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Public Purchasing Subsidies and the Fear of Missing Out: A Full-Sample Analysis of Electric Vehicle Adoption in Germany

Author

Listed:
  • Carsten Creutzburg

    (Chair for Economic Policy, University of Hamburg)

  • Leo M. Doerr

    (Chair for Economic Policy, University of Hamburg)

  • Wolfgang Maennig

    (Chair for Economic Policy, University of Hamburg)

Abstract

This is the first study to employ a national full sample dataset for a socioeconomic analysis of the adoption of electric vehicles (EVs). We use the most recent vehicle registration dataset from the Fed-eral Motor Transport Authority of Germany, which includes the entire underlying population of German vehicle owners. Combining web-scraped data covering all vehicles available in the German market with actual registration data allows a unique analysis of the individual decisions to purchase an EV. Our results suggest that financial incentives are the most relevant factor for EV adoption, with a €1,000 subsidy in-crease boosting EV choice probability by 1.2 percentage points. Given that EVs currently constitute 12% of newly registered private vehicles in Germany, our model calculates that, in the absence of subsidies, this share would be 1.2%. In contrast, a uniform maximum subsidy of €9,000 from 2011 to 2023 could have increased the adoption rate to 20%. These results underscore the importance of fin ancial incentives in achieving policy targets for EV adoption and suggest that purchase subsidies exhibit increasing marginal returns.

Suggested Citation

  • Carsten Creutzburg & Leo M. Doerr & Wolfgang Maennig, 2025. "Public Purchasing Subsidies and the Fear of Missing Out: A Full-Sample Analysis of Electric Vehicle Adoption in Germany," Working Papers 081, Chair for Economic Policy, University of Hamburg.
    • Handle: RePEc:hce:wpaper:081
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    File URL: http://www.hced.uni-hamburg.de/WorkingPapers/HCED-081.pdf
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    More about this item

    Keywords

    Electric vehicles; Vehicle choice; Financial Incentives; Discrete choice;
    All these keywords.

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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