International Conference on Transportation and Development 2019
Evaluating Fuel Tax Revenue Impacts of Electric Vehicle Adoption in Virginia Counties: Application of a Bivariate Linear Mixed Count Model
Publication: International Conference on Transportation and Development 2019: Innovation and Sustainability in Smart Mobility and Smart Cities
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.
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ACKNOWLEDGEMENTS
This study is funded by Mid-Atlantic Transportation Sustainability University Center (MATS UTC) Grant No: 146221. The authors would like to thank Lam Phan for providing VA DMV vehicle registration data.
REFERENCES
Anable, J., S. Skippon, et al. (2011). “Who will adopt electric vehicles: A segmentation approach of UK consumers.” European Council for an Energy Efficient Economy.
Bansal, P., K. Kockelman, and Y. Wang. (2015). “Hybrid electric vehicle ownership and fuel economy across Texas: an application of spatial models.” Transportation Research Record: Journal of the Transportation Research Board, 2495: 53-64.
Bloomberg New Energy Finance. (2017). “Electric Vehicle Outlook 2017.”
Brand, D. “Impacts of Higher Fuel Costs.” (2009). Federal Highway Administration, 2009.
Brownstone, D., and H. Fang. (2009). “Vehicle ownership and utilization choice model with edogenous residential density.” Presented at the 88th Annual Meeting of the Transportation Research Board, Washington, D.C.
Carley, S., R. Krause, B. Lane, and J. Graham. (2013). “Intent to purchase a plug-in electric vehicle: A survey of early impressions in large US cites.” Transportation Research Part D: Transport and Environment, 18: 39-45.
Chamberlin, R., C. Kergaye, and K. Nichol. (2016). “Methodology to Assess High Efficiency Vehicle Trends on Fuel Tax Revenue in Utah.” Presented at the 95th Annual Meeting of the Transportation Research Board, Washington, D.C.
Chen, T., Y. Wang, and K. Kockelman. (2015). “Where are the electric vehicles? A spatial model for vehicle-choice count data.” Journal of Transport Geography, 43: 181-188.
Demographics Research Group. “Weldon Cooper Center for Public Service.” https://coopercenter.org/. Accessed June 2018.
Dimatulac, T., and H. Maoh. (2017). “The spatial distribution of hybrid electric vehicles in a sprawled mid-size Canadian city: Evidence from Windsor, Canada.” Journal of Transport Geography, 60: 59-67.
Egbue, O., and S. Long. (2012). “Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions.” Energy policy, 48: 717-729.
EVAdoption. “Analyzing Key Factors That Will Drive Mass Adoption of Electric Vehicles.” http://evadoption.com/. Accessed July 2018.
Farkas, Z., H. Shin, A. Nickkar. (2018). “Environmental Attributes of Electric Vehicle Ownership and Commuting Behavior in Maryland: Public Policy and Equity Considerations.” Mid-Atlantic Transportation Sustainability University Transportation Center University of Virginia.
Federal Highway Administration, U.S. Department of Transportation. Alternative Fuel Corridors. https://www.fhwa.dot.gov/environment/alternative_fuel_corridors/all_corridors/index.cfm. Accessed June 2018.
Ferguson, M., M. Mohamed, et al. (2018). “How open are Canadian households to electric vehicles? A national latent class choice analysis with willingness-to-pay and metropolitan characterization.” Transportation Research Part D: Transport and Environment, 58: 208-224.
Gillingham, K. (2014). “Identifying the elasticity of driving: evidence from a gasoline price shock in California.” Regional Science and Urban Economics, 47: 13-24.
Hadfield, J. D. (2010). “MCMC methods for multi-response generalized linear mixed models: The MCMCglmm R Package.” Journal of Statistical Software, 33(2):1-22.
Hess, S., M. Fowler, et al. (2012). “A joint model for vehicle type and fuel type choice: evidence from a cross-nested logit study.” Transportation, 39(3): 593-625.
Hidrue, K., G. Parsons et al. (2011). “Willingness to pay for electric vehicles and their attributes.” Resource and Energy Economics, 33(3): 686-705.
Higgins, C., M. Mohamed, and M. Ferguson. (2017). “Size matters: How vehicle body type affects consumer preferences for electric vehicles.” Transportation Research Part A: Policy and Practice, 100: 182-201.
Hoen, A., and M. Koetse. (2014). “A choice experiment on alternative fuel vehicle preferences of private car owners in the Netherlands.” Transportation Research Part A: Policy and Practice, 61: 199-215.
Hymel, M., K. Small, and K. Dender. (2010). “Induced demand and rebound effects in road transport.” Transportation Research Part B: Methodological, 44(10): 1220-1241.
International Energy Agency. (2018). “Global EV outlook 2018.”
Jenn, A., I. Azevedo, and P. Fischbeck. (2015). “How will we fund our roads? A case of decreasing revenue from electric vehicles.” Transportation Research Part A: Policy and Practice, 74: 136-147.
Jensen, F., E. Cherchi, and S. Mabit. (2013). “On the stability of preferences and attitudes before and after experiencing an electric vehicle.” Transportation Research Part D: Transport and Environment, 25: 24-32.
Jin, L., S. Stephanie, and L. Nic. (2014). “Evaluation of state-level U.S. PEV incentives.” International Council on Clean Transportation.
Kim, J., S. Rasouli, and H. Timmermans. (2014). “Expanding scope of hybrid choice models allowing for mixture of social influences and latent attitudes: Application to intended purchase of electric cars.” Transportation research part A: policy and practice, 69: 71-85.
