I recently found that Lloyd's has a number of interesting resources on risk. One is the City Risk Index, the methodology for which comes from Cambridge's Judge Business School.

The key metric is something they call GDP@Risk. Despite the name, it is not simply an application of Value@Risk to GDP. Instead, it is simply the sum of the expected damage from a given threat (or from a set of threats) during a given time period. In this case, the time period is 2015-2015. The threats considered include manmade ones (e.g., cyber attack, oil price shock) and natural ones (e.g., drought, solar storm). The site includes brief case studies for the threats. For example, the "plant epidemic" study focuses on the demise of the Gros Michel banana:

Event: Panama disease outbreak, 1950s

Location: Latin America

Economic cost: Estimated losses across Latin America were around $400m ($2.3bn today) although this figure does not include any of the economic losses caused by unemployment, abandoned villages and unrealised income in the affected region.

Description: The Fusarium oxysporum cubense fungus was first diagnosed in Panama but quickly travelled across Central America.

Damage: The disease wiped out the Gros Michel banana, the principal cultivar at the time, from plantations across the region. Between 1940 and 1960, around 30,000 hectares of Gros Michel plantations were lost in the Ulua Valley of Honduras, and in a decade 10,000 hectares were lost in Suriname and the Quepos area of Costa Rica.

Insight: Gros Michel was replaced in the 1960s by Cavendish, a variety thought to be resistant to the disease. However, a new strain of the pathogen was found to be attacking Cavendish plantations in Southeast Asia in the early 1990s. It has since spread, destroying tens of thousands of hectares across Indonesia and Malaysia, and costing more than $400m in the Philippines alone. There is concern that it could reach Central America and destroy up to 85% of the world’s banana crop. Solutions to contain the disease could include increasing genetic diversity among banana cultivars and developing hybrid varieties with stronger resistance.

As the name implies, the site quantifies risks from these threats at the city level. So which cities are the most at risk from a plant epidemic? They're all in APAC:

  • Hong Kong ($3.83b)
  • Shanghai ($2.89b)
  • Beijing ($2.38b)
  • Bangkok ($2.22b)
  • Jakarta ($2.09b)

These account for 1/6 of the plant-epidemic risk across all 301 cities ($75b).

Which cities are the most "at risk," all threats considered? Once again, APAC dominates, but with a different set of cities:

  • Taipei
  • Tokyo
  • Seoul
  • Manila
  • New York (not APAC of course)

This kind of information is interesting. It may even be useful as an approximate indication of where to focus risk mitigation efforts. But without more detail (probability distributions? second-order interaction effects? etc.) it's hard to see what role it would play in a serious risk analysis, existential or commercial or otherwise.

Coda: Despite their application to less-than-existential risks and the superficiality of this particular resource (it is a marketing tool for Lloyd's, after all), perhaps existential riskologists could benefit from looking at the insurance industry. Has this already been done?

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It's interesting that they do have a cyber-attack section, but it's also noteworthy that a global pandemic puts at risk only half the GDP of a market crash.

Presumably the computers won't get sick :).

Lloyds also has good reports on things like Coronal Mass Ejections and similar mid-range risks; eg: https://www.lloyds.com/~/media/lloyds/reports/emerging-risk-reports/solar-storm-risk-to-the-north-american-electric-grid.pdf

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perhaps existential riskologists could benefit from looking at the insurance industry

Well, the insurance industry is mostly concerned with pricing risks. Most of its money is allocated to diversifiable risk that we understand very well -- life, fire, accidents, etc. Even for pretty-common-but-not-too-frequent risks like hurricanes, the insurance industry's record is mixed: a single bad hurricane season can lead to large losses (and a good one can lead to large profits, of course).

For unique, poorly-estimable risks the insurance industry had strong incentive to overprice them and so its estimates should not be considered unbiased.

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Fixed, thanks.

For unique, poorly-estimable risks the insurance industry had strong incentive to overprice them

Plausible, and one should certainly beware of biases like this. On the other hand, given conventional assumptions regarding the competitiveness of markets, shouldn't prices converge toward a rate that is "fair" in the sense that it reflects available knowledge?

On the other hand, given conventional assumptions regarding the competitiveness of markets, shouldn't prices converge toward a rate that is "fair" in the sense that it reflects available knowledge?

That requires a market. And even if you have one, the further that real-life market is away from the abstract free market, the less prices converge to cost + usual profit.

I suspect that there is no market for unique, poorly-estimable risks.

And even if you have one, the further that real-life market is away from the abstract free market, the less prices converge to cost + usual profit.

True.

I suspect that there is no market for unique, poorly-estimable risks.

That's probably true for most such risks, but it's worth noting that there are markets for some forms of oddball events. One example is prize indemnity insurance (contest insurance).