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Give or take? Rewards versus charges for a congested bottleneck

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  • Rouwendal, Jan
  • Verhoef, Erik T.
  • Knockaert, Jasper

Abstract

This paper analyzes the possibilities to relieve traffic congestion using subsidies instead of Pigouvian taxes, as well as revenue-neutral combinations of rewards and taxes (‘feebates’). The model considers a Vickrey–ADL model of bottleneck congestion with endogenous scheduling. With inelastic demand, a fine (time-varying) reward is found to be equivalent to a fine toll, and to a continuum of combinations of time-varying tolls and rewards, including fine feebates. When demand is price-sensitive, a reward becomes less attractive from the efficiency viewpoint, because it attracts additional users to the congested bottleneck. As a result, both the second-best optimal fraction of rewarded travelers in the scheme, and the relative efficiency that can be achieved with it, decrease when demand becomes more elastic. Our analytical and simulation results for coarse schemes reveal that a coarse reward is less effective than a coarse feebate, which is itself less effective than a coarse toll. The most efficient coarse system is the step toll, which is also allowed to be positive in the fringes of the peak. Despite the smaller efficiency gains, rewards and feebates may be attractive to use in circumstances where public and political acceptability of tolling is especially low, so that its implementation is unlikely, including the temporary use of price incentives in case of road works and large-scale events.

Suggested Citation

  • Rouwendal, Jan & Verhoef, Erik T. & Knockaert, Jasper, 2012. "Give or take? Rewards versus charges for a congested bottleneck," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 166-176.
  • Handle: RePEc:eee:regeco:v:42:y:2012:i:1:p:166-176
    DOI: 10.1016/j.regsciurbeco.2011.08.011
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Wu, Jiyan & Tian, Ye & Sun, Jian & Michael Zhang, H. & Wang, Yunpeng, 2023. "Public or private? Optimal organization for incentive-based travel demand management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 174(C).
    2. Tang, Yili & Jiang, Yu & Yang, Hai & Nielsen, Otto Anker, 2020. "Modeling and optimizing a fare incentive strategy to manage queuing and crowding in mass transit systems," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 247-267.
    3. Bao, Yue & Verhoef, Erik T. & Koster, Paul, 2019. "Regulating dynamic congestion externalities with tradable credit schemes: Does a unique equilibrium exist?," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 225-236.
    4. Knockaert, Jasper & Verhoef, Erik T. & Rouwendal, Jan, 2016. "Bottleneck congestion: Differentiating the coarse charge," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 59-73.
    5. te Brömmelstroet, Marco, 2014. "Sometimes you want people to make the right choices for the right reasons: potential perversity and jeopardy of behavioural change campaigns in the mobility domain," Journal of Transport Geography, Elsevier, vol. 39(C), pages 141-144.
    6. Wu, Jiyan & Tian, Ye & Sun, Jian, 2023. "Managing ridesharing with incentives in a bottleneck model," Research in Transportation Economics, Elsevier, vol. 101(C).
    7. Li, Zhi-Chun & Huang, Hai-Jun & Yang, Hai, 2020. "Fifty years of the bottleneck model: A bibliometric review and future research directions," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 311-342.
    8. Zhao, Chuan-Lin & Leclercq, Ludovic, 2018. "Graphical solution for system optimum dynamic traffic assignment with day-based incentive routing strategies," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 87-100.
    9. Knockaert, Jasper & Tseng, Yin-Yen & Verhoef, Erik T. & Rouwendal, Jan, 2012. "The Spitsmijden experiment: A reward to battle congestion," Transport Policy, Elsevier, vol. 24(C), pages 260-272.
    10. Sun, Jian & Wu, Jiyan & Xiao, Feng & Tian, Ye & Xu, Xiangdong, 2020. "Managing bottleneck congestion with incentives," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 143-166.
    11. Tian, Ye & Li, Yudi & Sun, Jian, 2022. "Stick or carrot for traffic demand management? Evidence from experimental economics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 235-254.

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    More about this item

    Keywords

    Traffic congestion; Road pricing; Subsidies; Rewards; Bottleneck model;
    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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