A Regression Model with ARMA Errors to Investigate the Frequency and Severity of Road Traffic Accidents

In this paper, models are developed to explain and forecast the frequency and severity of accidents in Belgium. The objective of this study is to enhance the understanding of the developments in road safety by studying the impact of various explanatory variables on traffic safety. We investigate whether the number of accidents and victims are influenced by weather conditions, economic conditions and policy regulations, and then use the results to predict the frequency and severity of accidents for a 12-months out-of-sample data set. Monthly Belgian data from January 1974 to December 1999 are used in the model, and predictions are made for the year 2000. We use a regression model with ARMA errors to quantify the impact of variables on aggregate traffic safety. The results show a significant effect of weather conditions and laws and regulations, but there seems to be negligible statistical impact of economic conditions on traffic safety. The model can easily be used to forecast traffic safety, as can be seen from the reasonably good fit we obtained on a 95% confidence level. Van den Bossche, Wets and Brijs 3