Monetary valuation of the environmental impacts of road transport : a stated preference approach

The impact of road transport and road transport infrastructure on the environment is an important public issue in the United Kingdom today. Economists have suggested that the present Trunk Road appraisal process undervalues the environmental impact of road schemes because environmental impacts are not included in the monetary cost-benefit process, i.e. they are externalised. Furthermore, critics state that the present evaluation process is complicated by the number and type of qualitative and quantitative measures of environmental impact, this leads to confusion and non-standardisation in the decision-making process. In answer to these criticisms it has been suggested that monetary values of environmental impacts should be incorporated into the Trunk Road appraisal process, i.e. placing environmental benefits or losses into the cost-benefit framework and hence simplifying the decision-making process. This research identified the present methods of monetary valuation, and showed that these have insufficient institutional or public acceptability to be used for the purpose of monetary valuation in this case. This research therefore examined a new methodology for placing values on environmental impacts. i.e. Stated Preference (SP) techniques. SP determines implicit valuations by asking people to trade-off between a number of different choice situations. SP techniques are widely used throughout the transport industry for placing monetary values on factors such as journey time and ride quality. The research was successful in gaining statistically significant monetary values for Road Safety and Air Quality and respondents were able to understand the SP experiments and to trade logically between choice scenarios. However, the research identified that particular care is required when measuring and representing environmental attributes and attribute levels to respondents, as these impact on the valuations gained. Further research is also required to define the reasons for significant variation within the response data. The reasons for this variation need to be investigated further so that significant valuations can be obtained that relate to the whole population.