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Travel demand in the US urban areas: A system dynamic panel data approach

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  • Su, Qing

Abstract

Using panel data from 85 urban areas over a 20-year period and applying a system panel data approach, this paper examines the relationship between travel demand in terms of per-capita VMT and urban spatial characteristics. Regression results show that road density and urban spatial size have positive and statistically significant effects on travel demand in the US urban areas. Urban population density and urban congestion have negative and statistically significant effects on travel demand.

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  • Su, Qing, 2010. "Travel demand in the US urban areas: A system dynamic panel data approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(2), pages 110-117, February.
    • Handle: RePEc:eee:transa:v:44:y:2010:i:2:p:110-117
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    Cited by:

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    4. Mamkhezri, Jamal & Khezri, Mohsen, 2024. "Vehicle miles traveled induced demand, rebound effect, and price and income elasticities: A US spatial econometric analysis," Transport Policy, Elsevier, vol. 158(C), pages 224-240.
    5. Daniel Albalate & Xavier Fageda, 2019. "Congestion, Road Safety, and the Effectiveness of Public Policies in Urban Areas," Sustainability, MDPI, vol. 11(18), pages 1-21, September.
    6. Gkritza, Konstantina & Karlaftis, Matthew G. & Mannering, Fred L., 2011. "Estimating multimodal transit ridership with a varying fare structure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 148-160, February.
    7. Su, Qing, 2011. "Induced motor vehicle travel from improved fuel efficiency and road expansion," Energy Policy, Elsevier, vol. 39(11), pages 7257-7264.
    8. Qing Su, 2017. "Travel Demand Management Policy Instruments, Urban Spatial Characteristics, and Household Greenhouse Gas Emissions from Travel in the US Urban Areas," International Journal of Energy Economics and Policy, Econjournals, vol. 7(3), pages 157-166.
    9. Goetzke, Frank & Vance, Colin, 2021. "An increasing gasoline price elasticity in the United States?," Energy Economics, Elsevier, vol. 95(C).
    10. Goetzke, Frank & Vance, Colin, 2018. "Is gasoline price elasticity in the United States increasing? Evidence from the 2009 and 2017 national household travel surveys," Ruhr Economic Papers 765, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    11. Su, Qing, 2012. "A quantile regression analysis of the rebound effect: Evidence from the 2009 National Household Transportation Survey in the United States," Energy Policy, Elsevier, vol. 45(C), pages 368-377.
    12. Woods, Lee & Ferguson, Neil S., 2014. "The influence of urban form on car travel following residential relocation: a current and retrospective study in Scottish urban areas," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 7(1), pages 95-104.
    13. Firman Permana Wandani & Yuichiro Yoshida, 2013. "Spatial Econometric Analysis of Automobile and Motorcycle Traffic on Indonesian National Roads : Is It Local or Beyond City Boundaries?," IDEC DP2 Series 3-11, Hiroshima University, Graduate School for International Development and Cooperation (IDEC).
    14. Yin, Yanhong & Mizokami, Shoshi & Maruyama, Takuya, 2013. "An analysis of the influence of urban form on energy consumption by individual consumption behaviors from a microeconomic viewpoint," Energy Policy, Elsevier, vol. 61(C), pages 909-919.
    15. Pang, Jindong & An, Lan & Shen, Shulin, 2023. "Gasoline prices, traffic congestion, and carbon emissions," Resource and Energy Economics, Elsevier, vol. 75(C).
    16. Le Vine, Scott & Chen, Bingqing (Emily) & Polak, John, 2014. "Does the income elasticity of road traffic depend on the source of income?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 15-29.
    17. Woo, C.K. & Cheng, Y.S. & Li, R. & Shiu, A. & Ho, S.T. & Horowitz, I., 2015. "Can Hong Kong price-manage its cross-harbor-tunnel congestion?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 94-109.
    18. Xavier Fageda, 2021. "Measuring the impact of ride‐hailing firms on urban congestion: The case of Uber in Europe," Papers in Regional Science, Wiley Blackwell, vol. 100(5), pages 1230-1253, October.
    19. Firman Permana Wandani & Yuichiro Yoshida, 2013. "Automobile and Motorcycle Traffic on Indonesian National Roads: Is It Local or Beyond the City Boundary?," GRIPS Discussion Papers 12-19, National Graduate Institute for Policy Studies.
    20. Merlin, Louis A., 2018. "The influence of infill development on travel behavior," Research in Transportation Economics, Elsevier, vol. 67(C), pages 54-67.
    21. Elhorst, J. Paul & Madre, Jean-Loup & Pirotte, Alain, 2020. "Car traffic, habit persistence, cross-sectional dependence, and spatial heterogeneity: New insights using French departmental data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 614-632.
    22. Bastani, Parisa & Heywood, John B. & Hope, Chris, 2012. "The effect of uncertainty on US transport-related GHG emissions and fuel consumption out to 2050," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 517-548.
    23. Clauss, Thomas & Döppe, Sebastian, 2016. "Why do urban travelers select multimodal travel options: A repertory grid analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 93(C), pages 93-116.
    24. Marshall, Wesley & Garrick, Norman, 2012. "Community design and how much we drive," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(2), pages 5-21.

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