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

Author(s)
FRIDSTROEM, L & INGEBRIGTSEN, S
Year
Abstract

The determinants of personal injury road accidents and their severity are studied by means of generalized Poisson regression models estimated on the bais 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. Separateprobability 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.(A) This paper was published in a special issue of Accident Analysis and Prevention entitled 'Theoretical models for traffic safety' and for the covering abstract see IRRD 846002.

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Publication

Library number
I 846011 IRRD 9201
Source

ACCIDENT ANALYSIS AND PREVENTION 1991 /10 E23 5 PAG:363-78 T

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