AN AGGREGATE ACCIDENT MODEL BASED ON POOLED, REGIONAL TIME-SERIES DATA

The determinants of personal injury road accidents and their severity are studied by means of generalized Poisson regression models estimated on the basis of combined cross-section/ time-series data. Monthly data have been assembled for 18 Norwegian counties (every county but one), covering the period from January 1974 until December 1986. A rather wide range of potential explanatory factors are taken into account, including road use (exposure), weather, daylight, traffic density, road investment and maintenance expenditure, accident reporting routines, vehicle inspection, law enforcement, seat belt usage, proportion of inexperienced drivers, and alcohol sales. Separate probability models are estimated for the number of personal injury accidents, fatal accidents, injury victims, death victims, car occupants injured, and bicyclists and pedestrians injured. The fraction of personal injury accidents that are fatal is interpreted as an average severity measure and studied by means of a binomial logit model. © 1991.