Advocates of HSR projects need to read this 2006 Danish study by the Department of Development and Planning, Aalborg University, Aalborg. Authors: Bent Flyvbjerga; Mette K. Skamris Holma; Sren L. Buhla. Published in: Transport Reviews, Volume 26, Issue 1 January 2006 , pages 1 – 24
Abstract: This paper presents results from the first statistically significant study of traffic forecasts in transportation infrastructure projects. The sample used is the largest of its kind, covering 210 projects in 14 nations worth US$58 billion. The study shows with very high statistical significance that forecasters generally do a poor job of estimating the demand for transportation infrastructure projects. The result is substantial downside financial and economic risk. Forecasts have not become more accurate over the 30-year period studied. If techniques and skills for arriving at accurate demand forecasts have improved over time, as often claimed by forecasters, this does not show in the data. For nine out of ten rail projects, passenger forecasts are overestimated; average overestimation is 106%. For 72% of rail projects, forecasts are overestimated by more than two-thirds. For 50% of road projects, the difference between actual and forecasted traffic is more than ±20%; for 25% of road projects, the difference is larger than ±40%. Forecasts for roads are more accurate and more balanced than for rail, with no significant difference between the frequency of inflated versus deflated forecasts. But for both rail and road projects, the risk is substantial that demand forecasts are incorrect by a large margin. The causes of inaccuracy in forecasts are different for rail and road projects, with political causes playing a larger role for rail than for road. The cure is more accountability and reference class forecasting. Highly inaccurate traffic forecasts combined with large standard deviations translate into large financial and economic risks. But such risks are typically ignored or downplayed by planners and decision-makers, to the detriment of social and economic welfare. The paper presents the data and approach with which planners may begin valid and reliable risk assessment.
Download PDF. In the study you will learn why rail forecast errors are largely overestimates of traffic, while road forecasts are more balanced about the mean.
Again, the results are highly different for rail and road. For rail projects, the two most important stated causes are ‘uncertainty about trip distribution’ and ‘deliberately slanted forecasts’. Trip distribution in rail passenger forecasts is often adapted to fit national or urban policies aimed at boosting rail traffic. But such policies frequently fail and the result is the type of overestimated passenger forecast which has been documented above as typical for rail passenger forecasting. As regards deliberately slanted forecasts, such forecasts are fabricated by rail promoters to increase the likelihood that rail projects are built (Wachs, 1990). Such forecasts exaggerate passenger traffic and thus revenues. The present authors have shown elsewhere that the massive overestimation of traffic and revenues documented above for rail goes hand in hand with an equally massive underestimation of costs (Flyvbjerg et al., 2002, 2004). The result is cost-benefit analyses of rail projects that are highly inflated, with benefit-cost ratios that are contrived with a view to getting projects accepted and built.
For road projects, the two most often stated causes for inaccurate traffic forecasts are uncertainties about ‘trip generation’ and ‘land-use development’. Trip generation is based on traffic counts and demographic and geographical data. Such data are often dated and incomplete and forecasters quote this as a main source of uncertainty in road traffic forecasting. Forecasts of land-use development are based on land-use plans. What is actually implemented is often quite different from what is planned, however. This, again, is a source of uncertainty in forecasting.
The different patterns in stated causes for rail and road, respectively, fit well with the figures for actual forecast inaccuracies documented above. Rail forecasts are systematically and significantly overestimated to a degree that indicates foul play on the part of rail forecasters and promoters. The stated causes, with ‘deliberately slanted forecasts’ as the second to largest category, corroborate this interpretation, which corresponds with findings by Wachs (1986) and Flyvbjerg et al. (2002). Road forecasts are also often inaccurate, but they are substantially more balanced than rail forecasts, which indicate a higher degree of fair play in road forecasting. This interpretation is corroborated by the fact that deliberately slanted forecasts are not quoted as a main cause of inaccuracy for road traffic forecasts, whereas more technical factors such as trip generation and land-use development are quoted. This is not to say that road traffic forecasts are never politically manipulated. It is to say, however, that this appears to happen less often and less systematically for road than for rail projects. It is also not to say that road projects generally have a stronger justification than rail projects; just that they have less biased forecasts than rail projects.