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The impact of CO2 taxation on Swiss households' heating demand

Author

Listed:
  • Laurent Ott
  • Sylvain Weber

Abstract

This paper investigates the impacts of the Swiss CO2 levy on households' heating demand. Using a difference-in-differences approach combined with inverse probability of treatment weighting, we test whether the 2016 carbon tax rate increase had a short-term impact on Swiss households' heating consumption and propensity to renovate. Micro-level data from the 2016 and 2017 waves of the Swiss Household Energy Demand Survey (SHEDS) are used to estimate the models. In both cases, no statistically significant effect can be detected across a variety of specifications. Even though further research is needed to investigate possible long-run impacts, our findings question the relevance of this policy instrument under its current form to lower households' greenhouse gas emissions. Additional measures might be implemented to improve its efficiency.

Suggested Citation

  • Laurent Ott & Sylvain Weber, 2018. "The impact of CO2 taxation on Swiss households' heating demand," IRENE Working Papers 18-09, IRENE Institute of Economic Research.
  • Handle: RePEc:irn:wpaper:18-09
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    References listed on IDEAS

    as
    1. Stern,Nicholas, 2007. "The Economics of Climate Change," Cambridge Books, Cambridge University Press, number 9780521700801, September.
    2. Rivers, Nicholas & Schaufele, Brandon, 2015. "Salience of carbon taxes in the gasoline market," Journal of Environmental Economics and Management, Elsevier, vol. 74(C), pages 23-36.
    3. Roberton C. Williams III & Hal Gordon & Dallas Burtraw & Jared C. Carbone & Richard D. Morgenstern, 2015. "The Initial Incidence of a Carbon Tax Across Income Groups," National Tax Journal, National Tax Association;National Tax Journal, vol. 68(1), pages 195-214, March.
    4. Maral Kichian, 2018. "Carbon Tax Saliency: The Case of B.C. Diesel Demand," Cahiers de recherche CREATE 2018-01, CREATE.
    5. Puhani, Patrick A., 2012. "The treatment effect, the cross difference, and the interaction term in nonlinear “difference-in-differences” models," Economics Letters, Elsevier, vol. 115(1), pages 85-87.
    6. Baranzini, Andrea & Weber, Sylvain, 2013. "Elasticities of gasoline demand in Switzerland," Energy Policy, Elsevier, vol. 63(C), pages 674-680.
    7. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, September.
    8. Tiezzi, Silvia, 2005. "The welfare effects and the distributive impact of carbon taxation on Italian households," Energy Policy, Elsevier, vol. 33(12), pages 1597-1612, August.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Carbon tax; energy consumption; fossil fuel; policy evaluation; inverse probability of treatment weighting; difference-in-differences;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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