Evaluating Fuel Tax Revenue Impacts of Electric Vehicle Adoption in Virginia Counties: Application of a Bivariate Linear Mixed Count Model

Wenjian Jia, Zhiqiu Jiang, T. Donna Chen, Rajesh Paleti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Increasing electric vehicle (EV) shares and fuel economy pose challenges to a fuel tax-based transportation funding scheme. This paper evaluates the fuel tax revenue impacts of such trends using Virginia as a case study. First, a county-level bivariate count model is developed using vehicle registration data in 132 counties from 2012 to 2016. Model results indicate strong correlation between presence of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) on a county basis. Counties with higher percent of males are associated with higher BEV (but not PHEV) counts. In contrast, higher average commute time is predicted to increase the number of PHEVs in each county, but not BEVs. Greater population density, population over 65, population with graduate degrees, and household size are found to increase PHEV and BEV counts while more households with children is associated with fewer EVs. The analysis forecasts 0.6% to 10% statewide EV adoption by 2025, with an adoption rate of 2.4% in the most likely scenario. Nine scenarios, combining different predictions of EV adoption and fuel economy improvement, project statewide fuel tax revenue to decrease by 5% to 19%, relative to 2016 receipts. Furthermore, though all counties are predicted to experience decreasing fuel tax revenue contribution per vehicle (due to fuel economy improvements and EV adoption), the decrease is more significant in urban areas. Model results predict that on average a light duty vehicle in a rural area will pay 28% more in fuel taxes than its urban counterpart by 2025. The framework proposed here provides a reference for other regions to conduct similar analysis using public agency data in the vehicle electrification era.

Original languageEnglish (US)
Title of host publicationInternational Conference on Transportation and Development 2019
Subtitle of host publicationInnovation and Sustainability in Smart Mobility and Smart Cities - Selected Papers from the International Conference on Transportation and Development 2019
EditorsDavid A. Noyce
PublisherAmerican Society of Civil Engineers (ASCE)
Pages91-110
Number of pages20
ISBN (Electronic)9780784482582
DOIs
StatePublished - Jan 1 2019
EventInternational Conference on Transportation and Development 2019: Innovation and Sustainability in Smart Mobility and Smart Cities, ICTD 2019 - Alexandria, United States
Duration: Jun 9 2019Jun 12 2019

Publication series

NameInternational Conference on Transportation and Development 2019: Innovation and Sustainability in Smart Mobility and Smart Cities - Selected Papers from the International Conference on Transportation and Development 2019

Conference

ConferenceInternational Conference on Transportation and Development 2019: Innovation and Sustainability in Smart Mobility and Smart Cities, ICTD 2019
CountryUnited States
CityAlexandria
Period6/9/196/12/19

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Geography, Planning and Development
  • Transportation
  • Mechanics of Materials
  • Civil and Structural Engineering

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  • Cite this

    Jia, W., Jiang, Z., Chen, T. D., & Paleti, R. (2019). Evaluating Fuel Tax Revenue Impacts of Electric Vehicle Adoption in Virginia Counties: Application of a Bivariate Linear Mixed Count Model. In D. A. Noyce (Ed.), International Conference on Transportation and Development 2019: Innovation and Sustainability in Smart Mobility and Smart Cities - Selected Papers from the International Conference on Transportation and Development 2019 (pp. 91-110). (International Conference on Transportation and Development 2019: Innovation and Sustainability in Smart Mobility and Smart Cities - Selected Papers from the International Conference on Transportation and Development 2019). American Society of Civil Engineers (ASCE). https://doi.org/10.1061/9780784482582.009