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VMT, energy consumption, and GHG emissions forecasting for passenger transportation

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  • Rentziou, Aikaterini
  • Gkritza, Konstantina
  • Souleyrette, Reginald R.
Abstract
Globalization, greenhouse gas emissions and energy concerns, emerging vehicle technologies, and improved statistical modeling capabilities make the present moment an opportune time to revisit aggregate vehicle miles traveled (VMT), energy consumption, and greenhouse gas (GHG) emissions forecasting for passenger transportation. Using panel data for the 48 continental states during the period 1998–2008, the authors develop simultaneous equation models for predicting VMT on different road functional classes and examine how different technological solutions and changes in fuel prices can affect passenger VMT. Moreover, a random coefficient panel data model is developed to estimate the influence of various factors (such as demographics, socioeconomic variables, fuel tax, and capacity) on the total amount of passenger VMT in the United States. To assess the influence of each significant factor on VMT, elasticities are estimated. Further, the authors investigate the effect of different policies governing fuel tax and population density on future energy consumption and GHG emissions. The presented methodology and estimation results can assist transportation planners and policy-makers in determining future energy and transportation infrastructure investment needs.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:transa:v:46:y:2012:i:3:p:487-500
    DOI: 10.1016/j.tra.2011.11.009
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    References listed on IDEAS

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    1. Noland, Robert B., 2001. "Relationships between highway capacity and induced vehicle travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 47-72, January.
    2. Patricia L. Mokhtarian & Michael N. Bagley, 2002. "The impact of residential neighborhood type on travel behavior: A structural equations modeling approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 36(2), pages 279-297.
    3. Fang, Hao Audrey, 2008. "A discrete-continuous model of households' vehicle choice and usage, with an application to the effects of residential density," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 736-758, November.
    4. Kenneth A. Small & Kurt van Dender, 2007. "Long Run Trends in Transport Demand, Fuel Price Elasticities and Implications of the Oil Outlook for Transport Policy," OECD/ITF Joint Transport Research Centre Discussion Papers 2007/16, OECD Publishing.
    5. Brownstone, David & Golob, Thomas F., 2009. "The impact of residential density on vehicle usage and energy consumption," Journal of Urban Economics, Elsevier, vol. 65(1), pages 91-98, January.
    6. Chatman, Daniel G., 2008. "Deconstructing development density: Quality, quantity and price effects on household non-work travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(7), pages 1008-1030, August.
    7. Robert Noland & William Cowart, 2000. "Analysis of Metropolitan Highway Capacity and the growth in vehicle miles of travel," Transportation, Springer, vol. 27(4), pages 363-390, December.
    8. Brantley Liddle, 2011. "Consumption-Driven Environmental Impact and Age Structure Change in OECD Countries," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 24(30), pages 749-770.
    9. Choo, Sangho & Mokhtarian, Patricia L., 2007. "Telecommunications and travel demand and supply: Aggregate structural equation models for the US," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(1), pages 4-18, January.
    10. Liddle, Brantley, 2009. "Long-Run Relationship among Transport Demand, Income, and Gasoline Price for the US," MPRA Paper 52080, University Library of Munich, Germany.
    11. Southworth, Frank, 2001. "On the potential impacts of land use change policies on automobile vehicle miles of travel," Energy Policy, Elsevier, vol. 29(14), pages 1271-1283, November.
    12. 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.
    13. Boarnet, Marlon & Crane, Randall, 2001. "The influence of land use on travel behavior: specification and estimation strategies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(9), pages 823-845, November.
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