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Forecasting and Evaluating Network Growth

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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.
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  • David Levinson & Feng Xie & Norah Oca, 2012. "Forecasting and Evaluating Network Growth," Networks and Spatial Economics, Springer, vol. 12(2), pages 239-262, June.
    • Handle: RePEc:kap:netspa:v:12:y:2012:i:2:p:239-262
    DOI: 10.1007/s11067-009-9113-z
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    1. David Levinson & Bhanu Yerra, 2006. "Self-Organization of Surface Transportation Networks," Transportation Science, INFORMS, vol. 40(2), pages 179-188, May.
    2. Bhanu Yerra & David Levinson, 2005. "The emergence of hierarchy in transportation networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 39(3), pages 541-553, September.
    3. Chaisak Suwansirikul & Terry L. Friesz & Roger L. Tobin, 1987. "Equilibrium Decomposed Optimization: A Heuristic for the Continuous Equilibrium Network Design Problem," Transportation Science, INFORMS, vol. 21(4), pages 254-263, November.
    4. Besley, Timothy & Coate, Stephen, 2003. "Centralized versus decentralized provision of local public goods: a political economy approach," Journal of Public Economics, Elsevier, vol. 87(12), pages 2611-2637, December.
    5. Norah Montes de Oca & David Levinson, 2006. "Network Expansion Decision-making in the Twin Cities," Working Papers 200608, University of Minnesota: Nexus Research Group.
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    Cited by:

    1. 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.
    2. Feng Xie & David Levinson, 2009. "Jurisdictional Control and Network Growth," Networks and Spatial Economics, Springer, vol. 9(3), pages 459-483, September.
    3. 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.
    4. 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.
    5. 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.
    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.

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    More about this item

    Keywords

    Network growth; Decision-making; Forecasting; Evaluation; The Twin Cities;
    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
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy

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