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Stochastic Dominance Approach to Evaluate Optimism Bias in Truck Toll Forecasts


  • Sen Gupta, Rajorshi
  • Vadali, Sharada R


Optimism bias is a consistent feature associated with truck toll forecasts, à la Standard & Poor’s and the NCHRP synthesis reports. Given the persistent problem, two major sources of this bias are explored. In particular, the ignorance of operating cost as a demand-side factor and lack of attention to user heterogeneity are found to contribute to this bias. To address it, stochastic dominance analysis is used to assess the risk associated with toll revenue forecasts. For a hypothetical corridor, it is shown that ignorance of operating cost savings can lead to upward bias in the threshold value of time distribution. Furthermore, dominance analysis demonstrates that there is greater risk associated with the revenue forecast when demand heterogeneity is factored in. The approach presented can be generally applied to all toll forecasts and is not restricted to trucks.

Suggested Citation

  • Sen Gupta, Rajorshi & Vadali, Sharada R, 2007. "Stochastic Dominance Approach to Evaluate Optimism Bias in Truck Toll Forecasts," MPRA Paper 12891, University Library of Munich, Germany, revised 2008.
  • Handle: RePEc:pra:mprapa:12891

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    References listed on IDEAS

    1. Hensher, David A. & Goodwin, Phil, 2004. "Using values of travel time savings for toll roads: avoiding some common errors," Transport Policy, Elsevier, vol. 11(2), pages 171-181, April.
    2. Yang, Hai & Tang, Wilson H. & Man Cheung, Wing & Meng, Qiang, 2002. "Profitability and welfare gain of private toll roads in a network with heterogeneous users," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(6), pages 537-554, July.
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    Cited by:

    1. Gomez, Juan & Vassallo, José Manuel, 2015. "Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 282-297.

    More about this item


    Forecast Bias; Operating costs; Risk assessment; Savings; Stochastic Dominance; Tolls; Trucks;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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