Socio-economic cost-benefit analysis (CBA) provides a quantitative measure of the extent to which, over its lifetime, a project or initiative will bring the community benefits that exceed its costs of construction and operation. This report describes efforts to improve the quality of transport CBA and its applicability to decision making. Three areas are addressed in detail: strategies for making the most of CBA, valuing and forecasting reliability benefits, and capturing wider economic impacts. The report is based on the papers and discussions at a roundtable meeting of 30 experts held in Paris in November 2015.

Socio-economic cost-benefit analysis (CBA) is a powerful framework that can be very useful to governments making investment decisions. However the standard application of transport CBA has room for improvement. This chapter describes efforts to improve the quality of transport CBA and its applicability to decision making. Three areas are addressed in detail: strategies for making the most of CBA, valuing and forecasting reliability benefits, and capturing wider economic impacts. The chapter is based on the papers and discussions at a roundtable meeting of 30 experts held in Paris in November 2015. Roundtable participants took the view that a multi-faceted approach is needed to address the shortfalls; CBA theory and practice need to be gradually expanded to incorporate more impacts in the rigorous valuation and forecasting framework; and CBA results need to be more effectively linked to other criteria in the broader decision-making framework, including by bringing in a more diverse evidence base. 1

This chapter provides an overview of some alternative conceptual definitions of travel-time variability, discusses their implications about behaviour, and puts them into a broader context, including deviations from the underlying assumptions regarding rational behaviour. The chapter then discusses the empirical basis for assigning a value to travel-time variability. This discussion leads to the conclusion that a fair amount of scepticism is appropriate regarding stated preference data and that attention should turn to the possibilities that are emerging for using large revealed preference datasets. The bottom line is that travel-time variability is quantitatively important and cost-benefit analysis should account for it, using the best values we can get, in order not to imply a bias towards projects that do not reduce travel-time variability. Omitting the cost of travel-time variability is not the neutral option.

In this chapter we describe how we included travel-time variability in the national Dutch transport forecasting model and the policy impacts of this new forecasting tool. Until now, traveltime reliability improvements for road projects were included in Dutch cost-benefit analysis (CBA) by multiplying the travel-time benefits from reduced congestion by a factor 1.25. This proportionality is based on the linkage between congestion reduction and reliability improvements. However, this treatment of reliability is not useful to evaluate policies that especially affect traveltime variability. From the start, this method was provisional and meant to be replaced by a better method capturing travel-time variability. For this, we derived an empirical relation between the standard deviation of travel time, mean delay of travel time and length of route. This has been implemented in the national Dutch model as a post processing module. The new travel-time reliability forecasting model will be incorporated in the Dutch guidelines for CBA. 1

Transport project prioritisation and selection processes require consideration of many aspects of costs, intended benefits and other impacts. Economic analysis methods can measure many of those factors, though the analysis methods must be specified in ways that meet the information needs of decision-makers. This chapter examines how cost-benefit analysis, economic impact analysis and multi-criteria analysis approaches have evolved and been applied to address the specific form of governmental decision processes that exist in the U.S. and some other countries. It discusses how “ex-post” case studies and associated statistical studies of have been promoted and utilised to both inform and refine “ex-ante” evaluation methods. It concludes by discussing the advantages, limitations and trade-offs involved in the use of this approach for transport project decision making.

This chapter analyses three main mechanisms through which transport improvements have impacts that deliver real income gain over and above user-benefits. One is economic density and productivity, a second is induced private investment and associated land-use change, and a third is employment effects. There are relatively well-established methodologies for incorporating the first and third of these in cost-benefit appraisal, and these methodologies are reviewed in the chapter. For the second, the chapter outlines how transport induced investments can create consumer surplus, and describes a method for quantifying this in cost-benefit appraisal. Data issues encountered in implementing these methods are discussed.