Inaccuracies in Cost and Demand Forecasts

  • Joseph Berechman
Chapter

Abstract

Decisions regarding transport infrastructure investments should rest, at least in theory, on ex-ante cost and demand projections. These serve to determine the size and capacity of the new facility, its design attributes (e.g., number of lanes), the extent of support facilities (e.g., access roads and intersections), as well as expected operational and maintenance costs and revenues (e.g., farebox or tolls). The associated social costs and benefits should likewise be based on empirical estimation. This chapter focuses on how cost and demand projections are to be made and why significant biases commonly enter into the forecasting process. We subsequently ask how these projections are used in reality. We leave a discussion of other external impacts from investments, such as environmental degradation costs and economic development benefits, to Chap.  10.

References

  1. AASHTO. 2013. NY Court: Fraud Lawsuit to Proceed Against Toll Road Firm, July 19. https://www.tsp2.org/2013/07/22/n-y-court-fraud-lawsuit-to-proceeds-against-toll-road-firm.
  2. Algers, S., and M. Beser. 2002. SAMPERS – The New Swedish National Demand Forecasting Tool. In National Transport Models: Recent Developments and Prospects, ed. S. Lundquist and L.G. Mattsson. New York: Springer.Google Scholar
  3. Bain, R. 2009. Error and Optimism Bias in Toll Road Traffic Forecasts. Transportation 36 (5): 469–482.CrossRefGoogle Scholar
  4. ———. 2011. On the Reasonableness of Traffic Forecasts: A Survey of Predictive Capability. Traffic Engineering, and Control 52 (5): 213–217.Google Scholar
  5. Banister, D., and J. Berechman. 2000. Transportation Investment and Economic Development. London: University College London Press.Google Scholar
  6. Banister, D., and M. Thurstain-Goodwin. 2011. Quantification of the Non-transport Benefits Resulting from Rail Investment. Journal of Transport Geography 19 (2): 212–223.CrossRefGoogle Scholar
  7. Ben-Akiva, M., and S. Lerman. 1985. Discrete Choice Analysis: Theory and Application, to Travel Demand. Cambridge, MA: The MIT Press.Google Scholar
  8. Berechman, J. 2009. The Evaluation of Transportation Investment Projects. London and New York: Routledge.Google Scholar
  9. Berechman, J., and L. Chen. 2011. Incorporating Risk of Cost Overruns Into Transportation Capital Projects Decision-Making. Journal of Transport Economics and Policy 45: 83–104.Google Scholar
  10. Berechman, J., and D. Pines. 1991. Financing Road Capacity and Returns to Scale Under Marginal Cost Pricing. Journal of Transport Economics and Policy 25 (2): 177–181.Google Scholar
  11. Boyce, D., and H.C.W.L. Williams. 2013. Forecasting Urban Travel – Past, Present and Future. Cheltenham: Edward Elgar.Google Scholar
  12. Bruzelius, N., B. Flyvbjerg, and W. Rothengatter. 2002. Big Decision, Big Risks—Improving Accountability in Mega Projects. Transport Policy 9: 143–154.CrossRefGoogle Scholar
  13. Cantarelli, C., E. Molin, B. van Wee, and B. Flyvbjerg. 2012. Characteristics of Cost Overruns for Dutch Transport Infrastructure Projects and the Importance of the Decision to Build and Project Phases. Transport Policy 22: 49–56.CrossRefGoogle Scholar
  14. Chow, J., R. Jayakrishnan, and H. Mahmassani. 2012. Is Transport Modeling Education Too Multi-Disciplinary? A Manifesto on the Search of for Its Evolving Identity. In Travel Behavior Research: Current Foundations, Future Prospects, ed. E. Miller and M. Roorda. Raleigh, NC: Lulu Press. www.lulu.com.Google Scholar
  15. Cooper, R. 2014. Why Is it so Expensive to Build a Bridge in America? The Week, March 10. http://theweek.com/article/index/257684/why-is-it-so-expensive-to-build-a-bridge-in-america.
  16. Department for Transport (UK). 2013. Transportation Analysis Guidance: Treatment of Uncertainty in Model Forecasting. Section 3.15.5. http://www.dft.gov.uk/webtag/index.php.
  17. Donnelly, R., et al. 2010. Advanced Practices in Travel Forecasting: A Synthesis of Highway Practice. National Cooperative Highway Research Program Synthesis 406. Washington, DC: Transportation Research Board. www.trb.org.
