-risk
Houseprices-at-risk
Inflation-at-risk
density forecast
fan charts
JEL: 
C53
E23
E27
E3
E44
Persistent Identifier of the first edition: 
ISBN: 
978-82-8379-286-7
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Research Report
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