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The impact of residential density on vehicle usage and fuel consumption: Evidence from national samples

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  • Kim, Jinwon
  • Brownstone, David

Abstract

This paper investigates the impact of residential density on household vehicle usage and fuel consumption. We estimate a simultaneous equations system to account for the potential residential self-selection problem. While most previous studies focus on a specific region, this paper uses national samples from the 2001 National Household Travel Survey. The estimation results indicate that residential density has a statistically significant but economically modest influence on vehicle usage, which is similar to that in previous studies. However, the joint effect of the contextual density measure (density in the context of its surrounding area) and residential density on vehicle usage is quantitatively larger than the sole effect of residential density. Moving a household from a suburban to an urban area reduces household annual mileage by 18%. We also find that a lower neighborhood residential density induces consumer choices toward less fuel-efficient vehicles, which confirms the finding in Brownstone and Golob (2009).

Suggested Citation

  • Kim, Jinwon & Brownstone, David, 2013. "The impact of residential density on vehicle usage and fuel consumption: Evidence from national samples," Energy Economics, Elsevier, vol. 40(C), pages 196-206.
  • Handle: RePEc:eee:eneeco:v:40:y:2013:i:c:p:196-206
    DOI: 10.1016/j.eneco.2013.06.012
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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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    Cited by:

    1. Ahlfeldt, Gabriel M. & Pietrostefani, Elisabetta, 2019. "The economic effects of density: A synthesis," Journal of Urban Economics, Elsevier, vol. 111(C), pages 93-107.
    2. 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.
    3. repec:eee:juecon:v:109:y:2019:i:c:p:27-40 is not listed on IDEAS
    4. 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.
    5. repec:eee:jotrge:v:74:y:2019:i:c:p:341-358 is not listed on IDEAS
    6. 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.
    7. Kim, Jinwon, 2016. "Vehicle fuel-efficiency choices, emission externalities, and urban sprawl," Economics of Transportation, Elsevier, vol. 5(C), pages 24-36.
    8. 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.
    9. repec:eee:ecotra:v:19:y:2019:i:c:1 is not listed on IDEAS
    10. repec:gam:jlands:v:8:y:2019:i:1:p:16-:d:196807 is not listed on IDEAS
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. repec:eco:journ2:2017-03-20 is not listed on IDEAS
    16. 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.
    17. 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.
    18. 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.
    19. 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

    Household vehicle choice; Simultaneous equations systems; Residential density;

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • 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
    • 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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