Cost-benefit analysis has been applied in this report to assess the benefits and costs of road safety measures and road safety strategies. It is important, however, to keep in mind that the application of cost-benefit analysis to analyse policy options relies on a number of assumptions.
Cost-benefit analysis has been used for at least twenty five years to help in setting priorities for road safety measures. The use of cost-benefit analysis in road safety policy making has, however, remained controversial. Not everybody accepts the idea that putting a monetary value on life and limb is ethically defensible, or in any way helpful in the task of developing an effective road safety programme.
Others, while accepting that there is a legitimate role for cost-benefit analysis, are sceptical because they think that the estimates of accident costs, in particular the valuation of quality of life, are too uncertain to give reliable guidance.
It would go beyond the scope of this report to discuss all the objections to cost- benefit analysis in detail. However, the basic principles of cost-benefit analysis will be stated, to give readers the opportunity to make up their own minds about whether they accept these principles or not.
Applied welfare economics supplies the basic principles of cost-benefit analysis.
There are four main principles: Consumer sovereignty, welfare maximisation, valuation of goods according to willingness-to-pay, and neutrality with respect to distributive outcomes. The principle of consumer sovereignty, briefly stated, means that welfare is defined in terms of how consumers choose to spend their income between commodity bundles. The right of consumers to choose how to spend their income is respected. The strength of consumer preferences for the provision of various public goods is measured by the amount of money that consumers are willing to pay for these goods. Various techniques have been developed to assess willingness to pay for non-marketed goods. It is beyond the scope of this report to discuss these techniques in detail.
The objective of cost-benefit analysis is welfare maximisation. To determine whether a project increases welfare or not, cost-benefit analysis relies on the Pareto-criterion. This criterion states that welfare is increased when a change makes at least one person better off and nobody worse off. In practice, many public projects will make some people better off and others worse off. Hence, the Pareto criterion is not very practical. Most economists therefore subscribe to a less demanding criterion of welfare maximisation, stating that welfare is increased when a potential Pareto improvement occurs. A project satisfies this criterion when those who benefit from it can compensate those who lose from it (in utility terms) and still retain a net benefit (in utility terms). In practice, a project is
regarded as satisfying this criterion when benefits are greater than costs. There is, however, no requirement that actual compensation of those who lose takes place.
Cost-benefit analysis is neutral with respect to distributive outcomes. What counts is the aggregate size of benefits and costs, not how these impacts are distributed between various groups of the population.
The monetary valuation of a non-marketed good in cost-benefit analysis should be based on the willingness-to-pay of the potential purchasers of the good. There are many ways of estimating the monetary value of a good not provided by the market. One way of doing it, is to set up a hypothetical market, in which people are asked to state their willingness-to-pay for a certain amount of the good, or choose between various options that provide different amounts of the good.
Another way of estimating the value of a non-marketed good is to study the choices people make when the probability of sustaining a fatal injury has to be traded off against other values, at least one of which is denominated in monetary terms. Workers, for example, face a choice between occupations that differ with respect to wages and fatality risk (as well as numerous other attributes). There is a host of methodological pitfalls in such studies. It would go beyond the scope of this report to discuss all these difficulties in detail. An essential assumption made in all techniques designed to estimate the monetary value of non-marketed goods, is that the choices made by individuals can be adequately modelled by relying on the principle of utility maximisation. If individuals are not rational utility
maximisers, the values estimated for non-marketed goods may be wrong, or at least highly uncertain.
Cost-benefit analysis is designed to help decision makers set the priorities that will maximise overall goal achievement in situations where there are several policy objectives that have to be traded off against each other. Relevant policy objectives typically include improving road safety, improving mobility, reducing transport costs and improving the environment. Each policy objective may consist of several sub-targets, like those of reducing noise, reducing air pollution and improving visual amenity, all subsumed under the objective of improving the environment.
Although the hierarchy of policy objectives may consist of many levels, it is assumed that, at the most basic level, each objective is unitary in the sense that the value of realising it can be adequately expressed in monetary terms. Is this assumption reasonable? There is evidence to suggest that “improving road safety”
is not a unitary policy objective in this sense, but has many dimensions, not all of which can be adequately represented by assigning a monetary value to life and limb. Consider the following possible interpretations of a target of improving road safety:
1 Reducing the absolute number of accidents and injuries.
2 Reducing the average risk of road accident injury per kilometre travelled or per inhabitant.
3 Reducing the severity of injuries, by reducing the probability of death or serious injury when involved in an accident.
4 Reducing the difference in accident risk between different groups of road users, in particular reducing the high risk of injury for pedestrians and cyclists.
5 Reducing the probability of accidents in which a large number of people can be killed or injured, such as bus accidents or accidents involving hazardous goods.
6 Reducing the insecurity (anxiety) some groups of road users feel, particularly to the extent that insecurity prevents people from travelling where and when they want to.
It is obvious that some of these targets can be mutually conflicting. Costing accidents in the conventional manner can accommodate targets 1 and 3, and perhaps target 2. Targets 4 and 5 require a different approach to accident costing.
For target 4, costs that are proportional to the accident rate per kilometre of travel might be used. For target 5, functions are needed that take account of the fact that 20 fatalities in one accident count for more than 20 fatalities occurring one by one in 20 different accidents.
Whether target 6 is accommodated by standard accident costs or not, is a matter of interpretation. If the desire to avoid insecurity is part of the reason why people are willing to pay something to prevent accidents, it can be argued that this aspect of road safety is included in cost estimates based on the willingness-to-pay principle.
In general, one would expect the fear of having an accident to be one of the factors that influences willingness to pay for reduced risk. If this interpretation is accepted, it would constitute double counting to add an extra value of reduced insecurity to accident costs in evaluating projects that are believed to reduce insecurity. On the other hand, insecurity is not simply a function of statistical risk, but is likely to contain additional elements. It would therefore probably be wrong to simply assume that the entire benefit of feeling more secure is included in accident costs. One would need to obtain a separate value of security in order to be certain that this item is given sufficient weight in a cost-benefit analysis.
Some policy objectives are by their very nature unsuitable for cost-benefit analysis. This is particularly true of distributive objectives. An important
distributive objective for transport policy in Sweden and many other countries has been to provide a certain minimum standard for transport facilities in all parts of the country, regardless of traffic volume. This means that the regional distribution of road investments and the standard of roads is an important policy objective.
This often means that a disproportionate amount of investments are carried out in areas with little traffic, compared to the share of investments that would benefit these areas if funds were allocated on the basis of the returns earned on
investments. In short, road investments in sparsely populated areas are not performed because they earn a good return, but despite the fact that the return on these investments is often very low.
To summarise, the current state of the art with respect to the use of cost-benefit analysis to set priorities for road safety measures can be characterised as follows:
• Cost-benefit analysis comprises many of the policy objectives that are relevant for road safety policy, but is unlikely to comprise all relevant policy
objectives. In particular the objectives of balancing regional development and reducing the differences in accident rate between protected and unprotected road users are unlikely to be given due weight within the current framework for cost-benefit analysis.
• It is not clear to what extent the objective of reducing road user insecurity, as well as insecurity among residents along a road is part of the accident costs and thus included in current cost-benefit analyses.
• According to the cost-benefit analyses made in this report, measures that have a potential of reducing the number of fatalities by nearly 25% are not efficient, in the sense that benefits are smaller than costs. Abstaining from introducing these measures by referring to cost-benefit analyses is inconsistent with the ethical principles underlying Vision Zero.
11.4 Constraints on Road Safety Policy Making – the Power of