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Toll road Traffic Forecasts, Their Failures and How to Fix Them

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  • Brett Crowe

    (Queen’s University Kingston, Ontario, Canada)

Abstract

This paper focuses on the forecasting of transportation networks that involve either the introduction of, or existence of a tolled route. Tolls in traffic forecasts add a new source of uncertainty that can affect the forecasts in many different ways. At a basic level, tolls add additional complexity to both the demand side (road users) and supply side (concessionaires, governments, financiers etc.) of transportation networks. For road users, the toll adds more uncertainty into their route choice decisions. Even in situations where a toll is long established and road users have fully integrated it into their preferences, the toll can still produce unpredictable reactions and decisions, many of which are outlined in this paper. On the supply side, private investment generally depends on cost recovery through toll collection (Lemp, 2009) and the uncertainty created by tying cost recovery to future traffic volumes places an even higher burden on the traffic forecaster. Fortunately economists are well equipped with tools to address and in some cases mitigate this uncertainty; although, as this paper explains, they have not necessarily done a particularly good job of it in the past. The economist’s perspective at its most basic level is about asking whether or not the introduction of a toll will create or destroy surplus across new and existing road users. It also focuses on how the benefits of the road itself and the toll revenues are dispersed among road users, tax payers, governments, and private concessionaires. A somewhat parsimonious description might be to say that economists take the engineer’s predictions and forecasts and then explain that analysis from a creditor’s perspective. Conversely, a creditor or a financier will generally focus strictly on financial outcomes and ignore the economic outcomes involving opportunity cost and social externalities. This paper assess the causes of risk and uncertainty relating specifically to forecasting future traffic volumes on toll roads and subsequently, how such uncertainty influences both financial and economic outcomes. This is not the same as looking at project specific risks as if we were potential financiers or engineers, although many of the sources of risk will be the same. The focus of this paper will be instead placed on the forecasting results themselves. In simpler terms, it will examine why there is such potential for variability in the actual forecasts and why they are so often wrong.

Suggested Citation

  • Brett Crowe, 2014. "Toll road Traffic Forecasts, Their Failures and How to Fix Them," Development Discussion Papers 2014-09, JDI Executive Programs.
  • Handle: RePEc:qed:dpaper:4528
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    References listed on IDEAS

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    1. Robert Bain, 2009. "Error and optimism bias in toll road traffic forecasts," Transportation, Springer, vol. 36(5), pages 469-482, September.
    2. Flyvbjerg, Bent, 2005. "Measuring inaccuracy in travel demand forecasting: methodological considerations regarding ramp up and sampling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(6), pages 522-530, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Forecasting; Toll Roads; Traffic; Demand; Supply; Users; Government; Investments;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning

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