Using Data, Networks and Complexity to Study Trade, Aid, Economics

The great thing about having access to the entirety of the UN’s commodity trade database is that you can ask any kind of question you wish of the data.

For example, here’s a network representation of trade flows throughout the entire world in agricultural products in 2010.

COMTRADE 2010 agriculture sector

A network representation of global trade in agricultural products in 2010. Country size and colour is the exporter-ness of the country (purple = very exporter-y)

Bigger, more purple nodes are the ones with the biggest average export (simply the total export divided by the number of trading partners. Network scientists insist on calling this the ‘Weighted Out-Degree’. Don’t blame me.) When viewed from inside a country’s circle facing towards a particular trading partner exports curve out to the left, meaning, conversely, that imports curve in from the right. The colour of the lines is an average of the colours of the two countries.

Most interesting to note, are the following features:

  • The USA is by a huge margin the world’s biggest exporter of agricultural products ($67 billion compared to second-place Brazil’s $29 billion. The biggest products are soya, maize, cotton and wheat.)
  • China is by a huge margin the world’s biggest importer ($56 billion compared to second-place USA’s $35 billion. Since you ask, it imports soya beans from the US, Brazil and Argentina, cotton from the US and India, and wood from Russia. Now you know.)
  • Only Canada, Mexico, Ireland, the Netherlands (NLD) and Morocco (MAR) have a visually obvious trade balance. All other countries are either clear net importers or clear net exporters.

Also very interesting—but this ones requires a bit more concentrated looking if you’re not willing to take my word for it—you can definitely see geographic clusters. Look at the star around Japan (JPN); it includes Thailand, Vietnam, Australia, Indonesia and the Philipines. Europe is very clearly at the bottom (note that it’s purely fortuitous that Britain and Ireland have ended up on the Western fringe of Europe, but it’s not chance that they’re together on a fringe.) Israel (ISR) sits at the border of Europe and the Middle East/North Africa (Egypt, Syria, Jordan, and Tunisia are all nearby.)

The products which are categorised as ‘agricultural’ are according to the categorisation used by the World Input-Output Database (WIOD), the subject of at least one blog post here. The trade flow data is from a massive (200+ million rows) database of trade flows which I’ve spent the last hundred and fifty years assembling from the UN’s commodity trade database, COMTRADE. The visualisation is from a piece of open-source software called Gephi with a heavily-tweaked Force Atlas 2 layout.

This is just one of an unimaginable number of interesting analyses and visualisations I’ll be able to do, now that I’ve got my very own copy of UN’s COMTRADE database to play with and ask questions of as I see fit. If you’d like to see any interesting analyses in future blog posts, let me know on Twitter @aid_complexity.

The fun is only just beginning…

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