Fun with maps: Visualizing global wealth

By Christopher B. Daly 

Here is a terrific map that uses data visualization to dramatize the disparities in how well-off people are around the world. The map-makers at Worldmapper redrew the size of each country based on its per-capita GDP.

In the map below, several things stand out:

1. The bulging size of the USA compared to other countries.

2. That big purple area on the right is not China but Japan (which is much wealthier per capita).

3. Although it is is geographically huge, Africa practically vanishes (followed closely by South America).

Per-capita GDP by Worldmapper

Per-capita GDP
by Worldmapper

h/t to Vox for pointing to this.

2 Comments

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2 responses to “Fun with maps: Visualizing global wealth

  1. David

    Be careful, as you come close to another example of GDP–Grasping Data Poorly. GDP measures not wealth, but production. Many of the wealthiest countries per capita are not high in GDP–Qatar, Luxembourg, Hong Kong. As GDP does not reflect cost of living, which is important (as any Bostonian knows too well, “wealthy” in Biloxi is not wealthy in Boston), but does reflect exchange rates and prices of such commodities as oil and uranium (which can fluctuate dramatically with enormous impact to GDP but not to typical cost of living).

    That map also appears to have some errors–the US (sixth in per capita GDP) seems too large, in comparison to not only such small but wealthy nations as Singapore and Norway, but Brazil.

    I hope you assign your students Nate Silver’s The Signal and the Noise, which is an excellent primer on how data is constantly misunderstood or distorted–as well as how an unknown young blogging journalist such as Silver could almost overnight become one of the most influential journalists in the US because he understood data.

    Like

    • profdaly

      Excellent points. But, hey: I didn’t design the map. I think it’s a useful approximation, and your inquiries into the methodology are most welcome (and on-point, I believe).

      Like

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