This article 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$59
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 risks. Such risks are typically ignored or downplayed by planners and
decision makers, to the detriment of social and economic welfare. For nine out
of ten rail projects passenger forecasts are overestimated; average
overestimation is 106 percent. This results in large benefit shortfalls for
rail projects. For half of all road projects the difference between actual and
forecasted traffic is more than plus/minus 20 percent. 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. 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
transparency, accountability, and new forecasting methods. The challenge is to
change the governance structures for forecasting and project development. The
article shows how planners may help achieve this.Comment: arXiv admin note: text overlap with arXiv:1302.2544, arXiv:1303.6571,
arXiv:1302.364