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Micro-foundations of Congestion and Pricing: A Game Theory Perspective

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  • David Levinson

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

Abstract

This paper develops congestion theory and congestion pricing theory from its microfoundations, the interaction of two or more vehicles. Using game theory, with a two-player game it is shown that the emergence of congestion depends on the players-relative valuations of early arrival, late arrival, and journey delay. Congestion pricing can be used as a cooperation mechanism to minimize total costs (if returned to the players). The analysis is then extended to the case of the three-player game, which illustrates congestion as a negative externality imposed on players who do not themselves contribute to it.

Suggested Citation

  • David Levinson, 2005. "Micro-foundations of Congestion and Pricing: A Game Theory Perspective," Working Papers 200504, University of Minnesota: Nexus Research Group.
  • Handle: RePEc:nex:wpaper:microfoundations
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    File URL: http://hdl.handle.net/11299/179927
    File Function: First version, 2007
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    References listed on IDEAS

    as
    1. David Levinson, 1999. "Tolling at a Frontier: A Game Theoretic Analysis," Working Papers 199904, University of Minnesota: Nexus Research Group.
    2. David Levinson, 2000. "Revenue Choice on a Serial Network," Working Papers 200001, University of Minnesota: Nexus Research Group.
    3. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1990. "Economics of a bottleneck," Journal of Urban Economics, Elsevier, vol. 27(1), pages 111-130, January.
    4. Arnott, R. & De Palma, A. & Lindseyt, R., 1995. "Recent Developments in the Bottleneck Model," Papers 9523, Paris X - Nanterre, U.F.R. de Sc. Ec. Gest. Maths Infor..
    5. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
    6. Martin J. Osborne & Ariel Rubinstein, 1994. "A Course in Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262650401, January.
    7. S.C. Littlechild & G.F. Thompson, 1977. "Aircraft Landing Fees: A Game Theory Approach," Bell Journal of Economics, The RAND Corporation, vol. 8(1), pages 186-204, Spring.
    8. F. H. Knight, 1924. "Some Fallacies in the Interpretation of Social Cost," The Quarterly Journal of Economics, Oxford University Press, vol. 38(4), pages 582-606.
    9. C. Robin Lindsey & Erik T. Verhoef, 2000. "Traffic Congestion and Congestion Pricing," Tinbergen Institute Discussion Papers 00-101/3, Tinbergen Institute.
    10. Mohring, Herbert, 1970. "The Peak Load Problem with Increasing Returns and Pricing Constraints," American Economic Review, American Economic Association, vol. 60(4), pages 693-705, September.
    11. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1993. "A Structural Model of Peak-Period Congestion: A Traffic Bottleneck with Elastic Demand," American Economic Review, American Economic Association, vol. 83(1), pages 161-179, March.
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    Citations

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    Cited by:

    1. Ieromonachou, Petros & Warren, James, 2008. "Policy Packages as potential routes to urban road pricing in the UK," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 40, pages 106-123.
    2. Wuping Xin & David Levinson, 2015. "Stochastic Congestion and Pricing Model with Endogenous Departure Time Selection and Heterogeneous Travelers," Mathematical Population Studies, Taylor & Francis Journals, vol. 22(1), pages 37-52, March.
    3. Janusch, Nicholas, 2016. "A note on the distortionary effects of revenue-neutral tolls in a bottleneck congestion game," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 95-103.
    4. Holguín-Veras, José, 2011. "Urban delivery industry response to cordon pricing, time-distance pricing, and carrier-receiver policies in competitive markets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(8), pages 802-824, October.
    5. Feng Xiao & Zhen Qian & H. Zhang, 2011. "The Morning Commute Problem with Coarse Toll and Nonidentical Commuters," Networks and Spatial Economics, Springer, vol. 11(2), pages 343-369, June.
    6. Hugo Emilio Silva & Robin Lindsey & André de Palma & Vincent A.C. van den Berg, 2014. "On the Existence and Uniqueness of Equilibrium in the Bottleneck Model with Atomic Users," Tinbergen Institute Discussion Papers 14-077/VIII, Tinbergen Institute.
    7. Xi Zou & David Levinson, 2006. "A Multi-Agent Congestion and Pricing Model," Working Papers 200605, University of Minnesota: Nexus Research Group.
    8. Holgun-Veras, Jos & Cetin, Mecit, 2009. "Optimal tolls for multi-class traffic: Analytical formulations and policy implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 445-467, May.
    9. Holgui­n-Veras, Jose & Cetin, Mecit & Xia, Shuwen, 2006. "A comparative analysis of US toll policy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(10), pages 852-871, December.
    10. Shanjiang Zhu & David Levinson & Lei Zhang, 2007. "An Agent-based Route Choice Model," Working Papers 000089, University of Minnesota: Nexus Research Group.
    11. Xiao, Feng & Shen, Wei & Michael Zhang, H., 2012. "The morning commute under flat toll and tactical waiting," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1346-1359.
    12. Otsubo, Hironori & Rapoport, Amnon, 2008. "Vickrey's model of traffic congestion discretized," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 873-889, December.
    13. Yaron Hollander & Joseph Prashker, 2006. "The applicability of non-cooperative game theory in transport analysis," Transportation, Springer, vol. 33(5), pages 481-496, September.

    More about this item

    Keywords

    Game Theory; Congestion; Queueing; Traffic Flow; Congestion Pricing; Road Pricing; Value Pricing .;

    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
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy
    • D10 - Microeconomics - - Household Behavior - - - General
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

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