Probabilistic Analysis of the Economic Impact of Earthquake Prediction Systems
Tiffany Nicole Kolba
Valparaiso University
Ruyue Yuan
Valparaiso University
Abstract
In order to study the economic impact of an earthquake prediction system, we use probabilistic methods to model the expected cost per life saved from a prediction system. We improve upon previous work by directly modeling the expected cost per life saved rather than using the ratio of the expected cost to the expected number of lives saved, which we show is always an underestimate. The model is applied numerically to the San Francisco Bay area and the expected cost per life saved from an earthquake prediction system over a 50 year period is found to be $3.3 million. While the amount is quite high, it is substantially lower than the corresponding expected cost per life saved of $6.3 million from expenditures in earthquake engineering to improve building codes. Therefore, we conclude that earthquake prediction systems provide a valuable public good.
Author Biographies
Tiffany Nicole Kolba, Valparaiso University
Department of Mathematics and Statistics, Assistant Professor
Ruyue Yuan, Valparaiso University
Ruyue Yuan graduated from Valparaiso University in May 2015 with a B.S. in mathematics. She completed an REU in combinatorics at East Tennessee State University during Summer 2013 and participated in the Budapest Semester in Mathematics during Fall 2014. She will be entering a PhD program in mathematics at the University of Florida in Fall 2015.
