Sen Gupta, Rajorshi and Vadali, Sharada R (2007): Stochastic Dominance Approach to Evaluate Optimism Bias in Truck Toll Forecasts. Published in: Transportation Research Record: Journal of the Transportation Research Board , Vol. 2066, (December 2008): pp. 98-105.
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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.
|Item Type:||MPRA Paper|
|Original Title:||Stochastic Dominance Approach to Evaluate Optimism Bias in Truck Toll Forecasts|
|Keywords:||Forecast Bias; Operating costs; Risk assessment; Savings; Stochastic Dominance; Tolls;Trucks|
|Subjects:||D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D81 - Criteria for Decision-Making under Risk and Uncertainty
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General
R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R4 - Transportation Systems > R41 - Transportation: Demand, Supply, and Congestion; Safety and Accidents; Transportation Noise
|Depositing User:||Rajorshi Sen Gupta|
|Date Deposited:||22. Jan 2009 05:49|
|Last Modified:||13. Feb 2013 17:29|
1. Bain, R., and M. Wilkins. Credit Implications of Traffic Risk in Start-Up Toll Facilities. Standard & Poor’s, New York, 2002.
2. Bain, R., and L. Polakovic. Traffic Forecasting Risk: Study Update 2005: Through Ramp-up and Beyond. Standard & Poor’s, New York, 2005.
3. Bain, R. Traffic Forecasting Risk Study Update 2004—Through Ramp-up and Beyond. Standard & Poor’s, London, 2005.
4. NCHRP Synthesis of Highway Practice 364: Estimating Toll Road Demand and Revenue. Transportation Research Board of the National Academics, Washington, D.C., 2006.
5. American Trucking Research Institute. Top Industry Issues, 2005. atrionline.org/research/results/economicanalysis/index.htm. Accessed July 1,2007.
6. Kawamura, K. Perceived Benefits of Congestion Pricing for Trucks.In Transportation Research Record: Journal of the Transportation Research Board, No. 1833, Transportation Research Board of the National Academics, Washington, D.C., 2003, pp. 59–65.
7. Holguin-Veras, J., D. Sackey, S. Hussain, and V. Ochieng. Economic and Financial Feasibility of Truck Toll Lanes. In Transportation Research Record: Journal of the Transportation Research Board, No. 1833, Transportation Research Board of the National Academics, Washington, D.C., 2003, pp. 66–72.
8. Hensher, D. A., and P. Goodwin. Using Values of Travel Time Savings for Toll Roads: Avoiding Some Common Errors. Transport Policy, Vol. 11, 2004, pp. 171–181.
9. Yang, H., W. H. Tang, W. M. Cheung, and Q. Meng. Profitability and Welfare Gain of Private Toll Roads in a Network with Heterogeneous Users. Transportation Research, Part A, Vol. 36, 2002, pp. 537–554.
10. Kenneth, D. B. Principles of Transportation Economics. Addison Wesley Longman, Inc., 1997, pp. 20–24.
11. Verhoef, E. T., and K. A. Small. Product Differentiation on Roads: Second-Best Congestion Pricing with Heterogeneity Under Public and Private Ownership. Journal of Transport Economics and Policy, Vol. 38, 2004, pp. 127–156.
12. McKnight, C. E., I. Hirschman, J. R. Pucher, J. Berechman, R. E. Paaswell, J. A. Hernandez, and J. Gamill. Optimal Toll Strategies for the Triborough Bridge and Tunnel Authority. Final Report. 1992. www.utrc2.org/research/assets/51/tolls1.pdf. Accessed Sept. 30, 2007.
13. URS Corporation and Vollmer Associates, L.L.P. Central Texas Turnpike System: Traffic and Revenue Forecast Update. 2005. www.central texasturnpike.org. Accessed July 1, 2007.
14. Taft, B. Northern Ohio Freight Strategy:Recommendations to Improve Traffic Safety and Congestion. www.dot.state.oh.us/news/2004/10-11-04Gov.htm. Accessed July 1, 2007.
15. Veras, J. H., Q. Wang, N. Xu., K. Ozbay, M. Cetin, and J. Polimeni. The Impacts of Time of Day Pricing on the Behavior of Freight Traffic in a Congested Urban Area: Implications to Road Pricing. Transportation Research, Part A, Vol. 40, 2006, pp. 744–766.
16. Reebie Associates. The Impact of Tolls on Freight Movement for I-81 in Virginia. Final Report. Department of Rail and Public Transportation, Virginia, 2004.
17. Simon, H. A. A Behavioral Model of Rational Choice. Quarterly Journal of Economics, Vol. 69, 1955, pp. 99–118.
18. Yalcin, A., J. Hashiuchi, and S. Mizokami. A Study on Expressway Toll Pricing Based on Results of Social Experiments. Presented at 85th Annual Meeting of the Transportation Research Board, Transportation Research Board of the National Academies, Washington, D.C., 2006.
19. Knorring, J. H., R. He, and A. L. Kornhauser. Analysis of Route Choice Decisions by Long-Haul Truck Drivers. In Transportation Research Record: Journal of the Transportation Research Board, No. 1923, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 46–60.
20. Bonsall, P., J. Shires, J. Maule, B. Matthews, and J. Beale. Responses to Complex Pricing Signals: Theory, Evidence and Implications for Road Pricing. Transportation Research, Part A, Vol. 41, No. 7, Aug. 2007, pp. 672–683.
21. Van Zyl, N. J. W., and M. Raza. In Search of the Value of Time: From South Africa to India. In Travel Survey Methods: Quality and Future Directions (P. Stopher and C. Stecher, eds.), Pergamon Press, New York, 2006, pp. 457–484.
22. Gifford, J. L., and C. Checherita. Bounded Rationality and Transportation Behavior: Lessons for Public Policy. Presented at 86th Annual Meeting of the Transportation Research Board, Transportation Research Board of the National Academies, Washington, D.C., 2007.
23. Adkins, G. A., A. W. Ward, and W. F. McFarland. NCHRP Report 33: Values of Time Savings of Commercial Vehicles, HRB, National Research Council, Washington, D.C., 1967.
24. Smalkoski, B., and D. Levinson. Value of Time for Commercial Vehicle Operators. Working Papers 200501. University of Minnesota, Nexus Research Group, Minneapolis, 2005.
25. Richardson, J. W. Simulation for Applied Risk Management. Department of Agricultural Economics, Agricultural and Food Policy Center, Texas A&M University, College Station, 2006.
26. Williams, T. M. Practical Use of Distributions in Network Analysis.Journal of the Operational Research Society, Vol. 43, 1992, pp. 265–270.
27. Levinson, D., M. Corbett, and M. Hashami. Operating Costs for Trucks. Working Series Number 000024. University of Minnesota, Nexus Research Group, Minneapolis, 2004.
28. Barnes, G., and P. Langworthy. The Per-Mile Costs of Operating Automobiles and Trucks. Minnesota Department of Transportation, St. Paul, 2003.
29. American Trucking Trends. American Trucking Association, Washington,D.C., 2005–2006.
30. Veras, J. H., M. Cetin, and S. Xia. A Comparative Analysis of US Toll Policy. Transportation Research, Part A, Vol. 40, 2006, pp. 852–871.