↓ Skip to main content

Measuring economic mobility in India using noisy data: a partial identification approach

Overview of attention for article published in Journal of the Royal Statistical Society: Series A (Statistics in Society), January 2023
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

twitter
13 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
10 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Measuring economic mobility in India using noisy data: a partial identification approach
Published in
Journal of the Royal Statistical Society: Series A (Statistics in Society), January 2023
DOI 10.1093/jrsssa/qnac005
Authors

Hao Li, Daniel L Millimet, Punarjit Roychowdhury

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 20%
Researcher 1 10%
Student > Doctoral Student 1 10%
Lecturer > Senior Lecturer 1 10%
Unknown 5 50%
Readers by discipline Count As %
Economics, Econometrics and Finance 4 40%
Agricultural and Biological Sciences 1 10%
Social Sciences 1 10%
Unknown 4 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 01 February 2023.
All research outputs
#3,412,873
of 25,392,582 outputs
Outputs from Journal of the Royal Statistical Society: Series A (Statistics in Society)
#137
of 897 outputs
Outputs of similar age
#69,570
of 472,544 outputs
Outputs of similar age from Journal of the Royal Statistical Society: Series A (Statistics in Society)
#5
of 16 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 897 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has done well, scoring higher than 84% 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 472,544 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.