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Nowcasting GDP in Real-Time: A Density Combination Approach

Aastveit, Knut Are; Gerdrup, Karsten R.; Jore, Anne Sofie; Thorsrud, Leif Anders
Working paper
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CAMP_wp_01-2011.pdf (854.5Kb)
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http://hdl.handle.net/11250/95383
Utgivelsesdato
2011
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  • Centre for Applied Macro- and Petroleum economics (CAMP) [104]
Sammendrag
In this paper we use U.S. real-time vintage data and produce combined density nowcasts

for quarterly GDP growth from a system of three commonly used model classes. The

density nowcasts are combined in two steps. First, a wide selection of individual models

within each model class are combined separately. Then, the nowcasts from the three

model classes are combined into a single predictive density. We update the density nowcast

for every new data release throughout the quarter, and highlight the importance of

new information for the evaluation period 1990Q2-2010Q3. Our results show that the

logarithmic score of the predictive densities for U.S. GDP increase almost monotonically

as new information arrives during the quarter. While the best performing model class

is changing during the quarter, the density nowcasts from our combination framework

is always performing well both in terms of logarithmic scores and calibration tests. The

density combination approach is superior to a simple model selection strategy and also

performs better in terms of point forecast evaluation than standard point forecast combinations.
Beskrivelse
1/2010 and 2/2010 was published as CAMAR Working Paper Series (ISSN 1892-2198). From 2011 the series' name changed to CAMP Working Paper Series.
Utgiver
BI Norwegian Business School
Serie
CAMP Working Paper Series;1/2011

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