Economic evaluation of road safety measures

A great deal of effort is still needed to improve road safety in Europe. As well as assigning responsibilities and a systematic approach, optimum use of available resources is also required. For this last item, knowledge, methods and techniques developed by the economic sciences can be used. Firstly, criteria have been formulated which can be used to determine whether there is sufficient need for government intervention in traffic and road safety. Analysis shows that there are different reasons: safety is a 'merit good', the external costs of accidents have not been completely internalized, the consequences of accidents are sometimes unfairly divided, a road system is a 'public good', has external benefits and has large indivisible production units, and safety is a qualitative aspect in terms of construction, maintenance, and management of such a road system by the government. Secondly, evaluation tools have been developed to (1) determine the optimum size of the total government budget for road safety policy and (2) to find out how a given budget can be optimally employed in drawing up a package of measures. The method of social cost-benefit analysis is suitable for both objectives, cost-effectiveness analysis is only appropriate for the second objective. To determine who will be affected by the advantages and disadvantages, a supplementary redistribution analysis can be carried out. To test the robustness of the figures (particularly with regard to the effects of policy alternatives investigated) a sensitivity analysis can be done. To apply a social cost-benefit analysis, information is needed to quantify all the effects and put a monetary value to each. A portion of this information is also needed for a cost-effectiveness analysis. In practice, not all the necessary information will usually be available, so the optimum size of the road safety budget and/or the optimum composition of a package of measures cannot be determined using these methods. Nonetheless, decision-makers can still be supported by information about the costs and effects of measures that is available. With the help of non-monetary methods, like the 'goals achievement matrix' and the scorecard, this information can be classified and processed for decision-makers. This puts them in a better position to rank policy alternatives; an assessment of efficiency is not possible however.