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Forecasting and Evaluating Network Growth

Author

Listed:
  • Norah Montes de Oca
  • Feng Xie
  • David Levinson

    (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)

Abstract

This research assesses the implications of existing trends on future network investment, comparing alternative scenarios concerning budgets and investment rules across a variety of performance measures. The main scenarios compare 'stated decision rules', processes encoded in flowcharts and weights developed from official documents or by discussion with agency staff, with 'revealed decision rules', weights estimated statistically based on observed historical behavior. This research specifies the processes necessary to run the network forecasting models with various decision rules. Results for different scenarios are presented including adding additional constraints for the transportation network expansion and calibration process details. We find that alternative decision rules make only small differences in overall system performance, though they direct investments to very different locations. However, changes in total budget can make a significant difference to system-wide performance.

Suggested Citation

  • Norah Montes de Oca & Feng Xie & David Levinson, 2006. "Forecasting and Evaluating Network Growth," Working Papers 000010, University of Minnesota: Nexus Research Group.
    • Handle: RePEc:nex:wpaper:feng
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    File URL: http://hdl.handle.net/11299/180023
    File Function: Second version, 2012
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    Citations

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    Cited by:

    1. David Levinson & David Giacomin & Antony Badsey-Ellis, 2014. "Accessibility and the choice of network investments in the London Underground," Working Papers 000124, University of Minnesota: Nexus Research Group.
    2. Marcin Stępniak & Piotr Rosik, 2018. "The Role of Transport and Population Components in Change in Accessibility: the Influence of the Distance Decay Parameter," Networks and Spatial Economics, Springer, vol. 18(2), pages 291-312, June.
    3. Feng Xie & David Levinson, 2011. "Evaluating the effects of the I-35W bridge collapse on road-users in the twin cities metropolitan region," Transportation Planning and Technology, Taylor & Francis Journals, vol. 34(7), pages 691-703, April.
    4. Feng Xie & David Levinson, 2009. "Jurisdictional Control and Network Growth," Networks and Spatial Economics, Springer, vol. 9(3), pages 459-483, September.
    5. Castillo-Manzano, José I. & Pedregal, Diego J. & Pozo-Barajas, Rafael, 2016. "An econometric evaluation of the management of large-scale transport infrastructure in Spain during the great recession: Lessons for infrastructure bubbles," Economic Modelling, Elsevier, vol. 53(C), pages 302-313.
    6. Lei Kang & Chao Yang & Jeffrey C Peters & Peng Zeng, 2016. "Empirical analysis of road networks evolution patterns in a government-oriented development area," Environment and Planning B, , vol. 43(4), pages 698-715, July.
    7. C. Jacobs-Crisioni & C. C. Koopmans, 2016. "Transport link scanner: simulating geographic transport network expansion through individual investments," Journal of Geographical Systems, Springer, vol. 18(3), pages 265-301, July.

    More about this item

    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
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy

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