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Should Electric Vehicle Drivers Pay a Mileage Tax?

In: Environmental and Energy Policy and the Economy, volume 1

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  • Lucas W. Davis
  • James M. Sallee

Abstract

In many countries the revenue from gasoline taxes is used to fund highways and other transportation infrastructure. As the number of electric vehicles on the road increases, this raises questions about the effectiveness and equity of this financing mechanism. In this paper, we ask whether electric vehicle drivers should pay a mileage tax. Though the gasoline tax has been traditionally viewed as a benefits tax, we take instead the perspective of economic efficiency. We derive a condition for the optimal electric vehicle mileage tax that highlights a key trade-off. On the one hand, there are externalities from driving including traffic congestion and accidents that imply a mileage tax is efficient. On the other hand, gasoline tends to be underpriced, so a low (or even negative) mileage tax might be justified to encourage substitution away from gasoline-powered vehicles. We then turn to an empirical analysis aimed at better understanding the current policy landscape for electric vehicles in the United States. Using newly available nationally-representative microdata we calculate that electric vehicles have reduced gasoline tax revenues by $250 million annually. We show that the foregone tax revenue is highly concentrated in a handful of states and is highly regressive, as most electric vehicles are driven by high-income households, and we discuss how this motivates and informs optimal policy.
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Suggested Citation

  • Lucas W. Davis & James M. Sallee, 2019. "Should Electric Vehicle Drivers Pay a Mileage Tax?," NBER Chapters, in: Environmental and Energy Policy and the Economy, volume 1, pages 65-94, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberch:14286
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    Cited by:

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    3. Erich J. Muehlegger & David S. Rapson, 2023. "Correcting Estimates of Electric Vehicle Emissions Abatement: Implications for Climate Policy," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 10(1), pages 263-282.
    4. Huwe, Vera & Gessner, Johannes, 2020. "Are there rebound effects from electric vehicle adoption? Evidence from German household data," ZEW Discussion Papers 20-048, ZEW - Leibniz Centre for European Economic Research.
    5. Daniel Raimi & Emily Grubert & Jake Higdon & Gilbert Metcalf & Sophie Pesek & Devyani Singh, 2023. "The Fiscal Implications of the US Transition Away from Fossil Fuels," Review of Environmental Economics and Policy, University of Chicago Press, vol. 17(2), pages 295-315.
    6. Borenstein, Severin & Bushnell, James, 2021. "Issues, Questions, and a Research Agenda for the Role of Pricing in Residential Electrification," RFF Working Paper Series 21-35, Resources for the Future.
    7. Patrick Bigler & Doina Maria Radulescu, 2022. "Environmental, Redistributive and Revenue Effects of Policies Promoting Fuel Efficient and Electric Vehicles," CESifo Working Paper Series 9645, CESifo.
    8. Agrawal, David R. & Zhao, Weihua, 2023. "Taxing Uber," Journal of Public Economics, Elsevier, vol. 221(C).
    9. Fabian Feger & Nicola Pavanini & Doina Radulescu, 2022. "Welfare and Redistribution in Residential Electricity Markets with Solar Power [Residential Consumption of Gas and Electricity in the US: The Role of Prices and Income]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(6), pages 3267-3302.
    10. Edward L. Glaeser & Caitlin S. Gorback & James M. Poterba, 2022. "How Regressive Are Mobility-Related User Fees and Gasoline Taxes?," NBER Chapters, in: Tax Policy and the Economy, Volume 37, pages 1-56, National Bureau of Economic Research, Inc.
    11. Hayashida, Sherilyn & La Croix, Sumner & Coffman, Makena, 2021. "Understanding changes in electric vehicle policies in the U.S. states, 2010–2018," Transport Policy, Elsevier, vol. 103(C), pages 211-223.
    12. Ahmadian, Amirhossein & Ghodrati, Vahid & Gadh, Rajit, 2023. "Artificial deep neural network enables one-size-fits-all electric vehicle user behavior prediction framework," Applied Energy, Elsevier, vol. 352(C).

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    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L62 - Industrial Organization - - Industry Studies: Manufacturing - - - Automobiles; Other Transportation Equipment; Related Parts and Equipment
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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