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Optimal Policy and Network Effects for the Deployment of Zero Emission Vehicles

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  • Guy Meunier
  • Jean-Pierre Ponssard

Abstract

We analyze the impact of indirect network effects in the deployment of zero emission vehicles in a static partial equilibrium model. In most theoretical analysis direct and indirect effects are conflated, and relatively few authors have explicitly considered indirect network effects. We also introduce the market power of vehicle producers and scale effects in the production function. The model exhibits a multiplicity of local social extrema and of market equilibria, suggesting a possibility of lock-in. The optimal set of subsidies is derived so that the Pareto dominating market equilibrium would coincide with the social optimum. This framework is applied to the case of the fuel cell electric (hydrogen) vehicles.

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  • Guy Meunier & Jean-Pierre Ponssard, 2018. "Optimal Policy and Network Effects for the Deployment of Zero Emission Vehicles," CESifo Working Paper Series 7026, CESifo.
    • Handle: RePEc:ces:ceswps:_7026
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    3. Li,Shanjun & Wang,Binglin & Yang,Muxi & Zhang,Fan, 2021. "The Global Diffusion of Electric Vehicles : Lessons from the First Decade," Policy Research Working Paper Series 9882, The World Bank.
    4. Arlt, Marie-Louise & Astier, Nicolas, 2023. "Do retail businesses have efficient incentives to invest in public charging stations for electric vehicles?," Energy Economics, Elsevier, vol. 124(C).
    5. Shanjun Li & Xianglei Zhu & Yiding Ma & Fan Zhang & Hui Zhou, 2022. "The Role of Government in the Market for Electric Vehicles: Evidence from China," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 41(2), pages 450-485, March.
    6. Rolf Golombek & Mads Greaker & Snorre Kverndokk & Lin Ma, 2021. "The Transition to Carbon Capture and Storage Technologies," CESifo Working Paper Series 9047, CESifo.
    7. Rolf Golombek & Mads Greaker & Snorre Kverndokk & Lin Ma, 2023. "Policies to Promote Carbon Capture and Storage Technologies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 85(1), pages 267-302, May.
    8. Randall Wigle, 2019. "The Economic Case for EV Supports? Or: Network Effects, EV Pessimism and EV Supports," LCERPA Working Papers ec0123, Laurier Centre for Economic Research and Policy Analysis, revised 23 Oct 2019.
    9. Koch, Nicolas & Ritter, Nolan & Rohlf, Alexander & Scarazzato, Francesco, 2022. "When is the electric vehicle market self-sustaining? Evidence from Norway," Energy Economics, Elsevier, vol. 110(C).
    10. Brückmann, Gracia, 2022. "Test-drives & information might not boost actual battery electric vehicle uptake?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 204-218.
    11. Rostad Sæther, Simen, 2022. "Mobility at the crossroads – Electric mobility policy and charging infrastructure lessons from across Europe," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 144-159.
    12. Andreassen, Gøril L. & Rosendahl, Knut Einar, 2022. "One or two non-fossil technologies in the decarbonized transport sector?," Resource and Energy Economics, Elsevier, vol. 69(C).
    13. Li,Shanjun & Zhu,Xianglei & Ma,Yiding & Zhang,Fan & Zhou,Hui, 2020. "The Role of Government in the Market for Electric Vehicles : Evidence from China," Policy Research Working Paper Series 9359, The World Bank.

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    More about this item

    Keywords

    E-mobility; network effects; joint incentives for infrastructure and car rebates;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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