  18. Estache, A., J. Guasch, A. Iimi, and Trujillo Lm. 2009. Multidimensionality and Renegotiation: Evidence from Transport-Sector Public-Private-Partnership Transactions in Latin America. Review of Industrial Organization 35: 41.CrossRefGoogle Scholar
  19. European Court of Auditors. 2013. Are EU Cohesion Policy Funds Well Spent on Roads? Special Report No. 5, Luxembourg: European Court of Auditors. http://eca.europa.eu.
  20. Federal Transit Administration. 2009, 2015. Travel Forecasting for New Starts Proposals. Workshop PowerPoint Presentations, a Conference Paper (Review of Transit Modeling with Respect to FTA Guidance). Tampa, FL: Cambridge Systematic, Inc., http://www.fta.dot.gov/12304_9547.html.
  21. Flyvbjerg, B. 2005. Measuring Inaccuracy in Travel Demand Forecasting: Methodological Considerations Regarding Ramp Up and Sampling. Transportation Research Part A 39 (6): 522–530.Google Scholar
  22. ———. 2007. Cost Overruns and Demand Shortfalls in Urban Rail and Other Infrastructure. Transportation Planning and Technology 30 (1): 9–30.CrossRefGoogle Scholar
  23. ———. 2009. Survival of the Unfittest: Why the Worst Infrastructure Gets Built and What We Can Do About It. Oxford Review of Economic Policy 25 (3): 307–326.CrossRefGoogle Scholar
  24. Flyvbjerg, B., M.K. Skamris Holm, and S.L. Buhl. 2002. Underestimating Cost of Public Works Projects: Error or Lie? Journal of the American Planning Association 68 (3): 279–295.CrossRefGoogle Scholar
  25. ———. 2004. What Causes Cost Overrun in Transport Infrastructure Projects? Transport Reviews 24: 3–18.CrossRefGoogle Scholar
  26. ———. 2005. How (In)Accurate Are Demand Forecasts in Public Works Projects? The Case of Transportation. Journal of the American Planning Association 71: 131–146.CrossRefGoogle Scholar
  27. ———. 2006. Inaccuracy in Traffic Forecasts. Transport Reviews 26 (1): 1–24.CrossRefGoogle Scholar
  28. Hartgen, D. 2013. Hubris or Humility? Accuracy Issues for the Next 50 Years of Travel Demand Modeling. Transportation 40 (6): 1133–1157.CrossRefGoogle Scholar
  29. ———. 2014. The Next 50 Years in Travel Analysis: What We Need to Know. Internet Survey, January 14–March 17, and TRB Workshop 151, January 2014.Google Scholar
  30. Hartgen, D., G. Fields, and C. Chadwick 2008. Are They Ready? Mega-regions Growth and Transportation Investment: A Report to the Urban Land Institute. Concord, NC: The Hartgen Group. http://www.hartgengroup.net/Projects/ULI_Final_Report_2008-03-07.pdf.
  31. Jahren, T., and M. Ashe. 1990. Predictors of Cost Overruns Rates. Journal of Construction Engineering and Management 116 (3): 548–552.CrossRefGoogle Scholar
  32. Li, Z., and D. Hensher. 2010. Toll Roads in Australia: An Overview of Characteristics and Accuracy of Demand Forecasts. Transport Review 30 (5): 541–569.CrossRefGoogle Scholar
  33. Makovsek, D. 2014. Systematic Construction Risk, Cost Estimation Mechanism and Unit Price Movement. Transport Policy 35: 135–145.CrossRefGoogle Scholar
  34. Manski, C. 2013. Public Policy in an Uncertain World: Analysis and Decisions. Cambridge, MA: Harvard University Press.Google Scholar
  35. Mazur, A. 1981. The Dynamics of Technical Controversy. Washington, DC: Communications Press.Google Scholar
  36. McNally, M. 2000. The Four-Step Model. In Handbook of Transport Modeling, ed. D. Hensher and K. Button. New York: Pergamon.Google Scholar
  37. Mouter, N., J. Annema, and B. Van Wee. 2013. Attitudes Towards the Role of Cost-Benefit Analysis in the Decision-Making Process for Spatial Infrastructure Projects: A Dutch Case Study. Transportation Research A 58: 1–14.Google Scholar
  38. Naess, P., M. Nicolaisen, and A. Strand. 2012. Traffic Forecasts Ignoring Induced Demand: A Shaky Fundament for Cost-Benefit Analyses. European Journal of Transport and Infrastructure Research 12 (3): 291–309.Google Scholar
  39. Nicolaisen, M.S., and P.A. Driscoll. 2014. Ex-post Evaluations of Demand Forecast Accuracy: A Literature Review. Transport Reviews 34 (4): 540–557.CrossRefGoogle Scholar
