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Vehicle choices and urban transport externalities. Are Norwegian policy makers getting it right?


  • Wangsness, Paal Brevik

    () (Institute of Transport Economics – Norwegian Centre for Transport Research)

  • Proost, Stef

    (Department of Economics-KULeuven)

  • Rødseth, Kenneth Løvold

    (Norwegian University of Life Sciences)


Norway has the world’s highest share of electric vehicles in its vehicle stock – in particular battery electric vehicles (BEVs). BEVs have reached a 20% share of the new car sales in Norway, thanks to a set of policies that include high purchase taxes for fossil fueled cars, and for BEVs, free parking, no tolls, and the right to drive on the bus lanes. This paper uses a stylized model of the transport market in the greater Oslo area (1.2 million inhabitants) to analyze transport policies. First, we explore the medium-term effects of the current BEV friendly policies. Second, the model is used to explore the potential of better pricing of car and public transport use, and of better car purchase taxes. We find that the current policies lead to massive penetration of BEVs and therefore to a strong reduction of CO2 emissions. However, they also lead to much more congestion and a decrease in the use of public transport. Better policies require efficient pricing of road congestion, a better use of public transport, and provide incentives for consumers to choose the most efficient combinations of cars. Such policies lead to a less extreme penetration of BEVs, and lower CO2 emissions reductions than the current transport policies. However, they do achieve a better transport equilibrium and substantial resource cost savings, leading to higher welfare levels.

Suggested Citation

  • Wangsness, Paal Brevik & Proost, Stef & Rødseth, Kenneth Løvold, 2018. "Vehicle choices and urban transport externalities. Are Norwegian policy makers getting it right?," Working Paper Series 2-2018, Norwegian University of Life Sciences, School of Economics and Business.
  • Handle: RePEc:hhs:nlsseb:2018_002

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    References listed on IDEAS

    1. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    2. 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.
    3. Börjesson, Maria & Fung, Chau Man & Proost, Stef, 2017. "Optimal prices and frequencies for buses in Stockholm," Economics of Transportation, Elsevier, vol. 9(C), pages 20-36.
    4. Arie Beresteanu & Shanjun Li, 2011. "Gasoline Prices, Government Support, And The Demand For Hybrid Vehicles In The United States," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(1), pages 161-182, February.
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    Cited by:

    1. Christina Littlejohn & Stef Proost, 2019. "What Role for Electric Vehicles in the Decarbonization of the Car Transport Sector in Europe?," CESifo Working Paper Series 7789, CESifo.

    More about this item


    electric vehicles; climate policy; urban transport policy; transport modeling;

    JEL classification:

    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • H71 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Taxation, Subsidies, and Revenue
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • 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

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