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Optimal congestion pricing with diverging long-run and short-run scheduling preferences

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  • Verhoef, Erik T.

Abstract

Traffic congestion is among the main market failures in modern cities. Dynamic marginal external cost pricing is the textbook economic response to this externality. Recent empirical work has shown that there is an important distinction between short-run departure time choice versus long-run routine formation of commuters, also characterized by differences in values of time and schedule delays for the short-run versus the long-run problem. This paper investigates whether this affects optimal pricing of congested roads. Using a dynamic model of congestion, and integrating it with a dynamic model of routine formation, it is found that contrary to expectation, short-run optimal congestion pricing alone cannot optimally decentralize the optimal formation of long-run routines. A separate instrument is therefore needed to optimize routine formation.

Suggested Citation

  • Verhoef, Erik T., 2020. "Optimal congestion pricing with diverging long-run and short-run scheduling preferences," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 191-209.
    • Handle: RePEc:eee:transb:v:134:y:2020:i:c:p:191-209
    DOI: 10.1016/j.trb.2020.02.009
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    1. Takayama, Yuki, 2015. "Bottleneck congestion and distribution of work start times: The economics of staggered work hours revisited," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 830-847.
    2. van den Berg, Vincent & Verhoef, Erik T., 2011. "Winning or losing from dynamic bottleneck congestion pricing?: The distributional effects of road pricing with heterogeneity in values of time and schedule delay," Journal of Public Economics, Elsevier, vol. 95(7-8), pages 983-992, August.
    3. Mogens Fosgerau & Kenneth Small, 2017. "Endogenous Scheduling Preferences And Congestion," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58(2), pages 585-615, May.
    4. Mun, Se-il, 1994. "Traffic jams and the congestion toll," Transportation Research Part B: Methodological, Elsevier, vol. 28(5), pages 365-375, October.
    5. Henderson, J. Vernon, 1981. "The economics of staggered work hours," Journal of Urban Economics, Elsevier, vol. 9(3), pages 349-364, May.
    6. Fosgerau, Mogens, 2015. "Congestion in the bathtub," Economics of Transportation, Elsevier, vol. 4(4), pages 241-255.
    7. Mogens Fosgerau & Kenneth Small, 2017. "Endogenous Scheduling Preferences And Congestion," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58, pages 585-615, May.
    8. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1999. "Information and time-of-usage decisions in the bottleneck model with stochastic capacity and demand," European Economic Review, Elsevier, vol. 43(3), pages 525-548, March.
    9. van den Berg, Vincent & Verhoef, Erik T., 2011. "Winning or losing from dynamic bottleneck congestion pricing?," Journal of Public Economics, Elsevier, vol. 95(7), pages 983-992.
    10. Henderson, J. V., 1974. "Road congestion : A reconsideration of pricing theory," Journal of Urban Economics, Elsevier, vol. 1(3), pages 346-365, July.
    11. Arnott, Richard, 2013. "A bathtub model of downtown traffic congestion," Journal of Urban Economics, Elsevier, vol. 76(C), pages 110-121.
    12. Vickrey, William S, 1969. "Congestion Theory and Transport Investment," American Economic Review, American Economic Association, vol. 59(2), pages 251-260, May.
    13. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
    14. Tseng, Yin-Yen & Verhoef, Erik T., 2008. "Value of time by time of day: A stated-preference study," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 607-618, August.
    15. Stefanie Peer & Erik Verhoef & Jasper Knockaert & Paul Koster & Yin-Yen Tseng, 2011. "Long-Run vs. Short-Run Perspectives on Consumer Scheduling: Evidence from a Revealed-Preference Experiment among Peak-Hour Road Commuters," Tinbergen Institute Discussion Papers 11-181/3, Tinbergen Institute, revised 25 Aug 2014.
    16. Erik T. Verhoef, 2000. "articles: The implementation of marginal external cost pricing in road transport Long run vs short run and first-best vs second-best," Papers in Regional Science, Springer;Regional Science Association International, vol. 79(3), pages 307-332.
    17. de Palma, André & Kilani, Moez & Lindsey, Robin, 2005. "Congestion pricing on a road network: A study using the dynamic equilibrium simulator METROPOLIS," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 588-611.
    18. 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.
    19. Peer, Stefanie & Verhoef, Erik T., 2013. "Equilibrium at a bottleneck when long-run and short-run scheduling preferences diverge," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 12-27.
    20. Small, Kenneth A., 2012. "Valuation of travel time," Economics of Transportation, Elsevier, vol. 1(1), pages 2-14.
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    Cited by:

    1. Zhong, Shaopeng & Jiang, Yu & Nielsen, Otto Anker, 2022. "Lexicographic multi-objective road pricing optimization considering land use and transportation effects," European Journal of Operational Research, Elsevier, vol. 298(2), pages 496-509.
    2. Kosíková, Renata & Krčál, Ondřej & Peer, Stefanie, 2024. "The value of time in a repeated and one-off setup," Research in Transportation Economics, Elsevier, vol. 103(C).
    3. Zhang, Fangni & Lindsey, Robin & Yang, Hai & Shao, Chaoyi & Liu, Wei, 2022. "Two-sided pricing strategies for a parking sharing platform: Reselling or commissioning?," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 40-63.
    4. Jinwon Kim & Jucheol Moon, 2022. "Congestion Costs and Scheduling Preferences of Car Commuters in California: Estimates Using Big Data," Working Papers 2201, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    5. Verhoef, Erik T. & Silva, Hugo E., 2017. "Dynamic equilibrium at a congestible facility under market power," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 174-192.
    6. Xiaojuan Yu & Vincent A.C. van den Berg & Erik T. Verhoef, 2024. "Preference heterogeneity in a dynamic flow congestion model," Tinbergen Institute Discussion Papers 24-025/VIII, Tinbergen Institute.

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    More about this item

    Keywords

    Congestion pricing; Dynamic traffic congestion; Scheduling;
    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
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy
    • D62 - Microeconomics - - Welfare Economics - - - Externalities

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