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

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  • Su, Qing
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    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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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 44 (2010)
    Issue (Month): 2 (February)
    Pages: 110-117

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    Handle: RePEc:eee:transa:v:44:y:2010:i:2:p:110-117

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    Related research

    Keywords: Travel demand System dynamic panel data estimator Road density Population density Urban congestion;

    References

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    1. Mindali, Orit & Raveh, Adi & Salomon, Ilan, 2004. "Urban density and energy consumption: a new look at old statistics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(2), pages 143-162, February.
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    7. Cynthia Chen & Hongmian Gong & Robert Paaswell, 2008. "Role of the built environment on mode choice decisions: additional evidence on the impact of density," Transportation, Springer, vol. 35(3), pages 285-299, May.
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    Cited by:
    1. 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.
    2. Su, Qing, 2011. "Induced motor vehicle travel from improved fuel efficiency and road expansion," Energy Policy, Elsevier, vol. 39(11), pages 7257-7264.
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. Rentziou, Aikaterini & Gkritza, Konstantina & Souleyrette, Reginald R., 2012. "VMT, energy consumption, and GHG emissions forecasting for passenger transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 487-500.
    8. 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.
    9. 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.

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