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The impact of residential density on vehicle usage and fuel consumption

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  • Kim, Jinwon
  • Brownstone, David

Abstract

This paper investigates the impact of residential density on vehicle usage and fuel consumption. The empirical model accounts for both residential self-selection effects and non-random missing data problems. While most previous studies focus on a specific region, this paper analyzes national level data from the 2001 National Household Travel Survey. Comparing two households that are equal in all respects except residential density, the household residing in an area that is 1000 housing units per square mile denser (roughly 50% of the sample average) will drive 1500 (7.8%) less miles per year and will consume 70 (7.5%) fewer gallons of fuel than the household in the less dense area. The effect of the contextual density measure (density in the context of its surrounding area) is quantitatively larger than the sole effect of residential density. A simulation moving a household from suburban to urban area reduces household annual mileage by 15%.

Suggested Citation

  • Kim, Jinwon & Brownstone, David, 2010. "The impact of residential density on vehicle usage and fuel consumption," University of California Transportation Center, Working Papers qt31m0w2x3, University of California Transportation Center.
  • Handle: RePEc:cdl:uctcwp:qt31m0w2x3
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    References listed on IDEAS

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    1. Antonio M. Bento & Maureen L. Cropper & Ahmed Mushfiq Mobarak & Katja Vinha, 2005. "The Effects of Urban Spatial Structure on Travel Demand in the United States," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 466-478, August.
    2. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    3. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 38(2), pages 112-134.
    4. Salon, Deborah, 2009. "Neighborhoods, cars, and commuting in New York City: A discrete choice approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(2), pages 180-196, February.
    5. Bhat, Chandra R. & Guo, Jessica Y., 2007. "A comprehensive analysis of built environment characteristics on household residential choice and auto ownership levels," Transportation Research Part B: Methodological, Elsevier, vol. 41(5), pages 506-526, June.
    6. Bento, Antonio M. & Cropper, Maureen L. & Mobarak, Ahmed Mushfiq & Vinha, Katja, 2003. "The impact of urban spatial structure on travel demand in the United States," Policy Research Working Paper Series 3007, The World Bank.
    7. 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.
    8. 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.
    9. Matthew E. Kahn, 2000. "The environmental impact of suburbanization," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 19(4), pages 569-586.
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    Citations

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    Cited by:

    1. Gabriel Ahlfeldt & Elisabetta Pietrostefani, 2017. "The Economic Effects of Density: A Synthesis," CESifo Working Paper Series 6744, CESifo Group Munich.
    2. Bhat, Chandra R. & Astroza, Sebastian & Sidharthan, Raghuprasad & Alam, Mohammad Jobair Bin & Khushefati, Waleed H., 2014. "A joint count-continuous model of travel behavior with selection based on a multinomial probit residential density choice model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 31-51.
    3. Kotval-K, Zeenat & Vojnovic, Igor, 2016. "A socio-ecological exploration into urban form: The environmental costs of travel," Ecological Economics, Elsevier, vol. 128(C), pages 87-98.
    4. Gabriel M. Ahfeldt & Elisabetta Pietrostefani, 2017. "The Compact City in Empirical Research: A Quantitative Literature Review," SERC Discussion Papers 0215, Spatial Economics Research Centre, LSE.
    5. Kim, Jinwon, 2016. "Vehicle fuel-efficiency choices, emission externalities, and urban sprawl," Economics of Transportation, Elsevier, vol. 5(C), pages 24-36.
    6. Chai, Jian & Yang, Ying & Wang, Shouyang & Lai, Kin Keung, 2016. "Fuel efficiency and emission in China's road transport sector: Induced effect and rebound effect," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 188-197.
    7. repec:eco:journ2:2017-03-20 is not listed on IDEAS
    8. Gabriel M. Ahlfeldt & Elisabetta Pietrostefani, 2017. "The Economic Effects of Density: A Synthesis," SERC Discussion Papers 0210, Spatial Economics Research Centre, LSE.
    9. Ahfeldt, Gabriel M. & Pietrostefani, Elisabetta, 2017. "The compact city in empirical research: A quantitative literature review," LSE Research Online Documents on Economics 83638, London School of Economics and Political Science, LSE Library.
    10. Bhat, Chandra R., 2015. "A new generalized heterogeneous data model (GHDM) to jointly model mixed types of dependent variables," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 50-77.
    11. Song, Siqi & Diao, Mi & Feng, Chen-Chieh, 2016. "Individual transport emissions and the built environment: A structural equation modelling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 206-219.
    12. Bhat, Chandra R. & Astroza, Sebastian & Bhat, Aarti C. & Nagel, Kai, 2016. "Incorporating a multiple discrete-continuous outcome in the generalized heterogeneous data model: Application to residential self-selection effects analysis in an activity time-use behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 52-76.
    13. Kristof Dascher, 2013. "Climate Change and Urban Contours: Why Countries with Denser City Centers Fight Climate Change Harder," ERSA conference papers ersa13p744, European Regional Science Association.
    14. Ahlfeldt, Gabriel M. & Pietrostefani, Elisabetta, 2017. "The economic effects of density: A synthesis," LSE Research Online Documents on Economics 83628, London School of Economics and Political Science, LSE Library.
    15. Dillon, Harya S. & Saphores, Jean-Daniel & Boarnet, Marlon G., 2015. "The impact of urban form and gasoline prices on vehicle usage: Evidence from the 2009 National Household Travel Survey," Research in Transportation Economics, Elsevier, vol. 52(C), pages 23-33.

    More about this item

    Keywords

    Social and Behavioral Sciences;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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