Cost benefit analyses and policy development
As has been mentioned before, it is not always possible – indeed not always wise – to base road safety policy strictly on cost-benefit analyses, i.e. to implement all those, and only those, road safety measures that pass the cost-benefit test.
In the study of barriers to the use of efficiency assessment tools in road safety policy performed as part of the ROSEBUD thematic network , one of the questions that was asked to 83 road safety policy makers across Europe was the following:
Do politicians put more weight on the number of fatalities and injuries prevented than on the monetary valuation of these impacts?
A total of 70 answers were given to this question. 40 respondents answered that politicians assigned a greater weight to the number of fatalities or injuries prevented than to the benefits of preventing fatalities or injuries as stated in economic terms.
This may perhaps seem a bit puzzling. After all, the monetary valuation of all relevant impacts of a measure will, ideally, reflect its impacts on fatalities or injuries. It is not necessarily the case, however, that those road safety measures that have the most favourable benefit-cost ratios will also be those that contribute to the greatest reductions in the number of fatalities or injuries. It could be the case that measures whose benefits only marginally exceed the costs will produce the greatest improvement of road safety, may be even a greater improvement than, say, ten very highly cost-effective measures that influence small target groups.
Figure 3 probes if this is the case for the road safety measures included in the impact assessment for Norway quoted above 
Figure 3: Relationship between estimated fatality reduction and benefit-cost ratio for road safety measures in Norway
Taking all measures into consideration, there is no correlation between the size of the estimated fatality reduction and benefit-cost ratio. Yet, as indicated by the dotted line close to the most outward data points in the figure, a tendency can be seen for the measures producing the greatest reductions in fatalities to have the lowest benefit cost ratio. The mean benefit-cost ratio for measures that may reduce the number of fatalities by more than 20 is 2.20. The corresponding mean value is 3.25 for measures that can reduce the number of fatalities by between 10 and 20, and 2.99 for measures that can reduce the number of fatalities by less than 10. There thus seems to be a tendency, although not very strong, for the most cost-effective measures to have the smallest effects on the number of road accident fatalities. This may be felt as a dilemma for policy makers, in particular if Vision Zero is the basis for road safety policy, as is the case in Norway. The paramount criterion for setting priorities according to Vision Zero should be the size of the reduction in the number of fatalities.
It is not just the size of the safety effect that may compete with economic efficiency as a criterion for priority setting. Some policy makers regard pedestrians and cyclists as disadvantaged groups in the current transport system and want to favour these groups. A difficult trade-off arises if the most cost-effective measures mainly benefit motorists, rather than pedestrians or cyclists.
To investigate if this is actually the case, the estimated first order reduction in the number of fatalities of each road safety measure have been allocated between motorists and pedestrians or cyclists. The basis for allocating safety benefits between these groups of road users is analyses of Norwegian accident statistics, performed as part of the preparation of new guidelines for road accident black spot management in Norway . Figure 4 shows the relationship between the proportion of the estimated fatality reduction benefiting pedestrians or cyclists and benefit-cost ratio for the measures included in the road safety impact assessment.
Figure 4: Relationship between proportion of estimated fatality reduction benefiting pedestrians or cyclists and benefit-cost ratio of road safety measures
As in Figure 3, a dotted line has been drawn around the outer data points in the Figure, suggesting that there is a negative relationship between the proportion of fatality reductions benefiting pedestrians or cyclists and benefit-cost ratio. The (simple) mean benefit-cost ratio for road safety measures for which more than 40% of the fatality reduction benefits pedestrians or cyclists is 2.28. The mean benefit-cost ratio for measures for which between 20 and 40 % of the fatality reduction benefits pedestrians or cyclists is 2.35. Finally, the mean benefit-cost ratio for measures for which less than 20 % of the fatality reductions benefit pedestrians or cyclists is 3.27. This suggests that the most cost-effective measures are those that provide the smallest benefits for pedestrians or cyclists. There may thus be a trade-off between efficiency and equity in road safety policy. Cost-benefit analyses focus only on efficiency, not on equity.
In summary, performing cost-benefit analyses of road safety measures does not eliminate the potential presence of competing criteria for priority-setting, in particular criteria referring to the size of effects on road safety and to the distribution of safety effects between different groups of road users. To the extent policy makers regard such criteria for priority-setting as more relevant than the benefit-cost ratio, actual policy priorities may depart from the results of cost-benefit analyses.