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Simulation of Fuel Poverty in France

Author

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  • Corinne Chaton

    (EDF R&D SEQUOIA - EDF R&D - EDF R&D - EDF - EDF)

  • Alexandre Gouraud

Abstract

The assessment of fuel poverty in mainland France is based mainly on data provided by the French national housing survey. However, the last two surveys date from 2006 and 2014. To understand the change in the number of fuel poverty households, we have developed a microsimulation tool that takes into account the three predominant factors in the notion of fuel poverty, that is, household resources, energy prices and dwelling quality. Our tool includes three multiple linear models for estimating the following: 1. disposable income; 2. energy expenditure; and 3. the probability of performing a thermal renovation. We test our model with real values for variation in energy prices and variation in disposable income and a realistic number of housing renovations. The model is calibrated to the two last French national housing survey, matches the data very well and closely reproduces the number in fuel poverty in the 2012/2014 period. We not only evaluate fuel poverty in France in 2018 but also study the effects of variations in the unemployment rate, energy prices and number of thermal renovations.
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Suggested Citation

  • Corinne Chaton & Alexandre Gouraud, 2020. "Simulation of Fuel Poverty in France," Post-Print halshs-03983370, HAL.
    • Handle: RePEc:hal:journl:halshs-03983370
    DOI: 10.1016/j.enpol.2020.111434
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    References listed on IDEAS

    as
    1. Chaton, Corinne & Lacroix, Elie, 2018. "Does France have a fuel poverty trap?," Energy Policy, Elsevier, vol. 113(C), pages 258-268.
    2. A. Greening, Lorna & Greene, David L. & Difiglio, Carmen, 2000. "Energy efficiency and consumption -- the rebound effect -- a survey," Energy Policy, Elsevier, vol. 28(6-7), pages 389-401, June.
    3. Schenker, Nathaniel & Taylor, Jeremy M. G., 1996. "Partially parametric techniques for multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 22(4), pages 425-446, August.
    4. Schipper, Lee & Grubb, Michael, 2000. "On the rebound? Feedback between energy intensities and energy uses in IEA countries," Energy Policy, Elsevier, vol. 28(6-7), pages 367-388, June.
    5. Grepperud, Sverre & Rasmussen, Ingeborg, 2004. "A general equilibrium assessment of rebound effects," Energy Economics, Elsevier, vol. 26(2), pages 261-282, March.
    6. Daniel F. Heitjan & Roderick J. A. Little, 1991. "Multiple Imputation for the Fatal Accident Reporting System," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 40(1), pages 13-29, March.
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    Cited by:

    1. Marlena Piekut, 2020. "Patterns of Energy Consumption in Polish One-Person Households," Energies, MDPI, vol. 13(21), pages 1-31, October.
    2. Alasseur, Clémence & Chaton, Corinne & Hubert, Emma, 2022. "Optimal contracts under adverse selection for staple goods such as energy: Effectiveness of in-kind insurance," Energy Economics, Elsevier, vol. 106(C).

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    More about this item

    Keywords

    Fuel poverty; Energy prices; Disposable income; Simulation;
    All these keywords.

    JEL classification:

    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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