Wealth inhomogeneity applied to crash rate theory

A crash rate theory based on corporate economic utility maximization is applied to individual behavior in U.S. and German motorway death rates, by using wealth inhomogeneity data in ten-percentile bins to account for variations of utility maximization in the population. Germany and the U.S. have similar median wealth figures, a well-known indicator of accident risk, but different motorway death rates. It is found that inhomogeneity in roughly the 10(th) to 30(th) percentile, not revealed by popular measures such as the Gini index which focus on differences at the higher percentiles, provides a satisfactory explanation of the data. The inhomogeneity analysis reduces data disparity from a factor of 2.88 to 1.75 as compared with median wealth assumed homogeneity, and further to 1.09 with average wealth assumed homogeneity. The first reduction from 2.88 to 1.75 is attributable to inequality at lower percentiles and suggests it may be as important in indicating socioeconomic risk as extremes in the upper percentile ranges, and that therefore the U.S. socioeconomic risk may be higher than generally realized.