Klöckner, A., A. Nayum, and M. Mehmetoglu. (2013). “Positive and negative spillover effects from electric car purchase to car use.” Transportation Research Part D: Transport and Environment, 21: 32-38.
Kurani, K. (2018). “Gender Imbalance in the Plug-in Electric Vehicle Market Threatens to Slow Future Market Growth.” National Center for Sustainable Transportation.
Lane, B. (2018). “All plug-in electric vehicles are not the same: Predictors of preference for a plug-in hybrid versus a battery-electric vehicle.” Presented at the 97th Annual Meeting of the Transportation Research Board, Washington, D.C.
Li, S., J. Linn, and E. Muehlegger. (2014). “Gasoline taxes and consumer behavior.” American Economic Journal: Economic Policy, 6 (4): 302-42.
Liao, F., E. Molin, and B. Wee. (2017). “Consumer preferences for electric vehicles: a literature review.” Transport Reviews, 37(3): 252-275.
Lutsey, N., S. Stephanie, et al. (2015). “Assessment of leading PEV promotion activities in United States cities”. International Council on Clean Transportation.
Mohamed, M., C. Higgins, et al. (2016). “Identifying and characterizing potential electric vehicle adopters in Canada: A two-stage modelling approach.” Transport Policy, 52:100-112.
Narassimhan, E., and J. Caley. (2014). “The effect of state incentives on plug-in PEV purchases.” National Renewable Energy Laboratory.
NHTS Brief. (2006). “Rising Fuel Cost—A Big Impact”. FHWA, U.S. Department of Transportation.
Openshaw, S. (1984). “The modifiable areal unit problem. Concepts and techniques in modern Geography.”
Plötz, P., U. Schneider, et al. (2014). “Who will buy electric vehicles? Identifying early adopters in Germany.” Transportation Research Part A: Policy and Practice, 67: 96-109.
Potoglou, D., and P. Kanaroglou. (2007). “Household demand and willingness to pay for clean vehicles.” Transportation Research Part D: Transport and Environment, 12(4): 264-274.
Qian, L., and D. Soopramanien. (2011). “Heterogeneous consumer preferences for alternative fuel cars in China.” Transportation Research Part D: Transport and Environment, 16(8): 607-613.
Schleith, K. (2017). “Implications of Electric Vehicle Penetration on Federal and State Highway Revenues.” No. FSEC-CR-2052-17.
Small, K., and K. Dender. (2007). “Fuel efficiency and motor vehicle travel: the declining rebound effect.” The Energy Journal, 25-51.
Sierzchula, W., S. Bakker et al. (2014). “The influence of financial incentives and other socio-economic factors on electric vehicle adoption”. Energy Policy, 68: 183-194.
Soltani-Sobh, A., K. Heaslip et al. (2017). “Analysis of the Electric Vehicles Adoption over the United States.” Transportation Research Procedia, 22: 203-212.
U.S. Congressional Budget Office. (2011). “Alternative Approaches to Funding Highways.”
U.S. Congressional Budget Office. (2017). “The Budget and Economic Outlook: 2017 to 2027.”
U.S. Environmental Protection Agency. (2018). “Light-Duty Automotive Technology, Carbon Dioxide Emissions, and Fuel Economy Trends: 1975 Through 2017.” EPA-420-R-18-001.
Vasudevan, V., and S. Nambisan. (2013). “Impacts of energy regulations and vehicular technologies on fuel tax revenues.” Journal of Infrastructure Systems, 20(2): 04014007.
Vergis, S., and B. Chen. (2014). “Understanding variations in US plug-in PEV markets.” Research Report UCD-ITS-RR-14-25. Institute of Transportation Studies, University of California, Davis.
Vergis, S., and B. Chen. (2015). “Comparison of plug-in electric vehicle adoption in the United States: A state by state approach.” Research in Transportation Economics, 52: 56-64.
Wood, E., R. Clement, et al. (2017). “National Plug-In Electric Vehicle Infrastructure Analysis.” Office of Energy Efficiency & Renewable Energy, U.S. Department of Energy.
Zhou, Y., D. Santini, et al. (2017). “Contributing factors in plug-in electric vehicle adoption in the United States: A Metro/County Level Investigation.” Presented at the 96th Annual Meeting of the Transportation Research Board, Washington, D.C.
Ziegler, A. (2012). “Individual characteristics and stated preferences for alternative energy sources and propulsion technologies in vehicles: A discrete choice analysis for Germany.” Transportation Research Part A: Policy and Practice, 46(8): 1372-1385.
Information & Authors
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Published In
International Conference on Transportation and Development 2019: Innovation and Sustainability in Smart Mobility and Smart Cities
Pages: 91 - 110
Editor: David A. Noyce, Ph.D., University of Wisconsin–Madison
ISBN (Online): 978-0-7844-8258-2
Copyright
© 2019 American Society of Civil Engineers.
History
Published online: Aug 28, 2019
Authors
Author Contribution Statement
The authors confirm contribution to the paper as follows: study conception and design: W. Jia, T.D. Chen, Z. Jiang; data collection: W. Jia, Z. Jiang; analysis and interpretation of results: W. Jia, Z. Jiang, T.D. Chen, R. Paleti; draft manuscript preparation: W. Jia, T.D. Chen. All authors reviewed the results and approved the final version of the manuscript.
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