The Default Line by Faisal Islam

Author:Faisal Islam [Islam, Faisal]
Language: eng
Format: epub
ISBN: 9781781854099
Publisher: Head of Zeus, Ltd.

Earthquakes real and earthquakes economic

California is used to tremors. The 1906 earthquake in San Francisco is the most famous of many. Oldrich Vasicek remembers the 1989 quake, when buildings started to make faces and whole panes of glass crashed down onto the street. ‘You can see the temperament of different people,’ he says. ‘Some rushed out of the buildings crazily, some hid under the table. I myself am a complete fatalist.’ He recalls a meeting of the loan committee at Wells Fargo HQ on Montgomery Street in the mid-1970s, just a few years after he was forced out of Czechoslovakia following the 1968 Soviet invasion. At Wells Fargo they were trying to push through a hike of 3 per cent in interest rates on car loans. A big quake came, the room on the sixteenth floor of the skyscraper swayed, floating on a bed of sand. And when the aftershocks stopped, the committee reconvened. Perhaps disturbed by the interjection of plate tectonics, the hawks on the committee backed down, and the car loan rates were frozen at 13 per cent.

But in the engineering of a Montgomery Street skyscraper, or even in the construction of the Del Monte mill that survived the 1906 quake, there are lessons to be learnt about probability and risk. Earthquake losses have fat tails – one might say obese tails. This refers to the curve of probabilities of various losses from an earthquake.

The most famous version of such a chart is the bell curve, which represents the so-called normal distribution (also known as the Gaussian distribution). Such a curve, in the shape of a bell, is the core of modern statistics. The bell-shaped curve illustrates how certain kinds of variables (such as human height, weight and arm length) are predictably and evenly dispersed around an average. Variance around this average is called the standard deviation or sigma. The further one gets away from this average, up or down, taller or shorter, heavier or lighter, longer or smaller, the less likely is that outcome, until it basically becomes impossible. In a normal distribution, the thin tail tapers away exponentially to zero as the event rapidly becomes more improbable. Earthquakes, it turns out, are far from normally distributed. The upper tail is fat.

If earthquakes were normally distributed, it would be possible to calculate definitively the probability of significantly larger-than-average tremors. The probability of a so-called four-sigma catastrophe (which means four standard statistical deviations away from the average) would be just 0.003 or 1 in 33,000. If that were the case, the people of San Francisco could rest a little easier and might even risk working or living in a warehouse without a steel-reinforced roof. In reality, the fat tail means that the four-sigma catastrophe is fifty-one times more likely than a normal distribution suggests. A 2008 Harvard University study used US Geological Survey data to show that deaths from earthquakes have fat tails. The highest number of deaths, around 283,100, was from a 9.0 magnitude earthquake off the west coast of Sumatra in 2004.

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