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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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    1. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
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    3. 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.
    4. 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.
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    6. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
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    Cited by:

    1. Gillingham, Kenneth & Munk-Nielsen, Anders, 2019. "A tale of two tails: Commuting and the fuel price response in driving," Journal of Urban Economics, Elsevier, vol. 109(C), pages 27-40.

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