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Are public transit investments based on accurate forecasts? An analysis of the improving trend of transit ridership forecasts in the United States

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  • Hoque, Jawad Mahmud
  • Zhang, Ian
  • Schmitt, David
  • Erhardt, Gregory D.

Abstract

Historically, forecasts of travel demand on public transit infrastructures have been found to be optimistically biased. However, there has been a lack of data available for statistically significant analysis of factors affecting the accuracy. This paper analyzes the overall trend of transit ridership forecast accuracy in the US and contextualizes it with ridership trends based on the largest yet database of 164 large-scale transit infrastructure projects in the US. We find that transit ridership is about 24.6 % lower than forecast on average with about 70 % of the projects over-predicting ridership. Forecast accuracy varies by mode, service area characteristics, familiarity with transit, ramp up period, and time span. The accuracy has been getting better over the years, particularly after 2000 with the introduction of new analytical and evaluation tools as part of the Capital Investment Grants program. Projects that have been forecasted since 2000 have average ridership about 22 % lower than forecast, compared to about 52 % lower from pre-2000. The steadily improving accuracy, however, is offset by the unexpected decline in transit ridership since 2012. Advent of ride-hailing services and improved socio-economic trends that support auto-oriented cities have prompted this decline in ridership and have affected their forecasts as well. Despite the improving trend, we find that there remains substantial deviation in the outcomes from their forecasts. This points to the need of better scrutiny of model inputs and specifications and how they interact with the built environment to unearth the underlying reasons for inaccuracy. Planners and policymakers may make use of our results to advocate for considering the uncertainty around forecasts for any project and funding decision.

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  • Hoque, Jawad Mahmud & Zhang, Ian & Schmitt, David & Erhardt, Gregory D., 2024. "Are public transit investments based on accurate forecasts? An analysis of the improving trend of transit ridership forecasts in the United States," Transportation Research Part A: Policy and Practice, Elsevier, vol. 186(C).
    • Handle: RePEc:eee:transa:v:186:y:2024:i:c:s0965856424001903
    DOI: 10.1016/j.tra.2024.104142
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    References listed on IDEAS

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    1. Kenneth Button & Soogwal Doh & Matthew Hardy & Junyang Yuan & Xin Zhou, 2010. "The Accuracy Of Transit System Ridership Forecasts And Capital Cost Estimates," Articles, International Journal of Transport Economics, vol. 37(2).
    2. Bent Flyvbjerg, 2007. "Policy and Planning for Large-Infrastructure Projects: Problems, Causes, Cures," Environment and Planning B, , vol. 34(4), pages 578-597, August.
    3. 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.
    4. Erhardt, Gregory D. & Hoque, Jawad Mahmud & Goyal, Vedant & Berrebi, Simon & Brakewood, Candace & Watkins, Kari E., 2022. "Why has public transit ridership declined in the United States?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 161(C), pages 68-87.
    5. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    6. Morten Skou Nicolaisen & Patrick Arthur Driscoll, 2014. "Ex-Post Evaluations of Demand Forecast Accuracy: A Literature Review," Transport Reviews, Taylor & Francis Journals, vol. 34(4), pages 540-557, July.
    7. Hoque, Jawad Mahmud & Erhardt, Gregory D. & Schmitt, David & Chen, Mei & Wachs, Martin, 2021. "Estimating the uncertainty of traffic forecasts from their historical accuracy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 339-349.
    8. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    9. Michelle L. Barnes & Anthony W. Hughes, 2002. "A quantile regression analysis of the cross section of stock market returns," Working Papers 02-2, Federal Reserve Bank of Boston.
    10. Yong Zhao & Kara Maria Kockelman, 2002. "The propagation of uncertainty through travel demand models: An exploratory analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 36(1), pages 145-163.
    11. Odeck, James & Welde, Morten, 2017. "The accuracy of toll road traffic forecasts: An econometric evaluation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 73-85.
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