  40. Nicolaisen, M.S., and P. Naess. 2015. Roads to Nowhere: The Accuracy of Travel Demand Forecasts for Do-Nothing Alternatives. Transport Policy 37: 57–63.CrossRefGoogle Scholar
  41. Nijkamp, P., and B. Ubbels. 1999. How Reliable Are Estimates of Infrastructure Costs? A Comparative Analysis. International Journal of Transport Economics 26: 23–53.Google Scholar
  42. Nobbe, P., and J. Berechman. 2014. A Technical Report. New York: University Transportation Research Center Region 2, The City College of New York.Google Scholar
  43. Odeck, J. 2004. Cost Overruns in Road Construction: What Are Their Sizes and Determinants? Transport Policy 11: 43–53.CrossRefGoogle Scholar
  44. ———. 2013. How Accurate Are National Road Traffic Growth-Rate Forecasts? The Case of Norway. Transport Policy 27: 102–111.CrossRefGoogle Scholar
  45. Ort’uzar, J., and L. Willumsen. 2011. Modelling Transport. 4th ed. Chichester: John Wiley.CrossRefGoogle Scholar
  46. Parthasarathi, P., and D. Levinson. 2010. Post Construction Evaluation of Traffic Forecast Accuracy. Transport Policy 12 (6): 428–443.CrossRefGoogle Scholar
  47. Peeta, S., and A. Ziliaskopoulos. 2001. Foundations of Dynamic Traffic Assignment: The Past, the Present and the Future. Network and Spatial Economics 1: 233–265.CrossRefGoogle Scholar
  48. Pickrell, D. 1990. Urban Rail Transit Projects: Forecast Versus Actual Ridership and Cost. Washington, DC: Urban Mass Transportation Administration, US Dept. of Transportation.Google Scholar
  49. ———. 1992. A Desire Named Streetcar – Fantasy and Fact in Rail Transit Planning. Journal of American Planning Association 58: 158–176.CrossRefGoogle Scholar
  50. Plotch, P. 2015. Politics Across the Hudson: The Tappan Zee Megaproject. New Brunswick, NJ: Rutgers University Press.Google Scholar
  51. Quinet, E. 1998. Principes d’économie des transport. Paris: Economica.Google Scholar
  52. Recker, W.W. 2001. A Bridge Between Travel Demand Modeling and Activity-Based Travel Analysis. Transportation Research Part B 35 (5): 481–506.CrossRefGoogle Scholar
  53. Sager, T., and I. Ravlum. 2005. The Political Relevance of Planners’ Analysis, the Case of a Parliamentary Standing Committee. Planning Theory 4 (1): 33–65.CrossRefGoogle Scholar
  54. Siemiatycki, M. 2009. Academics and Auditors: Comparing Perspectives on Transportation Project Cost Overruns. Journal of Planning Education and Research 29 (2): 142–156.CrossRefGoogle Scholar
  55. Small, K. 1999. Economies of Scale and Self-Financing Rules with Non-competitive Markets. Journal of Public Economics 74: 431–450.CrossRefGoogle Scholar
  56. Small, K., and E. Verhoef. 2007. The Economics of Urban Transportation. London and New York: Routledge.Google Scholar
  57. Trujillo, L., E. Quinet, and A. Estache. 2002. Dealing with Demand Forecasting Games in Transport Privatization. Transport Policy 9: 325–334.CrossRefGoogle Scholar
  58. Tversky, A., and D. Kahneman. 1983. Extensional vs. Intuitive Reasoning: The Conjunction Fallacy in Probability Judgment. Psychological Review 90: 293–315.CrossRefGoogle Scholar
  59. Van Wee, B. 2007. Large Infrastructure Projects: A Review of Quality of Demand Forecast and Cost Estimation. Environment and Planning B 34: 611–625.CrossRefGoogle Scholar
  60. Venables, A. 2007. Evaluating Urban Transport Improvements: Cost-Benefits Analysis in the Presence of Agglomeration and Income Taxation. Journal of Transport Economics and Policy 41 (2): 173–188.Google Scholar
  61. Wachs, M. 1989. When Planners Lie with Numbers. Journal of the American Planning Association 55: 476–479.Google Scholar
  62. ———. 1990. Ethics and Advocacy in Forecasting for Public Policy. Business and Professional Ethics Journal 9 (1–2): 141–157.CrossRefGoogle Scholar

Copyright information

© The Author(s) 2018

Authors and Affiliations

  • Joseph Berechman
    • 1
  1. 1.City College of New YorkUniversity of New YorkNew YorkUSA

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