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Vector autoregressions with dynamic factor coefficients and conditionally heteroskedastic errors

Overview of attention for article published in Journal of Econometrics, May 2024
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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8 X users

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2 Mendeley
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Title
Vector autoregressions with dynamic factor coefficients and conditionally heteroskedastic errors
Published in
Journal of Econometrics, May 2024
DOI 10.1016/j.jeconom.2024.105750
Authors

Paolo Gorgi, Siem Jan Koopman, Julia Schaumburg

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 100%
Readers by discipline Count As %
Energy 2 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 May 2024.
All research outputs
#7,124,451
of 25,965,655 outputs
Outputs from Journal of Econometrics
#836
of 2,953 outputs
Outputs of similar age
#58,062
of 223,365 outputs
Outputs of similar age from Journal of Econometrics
#3
of 34 outputs
Altmetric has tracked 25,965,655 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 2,953 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has gotten more attention than average, scoring higher than 71% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 223,365 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.