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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 (82nd percentile)

Mentioned by

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

Citations

dimensions_citation
95 Dimensions

Readers on

mendeley
143 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 5 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 143 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 3 2%
Portugal 2 1%
Netherlands 2 1%
Brazil 1 <1%
Germany 1 <1%
Switzerland 1 <1%
United Kingdom 1 <1%
Belgium 1 <1%
Luxembourg 1 <1%
Other 0 0%
Unknown 130 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 29%
Researcher 27 19%
Student > Master 26 18%
Student > Doctoral Student 15 10%
Professor > Associate Professor 9 6%
Other 20 14%
Unknown 5 3%
Readers by discipline Count As %
Economics, Econometrics and Finance 48 34%
Physics and Astronomy 18 13%
Business, Management and Accounting 15 10%
Computer Science 11 8%
Social Sciences 9 6%
Other 26 18%
Unknown 16 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 08 February 2020.
All research outputs
#1,488,952
of 14,474,140 outputs
Outputs from PLoS ONE
#22,549
of 149,560 outputs
Outputs of similar age
#17,537
of 157,425 outputs
Outputs of similar age from PLoS ONE
#673
of 3,861 outputs
Altmetric has tracked 14,474,140 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 149,560 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. 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 157,425 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 3,861 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.