Exposure is a key variable in traffic safety research. In the literature, it is noted as the first and primary determinant of traffic safety. In many cases, however, no valid exposure measure is available. In Belgium, we have access to monthly traffic counts for 12 years. This offers the opportunity to investigate the added value of exposure in our models, next to legal, economic and climatologic variables. Multiple regression with ARMA errors is used to quantify the impact of these factors on aggregated traffic safety. For each dependent variable, a model with and without exposure is constructed. The models show that exposure is significantly related to the number of accidents with persons killed and seriously injured and to the corresponding victims, but not to the lightly injured outcomes. Moreover, the addition or deletion of exposure does not influence the effects of the remaining variables in the model. The effects of exposure clearly depend on the type of measure used, and on the time horizon considered. The framework of a regression model with ARMA errors allows for missing variables being accounted for by the error term. Even without a variable like exposure, valid models can be constructed.