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A Dynamic household Alternative-fuel Vehicle Demand Model Using Stated and Revealed Transaction Information

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  • Sheng, Hongyan

Abstract

Improving air quality has long been a big concern for society. The original Clean Air Act was signed by president Nixon in 1970 in accordance to national clamor for environmental healing. In 1990, president Bush signed the Clean Air bill which made significant revisions tot he original Clean Air Act. The Clean Air Act Amendments of 1990 establishes tighter pollution standards for emissions from automobiles and trucks. The new law also allows stricter emission limits for vehicles in California which can be met with any combination of vehicle technology and cleaner fuels. As a result, in the 1990s, California passed a law which mandates the introduction and sale of low-emission vehicles (e.g. natural gas vehicles) and zero-emission vehicles (e.g. electric vehicles). According to the levels set by California Air Resources Board, 10% of all vehicles sold in California must be electric vehicles by year 2003. Moreover, other states are actually considering following California's lead and adopting similar policies and incentive programs.

Suggested Citation

  • Sheng, Hongyan, 1999. "A Dynamic household Alternative-fuel Vehicle Demand Model Using Stated and Revealed Transaction Information," University of California Transportation Center, Working Papers qt0zp4g99j, University of California Transportation Center.
  • Handle: RePEc:cdl:uctcwp:qt0zp4g99j
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    References listed on IDEAS

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    1. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    2. Hausman, Jerry & McFadden, Daniel, 1984. "Specification Tests for the Multinomial Logit Model," Econometrica, Econometric Society, vol. 52(5), pages 1219-1240, September.
    3. Golob, Thomas F. & Bunch, David S. & Brownstone, David, 1997. "A Vehicle Use Forecasting Model Based on Revealed and Stated Vehicle Type Choice and Utilisation Data," University of California Transportation Center, Working Papers qt2x86k20c, University of California Transportation Center.
    4. Brownston, David & Bunch, David S. & Train, Kenneth, 1999. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Department of Economics, Working Paper Series qt7rf7s3nx, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    5. Calfee, John E., 1985. "Estimating the demand for electric automobiles using fully disaggregated probabilistic choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 19(4), pages 287-301, August.
    6. 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.
    7. 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.
    8. Beggs, S. & Cardell, S. & Hausman, J., 1981. "Assessing the potential demand for electric cars," Journal of Econometrics, Elsevier, vol. 17(1), pages 1-19, September.
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