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Measuring the Intangibles: A Metrics for the Economic Complexity of Countries and Products

Overview of attention for article published in PLoS ONE, August 2013
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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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

policy
1 policy source
twitter
4 tweeters
facebook
1 Facebook page
wikipedia
1 Wikipedia page
googleplus
1 Google+ user

Citations

dimensions_citation
83 Dimensions

Readers on

mendeley
136 Mendeley
citeulike
2 CiteULike
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Title
Measuring the Intangibles: A Metrics for the Economic Complexity of Countries and Products
Published in
PLoS ONE, August 2013
DOI 10.1371/journal.pone.0070726
Pubmed ID
Authors

Matthieu Cristelli, Andrea Gabrielli, Andrea Tacchella, Guido Caldarelli, Luciano Pietronero

Abstract

We investigate a recent methodology we have proposed to extract valuable information on the competitiveness of countries and complexity of products from trade data. Standard economic theories predict a high level of specialization of countries in specific industrial sectors. However, a direct analysis of the official databases of exported products by all countries shows that the actual situation is very different. Countries commonly considered as developed ones are extremely diversified, exporting a large variety of products from very simple to very complex. At the same time countries generally considered as less developed export only the products also exported by the majority of countries. This situation calls for the introduction of a non-monetary and non-income-based measure for country economy complexity which uncovers the hidden potential for development and growth. The statistical approach we present here consists of coupled non-linear maps relating the competitiveness/fitness of countries to the complexity of their products. The fixed point of this transformation defines a metrics for the fitness of countries and the complexity of products. We argue that the key point to properly extract the economic information is the non-linearity of the map which is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We present a detailed comparison of the results of this approach directly with those of the Method of Reflections by Hidalgo and Hausmann, showing the better performance of our method and a more solid economic, scientific and consistent foundation.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 1%
Portugal 2 1%
Italy 2 1%
United Kingdom 1 <1%
Switzerland 1 <1%
Brazil 1 <1%
Luxembourg 1 <1%
Belgium 1 <1%
Germany 1 <1%
Other 0 0%
Unknown 124 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 27%
Researcher 28 21%
Student > Master 25 18%
Student > Doctoral Student 15 11%
Professor > Associate Professor 8 6%
Other 23 17%
Readers by discipline Count As %
Economics, Econometrics and Finance 46 34%
Physics and Astronomy 16 12%
Unspecified 16 12%
Business, Management and Accounting 12 9%
Computer Science 11 8%
Other 35 26%

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 18 January 2019.
All research outputs
#1,394,151
of 13,232,126 outputs
Outputs from PLoS ONE
#22,627
of 141,721 outputs
Outputs of similar age
#18,245
of 155,810 outputs
Outputs of similar age from PLoS ONE
#706
of 3,874 outputs
Altmetric has tracked 13,232,126 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 141,721 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.0. This one has done well, scoring higher than 83% 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 155,810 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 88% of its contemporaries.
We're also able to compare this research output to 3,874 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.