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    Are Electric Vehicles Incentives Effective? Evidence from the Fifty U.S. States

    Cover for Are Electric Vehicles Incentives Effective? Evidence from the Fifty U.S. States
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    View/Open: Wang_georgetown_0076M_14607.pdf (1.0MB) Bookview

    Creator
    Wang, Shiying
    Advisor
    Catilina, Eliane
    ORCID
    0000-0001-9633-5427
    Abstract
    This study evaluates the effectiveness of state-level electric vehicles (EVs) incentives in the United States. Many barriers can prevent electric vehicles from gaining a larger market share. This study will mainly focus on two of these – “model availability” on the EV supply-side; and the “knowledge gap” on the EV demand-side to examine the heterogeneities in state-level incentive allocation structure and effectiveness. A three-level Stackelberg game model is used to illustrate the interactions among state governments, electric vehicle manufacturers, and electric vehicle consumers to understand how government subsidies should be allocated. A rich panel data set of annual state-level EV data is used to empirically evaluate the effectiveness of state incentives and policies. In addition, result of sentiment analysis of twitter data is introduced to categorize state-level public perception of electric vehicles, which can explain the importance of campaign plans and the networks among states, to better inform the future policies.
     
    My results show an overall 5%-14% increase in EV sales per every $1000 increase in subsidies across all the states. State-level climate commitments such as ZEV mandates and emissions reduction targets have a positive effect on the promotion of EV purchases, but do not significantly increase the effect of other policies instruments. Regional alliance and educational campaign activities can increase the effectiveness of incentives. More specifically, the results from frequency words and Latent Dirichlet Allocation (LDA) model on Twitter data indicate that linking electric vehicles to some topics such as climate change, healthcare, battery etc. will gain more public attention.
     
    Description
    M.P.P.
    Permanent Link
    http://hdl.handle.net/10822/1059653
    Date Published
    2020
    Subject
    Electric Vehicles; Incentives; Sentiment analysis; Stackelberg Game; Twitter API; Environmental economics; Climatic changes; Power resources; Environmental economics; Climate change; Energy;
    Type
    thesis
    Publisher
    Georgetown University
    Extent
    39 leaves
    Collections
    • Graduate Theses and Dissertations - Public Policy
    Metadata
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    Georgetown University Seal
    ©2009 - 2022 Georgetown University Library
    37th & O Streets NW
    Washington DC 20057-1174
    202.687.7385
    digitalscholarship@georgetown.edu
    Accessibility