Crisis chart of the day: The correlation between severity and probability

By Felix Salmon
January 14, 2010
released its annual Global Risks report, which kicks off with this chart:

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The World Economic Forum has released its annual Global Risks report, which kicks off with this chart:


There’s a key explaining what all these numbers are, ranging from 1 (food price volatility) to 36 (data fraud/loss). But the really scary thing, for me, is the pretty clear positive correlation between severity and likelihood: the trillion-dollar risks all have a significant probability of happening, with the most severe risk of all — a global asset price collapse — being associated with a probability of well over 20%.

That collapse in asset prices is #6; #7 (developed-country retrenchment from globalization) is just as severe, if not as likely. #2 is a spike in the oil price, #5 is fiscal crises, #31 is chronic diseases, and #4 is a slowing Chinese economy.

The report is being published in the run-up to the WEF’s annual meeting, in Davos, where the great and the good will try to convince themselves that they’re part of the solution rather than being part of the problem. But frankly there’s really nothing they can do about the biggest risk of all, that asset-price collapse. In fact, given how rich they are, they’re likely to bear the brunt of it themselves.

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One comment so far

Cute chart, Felix. On page 38 of the report it starts to describe how they generated it:

The Global Risks Landscape

The visualisation of risk on the landscape places risks
by severity of impact (measured in US$) on the vertical
axis and the likelihood of occurrence on the horizontal
axis over a 10-year time horizon. The numerical
assessment of these categories of risks is created
through qualitative assessment by the partners of the
report. The risks which appear in the upper right-hand
corner are those with the highest impact and highest
likelihood and are the focus of the narrative of this

I’m a statistician by trade. Whenever I see a nifty graph, I think: “Wow, how would you generate a graph like that?” This was one of those graphs.

Surveying expert opinion is sometimes the best method for generating data because there is no other reasonable option. But expert opinion is prone to biases — man is a social creature; even scientists are prone to the biases of their peers, much more the rest of us.

As a result, I wouldn’t give this graph too much weight. If the experts are generally right, it will indicate some weak tendency toward the result, but as for numbers, I would be reluctant to put one significant figure, much less two sig figs.

One other note: I think the timespan of the figures in the report are meant to span the next 10 years. That is an aid toward understanding what their hypothetical probabilities mean.

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