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Optimal incentive for electric vehicle adoption

Author

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  • Falbo, Paolo
  • Pelizzari, Cristian
  • Rizzini, Giorgio

Abstract

This paper is concerned with the interactions between a policymaker and a population of vehicle owners through a bilevel model. The policymaker aims to minimize a cost function to come up with the optimal incentive for encouraging the largest possible percentage of fossil fuel vehicle owners to purchase an electric vehicle. The fossil fuel vehicle owners have to decide whether to purchase an electric vehicle or not. Both the policymaker and the fossil fuel vehicle owners care about the PM10 concentration. In particular, the policymaker can decide to impose a traffic ban if the PM10 concentration exceeds the safety threshold for many consecutive days. Traffic bans generate a cost to the owners of a fossil fuel vehicle. We reduce the initial bilevel problem to a single-level problem and analytically solve it. We further provide a model calibration on real data and a detailed comparative statics.

Suggested Citation

  • Falbo, Paolo & Pelizzari, Cristian & Rizzini, Giorgio, 2022. "Optimal incentive for electric vehicle adoption," Energy Economics, Elsevier, vol. 114(C).
    • Handle: RePEc:eee:eneeco:v:114:y:2022:i:c:s0140988322004066
    DOI: 10.1016/j.eneco.2022.106270
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    References listed on IDEAS

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    Cited by:

    1. Paweł Bryła & Shuvam Chatterjee & Beata Ciabiada-Bryła, 2022. "Consumer Adoption of Electric Vehicles: A Systematic Literature Review," Energies, MDPI, vol. 16(1), pages 1-16, December.
    2. Unnati Tuladhar & Nuttaya Yuangyai & Theerakamol Pengsakul & Saroj Gyawali, 2023. "The Determination of Willingness to Pay for Electrical Vehicles: A Literature Review," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 425-431, September.

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    More about this item

    Keywords

    Environmental Policy; Bilevel Problems; Electric Vehicles;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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