The Mercury News is reporting a new study by the US Geological Survey that predicts “California faces a 99.7 percent chance of big quake by 2037.”
How the notion of “probability” is interpreted in these studies is a mystery. The power-law tails on these processes have a very low exponent and the ability to calibrate the probability in the tails shrinks very fast as one moves down the tail.
D. A. Freedman and P.B. Stark at Berkeley looked at this problem in a paper titled “What is the chance of an earthquake?” This 2001 paper studied an earlier similar forecast.
From the paper, on the probability forecast:
There is no straightforward interpretation of the USGS probability forecast. Many steps involve models that are largely untestable; modeling choices often seem arbitrary. Frequencies are equated with probabilities, fiducial distributions are used, outcomes are assumed to be equally likely, and sub jective probabilities are used in ways that violate Bayes rule.
…and:
Philosophical difficulties aside, the numerical probability values seem rather arbitrary.
They conclude with this:
Probabilities are a distraction. Instead of making forecasts, the USGS could help to improve building codes and to plan the government’s response to the next large earthquake. Bay Area
residents should take reasonable precautions, including bracing and bolting their homes as well as securing water heaters, bookcases, and other heavy objects. They should keep first aid supplies, water, and food on hand. They should largely ignore the USGS probability forecast.
Invest in preparation instead of building models and forecasting rare events. This false precision is dangerous if it informs decision making.
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