# Dataset of Trillion Dollar figures

Below I link to a small dataset with 130 figures of over \$1 trillion (e.g. Ap­ple’s Mar­ket cap­i­tal­iza­tion: \$1 trillion, or the value of Global Res­i­den­tial Real Es­tate: \$163 trillion).

If some­thing costs trillions, then it might score highly on the scale crite­ria of some pri­ori­ti­za­tion frame­works. This be­cause even if we have to in­vest billions to some­how save that money, the sav­ings would be huge.

Th­ese num­bers might also be helpful to get a sense of the world econ­omy. For in­stance, World GDP is ~\$100 trillion, and more than half of that is US, China, and EU with a GDP of ~\$20 trillion each.

Also, peo­ple some­times treat big num­bers—billions and trillions—as if they’re all the same (c.f. scale in­sen­si­tivity or scope ne­glect). Even re­searchers some­times con­fuse big num­bers (“Ad­ver­tis­ing has be­come an over \$500-trillion-dol­lar global in­dus­try” (should be billions) or “The benefits of au­to­mated and au­tonomous ve­hi­cles \$1.3 quadrillion” (should be trillions)).

So how can you con­cep­tu­al­ize \$1 trillion? 1 trillion is 1,000 billion. 1 billion is 1,000 mil­lion. Houses of­ten costs ~1 mil­lion. So 1 trillion ≈ 1 mil­lion houses—a whole city.

Some of the figures might be wrong. For in­stance, be­cause I op­ti­mized for se­lect­ing very high figures (I had a Google Scholar alert for things like “USD * trillion”), they are more likely to be in­flated than other num­bers (c.f. op­ti­miz­ers curse).

Also note that not all of these figures are nec­es­sar­ily di­rectly com­pa­rable (some figures are stock and some are flow, some of the large figures are no­tional).

I hope this is in­ter­est­ing or even use­ful to some peo­ple here.

Graph

Googlesheet (with sources)

# Error

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