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Household vehicle type holdings and usage: an application of the multiple discrete-continuous extreme value (MDCEV) model

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  • Bhat, Chandra R.
  • Sen, Sudeshna

Abstract

The increasing diversity of vehicle type holdings and the growing usage of vehicles by households have serious policy implications for traffic congestion and air pollution. Consequently, it is important to accurately predict the vehicle holdings of households as well as the vehicle miles of travel by vehicle type to project future traffic congestion and mobile source emission levels. In this paper, we apply a multiple discrete-continuous extreme value model to analyze the holdings and use of multiple vehicle types by households. Data for the analysis is drawn from a 2000 San Francisco Bay Area survey. The model results indicate the important effects of household demographics, residence location variables and vehicle attributes on vehicle type holdings and use. The model developed in the paper can be applied to predict the impact of demographic, land use, and operating cost changes on vehicle type holdings and usage. Such predictions are important at a time when the household demographic characteristics are changing rapidly in the United States. The predictions can also inform the design of proactive land-use, economic, and transportation policies to influence household vehicle holdings and usage in a way that reduces traffic congestion and air quality problems.

Suggested Citation

  • Bhat, Chandra R. & Sen, Sudeshna, 2006. "Household vehicle type holdings and usage: an application of the multiple discrete-continuous extreme value (MDCEV) model," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 35-53, January.
  • Handle: RePEc:eee:transb:v:40:y:2006:i:1:p:35-53
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    References listed on IDEAS

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    1. Hanemann, W Michael, 1984. "Discrete-Continuous Models of Consumer Demand," Econometrica, Econometric Society, vol. 52(3), pages 541-561, May.
    2. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    3. Neeraj Arora & Greg M. Allenby & James L. Ginter, 1998. "A Hierarchical Bayes Model of Primary and Secondary Demand," Marketing Science, INFORMS, vol. 17(1), pages 29-44.
    4. Mannering, Fred & Winston, Clifford & Starkey, William, 2002. "An exploratory analysis of automobile leasing by US households," Journal of Urban Economics, Elsevier, vol. 52(1), pages 154-176, July.
    5. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    6. Choo, Sangho & Mokhtarian, Patricia L., 2004. "What type of vehicle do people drive? The role of attitude and lifestyle in influencing vehicle type choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(3), pages 201-222, March.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, July.
    8. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    9. Jong, Gerard De, 1996. "A disaggregate model system of vehicle holding duration, type choice and use," Transportation Research Part B: Methodological, Elsevier, vol. 30(4), pages 263-276, August.
    10. Bhat, Chandra R., 1995. "A heteroscedastic extreme value model of intercity travel mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 29(6), pages 471-483, December.
    11. Berkovec, James & Rust, John, 1985. "A nested logit model of automobile holdings for one vehicle households," Transportation Research Part B: Methodological, Elsevier, vol. 19(4), pages 275-285, August.
    12. Berkovec, James, 1985. "Forecasting automobile demand using disaggregate choice models," Transportation Research Part B: Methodological, Elsevier, vol. 19(4), pages 315-329, August.
    13. Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
    14. Jaehwan Kim & Greg M. Allenby & Peter E. Rossi, 2002. "Modeling Consumer Demand for Variety," Marketing Science, INFORMS, vol. 21(3), pages 229-250, December.
    15. Pradeep K. Chintagunta, 1993. "Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households," Marketing Science, INFORMS, vol. 12(2), pages 184-208.
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