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This article presents results from the first statistically significant studyof traffic forecasts in transportation infrastructure projects. The sample usedis the largest of its kind, covering 210 projects in 14 nations worth US$59billion. The study shows with very high statistical significance thatforecasters generally do a poor job of estimating the demand for transportationinfrastructure projects. The result is substantial downside financial andeconomic risks. Such risks are typically ignored or downplayed by planners anddecision makers, to the detriment of social and economic welfare. For nine outof ten rail projects passenger forecasts are overestimated; averageoverestimation is 106 percent. This results in large benefit shortfalls forrail projects. For half of all road projects the difference between actual andforecasted traffic is more than plus/minus 20 percent. Forecasts have notbecome more accurate over the 30-year period studied. If techniques and skillsfor arriving at accurate demand forecasts have improved over time, as oftenclaimed by forecasters, this does not show in the data. The causes ofinaccuracy in forecasts are different for rail and road projects, withpolitical causes playing a larger role for rail than for road. The cure istransparency, accountability, and new forecasting methods. The challenge is tochange the governance structures for forecasting and project development. Thearticle shows how planners may help achieve this.

How (In)accurate Are Demand Forecasts in Public Works Projects? The Case of Transportation