A comprehensive joint econometric model of motor vehicle crashes arising from multiple sources of risk

The multiple risk source model significantly outperformed the single risk source model in terms of prediction ability and goodness of fit measures. In addition, while the single risk source model predicts total crash counts for individual sites, the multiple risk source model predicts crash count proportions contributed by each source of risk, and predicts crashes by risk source. The improvement in fit combined with the theoretical appeal of a multiple risk source model to explain unobserved heterogeneity in crashes suggests-at least for the sample used in the study-that the complexity in crash occurrence is better explained using multiple equation linear predictors. Further research should examine other datasets for repeatability and should further explore and test risk sources.