MIT1_201JF08_lec16

MIT1_201JF08_lec16 - Transportation Revenue Forecasting:...

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Transportation Revenue Forecasting: Theory and Models Moshe Ben-Akiva 1.201 / 11.545 / ESD.210 Transportation Systems Analysis: Demand & Economics Fall 2008 Overview Increasing reliance on private sector financing of transportation projects (particularly toll roads) has emphasized the importance of accurate revenue forecasting Main factors of revenue forecasting: – Pricing/tolling strategy – Travel demand forecasting – Traffic assignment 2
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Outline Review Basic Pricing Concepts Public Sector Pricing Private Sector Pricing Revenue Forecasting Forecasting Accuracy Sources of Uncertainty Enhanced Methods Conclusion 3 Review of Public Sector Pricing Maximize welfare Marginal cost pricing Under constraints – Cost recovery: Ramsey pricing – Distortions: second-best pricing 4
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Review of Private Sector Pricing Maximize profit or revenue Perfectly competitive market – Price close to marginal cost Less competitive market – Price discrimination 5 Outline Review Basic Pricing Concepts Revenue Forecasting Forecasting Accuracy Sources of Uncertainty Enhanced Methods Conclusion 6
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Revenue Forecasting Revenue forecasting is essential for assessing financial feasibility and project approval Here we focus on toll roads and toll bridges 7 Forecasting Accuracy Few examples where actual revenue exceeded the forecast Many examples where actual traffic demand and revenue have significantly lagged the forecasts – Dulles Greenway in Virginia went into default in 1996, when toll revenues were less than the forecast (20% of the forecast in its first year of operation; and only 35% in its fifth year) 8
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Forecasting Accuracy (cont.) 68 case studies during 2003 of traffic forecasting for international toll roads Ratio of actual/forecast traffic volumes follows a normal distribution with average 0.74 and standard deviation 0.26 Image removed due to copyright issues. Source: Bain, R. and Plantagie, T.W. (2003), Traffic Forecasting Risk: Study Update 2003 , Standard & Poor’s RatingsDirect, the McGraw-Hill Companies, New York, [Online], May 2008, Available at: http://www.people.hbs.edu/besty/projfinportal/S&P_Traffic_Update.pdf. Forecasting Accuracy (cont.) Examples: Actual revenue as percentage of forecast Facility Year of opening Year 1 Year 2 Year 3 Year 4 Year 5 Florida's Turnpike Enterprise/ Sawgrass Expressway 1986 17.8% 23.4% 32.0% 37.1% 38.4% Orlando-Orange Expressway Authority/Central Florida Greenway North Segment 1989 96.8% 85.7% 81.4% 69.6% 77.1% State Road and Tollway Authority (Georgia)/GA 400 1993 117.0% 133.1% 139.8% 145.8% 141.8% Transportation Corridor Agencies (California)/San Joaquin Hills 1996 31.6% 47.5% 51.5% 52.9% 54.1% Santa Rosa Bay Bridge Authority (Florida)/Garcon Point Bridge 1999 32.6% 54.8% 50.5% 47.1% 48.7% Pocahontas Parkway Association (Virginia)/Pocahontas Parkway 2002 41.6% 40.4% 50.8% NA NA Figure by MIT OpenCourseWare. Source: Kriger, D., Shiu, S. and Naylor, S. (2006),
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MIT1_201JF08_lec16 - Transportation Revenue Forecasting:...

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