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Measuring inaccuracy in travel demand forecasting: methodological considerations regarding ramp up and sampling

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  • Flyvbjerg, Bent
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    Abstract

    Project promoters, forecasters, and managers sometimes object to two things in measuring inaccuracy in travel demand forecasting: (1) using the forecast made at the time of making the decision to build as the basis for measuring inaccuracy and (2) using traffic during the first year of operations as the basis for measurement. This paper presents the case against both objections. First, if one is interested in learning whether decisions about building transport infrastructure are based on reliable information, then it is exactly the traffic forecasted at the time of making the decision to build that is of interest. Second, although ideally studies should take into account so-called demand "ramp up" over a period of years, the empirical evidence and practical considerations do not support this ideal requirement, at least not for large-N studies. Finally, the paper argues that large samples of inaccuracy in travel demand forecasts are likely to be conservatively biased, i.e., accuracy in travel demand forecasts estimated from such samples would likely be higher than accuracy in travel demand forecasts in the project population. This bias must be taken into account when interpreting the results from statistical analyses of inaccuracy in travel demand forecasting.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 39 (2005)
    Issue (Month): 6 (July)
    Pages: 522-530

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    Handle: RePEc:eee:transa:v:39:y:2005:i:6:p:522-530

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    References

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    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    1. Hugosson, Muriel Beser, 2005. "Quantifying uncertainties in a national forecasting model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(6), pages 531-547, July.
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    Cited by:
    1. Bent Flyvbjerg, 2013. "Quality Control and Due Diligence in Project Management: Getting Decisions Right by Taking the Outside View," Papers 1302.2544, arXiv.org.
    2. Hugosson, Muriel Beser, 2005. "Quantifying uncertainties in a national forecasting model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(6), pages 531-547, July.
    3. Salling, Kim Bang & Banister, David, 2009. "Assessment of large transport infrastructure projects: The CBA-DK model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(9-10), pages 800-813, November.
    4. Lise Arena & Eamonn Molloy, 2010. "The Governance Paradox in Megaprojects," Post-Print halshs-00721622, HAL.
    5. Mouter, Niek & Annema, Jan Anne & van Wee, Bert, 2013. "Ranking the substantive problems in the Dutch Cost–Benefit Analysis practice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 241-255.
    6. Odeck, James, 2013. "How accurate are national road traffic growth-rate forecasts?—The case of Norway," Transport Policy, Elsevier, vol. 27(C), pages 102-111.
    7. Susilo, Yusak O. & Kitamura, Ryuichi, 2008. "Structural changes in commuters' daily travel: The case of auto and transit commuters in the Osaka metropolitan area of Japan, 1980-2000," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 95-115, January.
    8. Athias, Laure & Nunez, Antonio, 2008. "The more the merrier? Number of bidders, information dispersion, renegotiation and winner’s curse in toll road concessions," MPRA Paper 10539, University Library of Munich, Germany.
    9. Sevcíková, Hana & Raftery, Adrian E. & Waddell, Paul A., 2011. "Uncertain benefits: Application of Bayesian melding to the Alaskan Way Viaduct in Seattle," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 540-553, July.
    10. 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.
    11. Chantal C. Cantarelli & Bent Flybjerg & Eric J. E. Molin & Bert van Wee, 2013. "Cost overruns in Large-Scale Transportation Infrastructure Projects: Explanations and Their Theoretical Embeddedness," Papers 1307.2176, arXiv.org.
    12. Olsson, Nils O.E. & Krane, Hans Petter & Rolstadås, Asbjørn & Veiseth, Mads, 2010. "Influence of reference points in ex post evaluations of rail infrastructure projects," Transport Policy, Elsevier, vol. 17(4), pages 251-258, August.
    13. Sciara, Gian-Claudia, 2012. "Financing congressional earmarks: Implications for transport policy and planning," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1328-1342.
    14. Pavithra Parthasarathi & David Levinson, 2008. "Post-Construction Evaluation of Traffic Forecast Accuracy," Working Papers 201005, University of Minnesota: Nexus Research Group.

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