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Can subsidy programs change the customer base of next-generation vehicles?

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  • Jiaxing Wang

    (Department of Economics, Aoyama Gakuin University. 4-4-25 Shibuya, Shibuya-ku, Tokyo, 150-8366, Japan.)

  • Shigeru Matsumoto

    (Department of Economics, Aoyama Gakuin University. 4-4-25 Shibuya, Shibuya-ku, Tokyo, 150-8366, Japan.)

Abstract

Although many countries have implemented subsidy programs for next-generation vehicles in order to reduce energy consumption and greenhouse gas emissions from the transportation sector, the effect of such programs has not yet been fully investigated in terms of their influence of households f vehicle selection. The Japanese government introduced a subsidy program entitled gEco-car h during 2009 and 2012. In this study, we apply multinomial logit models to micro-level data of vehicle selection from the National Survey of Family Income and Expenditure in order to identify the types of households who switched from conventional gasoline vehicles to hybrid electric vehicles (HEVs) using this subsidy program. Our analyses demonstrate that higher income households who used compact gasoline vehicles (CGVs) before the Eco-car program switched to HEVs using the subsidy, whereas those who used regular gasoline vehicles (RGVs) did not switched to HEVs. Although seniors chose HEVs over CGVs before the Eco-car program, younger consumers began choosing HEVs over CGVs after the Eco-car program. We also find that gasoline price became a less important factor on HEV purchase after the Eco-car program.

Suggested Citation

  • Jiaxing Wang & Shigeru Matsumoto, 2019. "Can subsidy programs change the customer base of next-generation vehicles?," RIEEM Discussion Paper Series 1904, Research Institute for Environmental Economics and Management, Waseda University.
  • Handle: RePEc:was:dpaper:1904
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    File URL: http://www.waseda.jp/prj-rieem/dp/dp1904.pdf
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    References listed on IDEAS

    as
    1. Qing Su, 2014. "Purchase and Utilization of New Fuel Efficient Vehicles in the US: Evidence from the 2009 National Household Transportation Survey Data," International Journal of Energy Economics and Policy, Econjournals, vol. 4(1), pages 1-14.
    2. repec:eee:enepol:v:125:y:2019:i:c:p:286-292 is not listed on IDEAS
    3. Daniel J. Graham & Stephen Glaister, 2002. "The Demand for Automobile Fuel: A Survey of Elasticities," Journal of Transport Economics and Policy, University of Bath, vol. 36(1), pages 1-25, January.
    4. Liu, Yizao, 2014. "Household demand and willingness to pay for hybrid vehicles," Energy Economics, Elsevier, vol. 44(C), pages 191-197.
    5. Chandra, Ambarish & Gulati, Sumeet & Kandlikar, Milind, 2010. "Green drivers or free riders? An analysis of tax rebates for hybrid vehicles," Journal of Environmental Economics and Management, Elsevier, vol. 60(2), pages 78-93, September.
    6. Coad, Alex & de Haan, Peter & Woersdorfer, Julia Sophie, 2009. "Consumer support for environmental policies: An application to purchases of green cars," Ecological Economics, Elsevier, vol. 68(7), pages 2078-2086, May.
    7. Yoshifumi Konishi & Meng Zhao, 2017. "Can Green Car Taxes Restore Efficiency? Evidence from the Japanese New Car Market," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(1), pages 51-87.
    8. Ozaki, Ritsuko & Sevastyanova, Katerina, 2011. "Going hybrid: An analysis of consumer purchase motivations," Energy Policy, Elsevier, vol. 39(5), pages 2217-2227, May.
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    More about this item

    Keywords

    Eco-car program; Hybrid electric vehicles; Micro-level data; Multinomial logit model;

    JEL classification:

    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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