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Inaccuracy in Traffic Forecasts

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  • Bent Flyvbjerg
  • Mette K. Skamris Holm
  • Søren L. Buhl

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.

Suggested Citation

  • Bent Flyvbjerg & Mette K. Skamris Holm & Søren L. Buhl, 2005. "Inaccuracy in Traffic Forecasts," Transport Reviews, Taylor & Francis Journals, vol. 26(1), pages 1-24, April.
  • Handle: RePEc:taf:transr:v:26:y:2005:i:1:p:1-24
    DOI: 10.1080/01441640500124779
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    File URL: http://hdl.handle.net/10.1080/01441640500124779
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    References listed on IDEAS

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    1. Leavitt, Dan & Ennis, Sean & McGovern, Pat, 1993. "The Cost Escalation of Rail Projects: Using Previous Experience to Re-Evaluate the CalSpeed Estimates," University of California Transportation Center, Working Papers qt2rt1w7xj, University of California Transportation Center.
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    Cited by:

    1. Fullerton, Thomas M., Jr. & Mukhopadhyay, Somnath, 2013. "Border Region Bridge and Air Transport Predictability," MPRA Paper 59583, University Library of Munich, Germany, revised 11 Jul 2013.
    2. Paul Timms, 2008. "Transport models, philosophy and language," Transportation, Springer, vol. 35(3), pages 395-410, May.
    3. Trefor Williams, 2002. "Predicting completed project cost using bidding data," Construction Management and Economics, Taylor & Francis Journals, vol. 20(3), pages 225-235.
    4. Hironori Kato & Yuichiro Kaneko & Masashi Inoue, 2010. "Comparative analysis of transit assignment: evidence from urban railway system in the Tokyo Metropolitan Area," Transportation, Springer, vol. 37(5), pages 775-799, September.

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