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Personal carbon allowances: Can a budget label do the trick?

Author

Listed:
  • Ewelina Marek

    (Poznan University of Life Sciences)

  • Charles Raux

    (LAET - Laboratoire Aménagement Économie Transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

  • Dirk Engelmann

    (HU Berlin - Humboldt-Universität zu Berlin = Humboldt University of Berlin = Université Humboldt de Berlin)

Abstract

In this study, participants in a computerized experiment were asked to manage Personal Carbon Allowances (PCAs) and tokens (here an experimental currency) simultaneously and to spend their budget on either private or public transportation. They participated in four treatments, which differed with respect to the available budget. Treatments 1 and 2 served as a baseline and concerned the administration of tokens only. In treatment 3, PCAs encompassed an environmental label on the budget in favour of public transportation. This increased choices for public transportation by 12 percentage points, when comparing to treatment 2. In treatment 4, by labelling a part of the budget for public transportation, subjects increased their spending on that transport mode by 15 percentage points when comparing to treatment 2. These findings contribute to the academic and policy discussions on whether PCAs could provide an effective instrument to tackle increasing levels of pollution from transportation.

Suggested Citation

  • Ewelina Marek & Charles Raux & Dirk Engelmann, 2018. "Personal carbon allowances: Can a budget label do the trick?," Post-Print halshs-02125850, HAL.
  • Handle: RePEc:hal:journl:halshs-02125850
    DOI: 10.1016/j.tranpol.2018.06.007
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    3. Yao Li & Shuai Wang, 2023. "Personal emission permit trading scheme: urban spatial equilibrium and planning," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(1), pages 1239-1259, March.
    4. Jianguo Zhou & Dongfeng Chen, 2021. "Carbon Price Forecasting Based on Improved CEEMDAN and Extreme Learning Machine Optimized by Sparrow Search Algorithm," Sustainability, MDPI, vol. 13(9), pages 1-20, April.
    5. Aysegul Kanay & Denis Hilton & Laetitia Charalambides & Jean-Baptiste Corrégé & Eva Inaudi & Laurent Waroquier & Stéphane Cézéra, 2021. "Making the carbon basket count: Goal setting promotes sustainable consumption in a simulated online supermarket," Post-Print hal-03403040, HAL.

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