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On the power of indicators: how the choice of fuel poverty indicator affects the identification of the target population


  • Florian Fizaine
  • Sondès Kahouli


In light of the creation of the EU Energy Poverty Observatory (EPOV) in January 2018 and the increase in debates on how fuel poverty is measured, we propose a critical analysis of fuel poverty indicators and demonstrate that choosing a given indicator is central to the identification of the fuel-poorpopulation.First, we conducted an inter-indicator analysis to show how profiles of fuel-poor households vary depending on the indicator selected. We designed a multidimensional approach based on a multiple correspondence analysis and a hierarchical and partitioning clustering analysis to study characteristics of fuel-poor households. We highlight the difficulty of identifying a fuel-poor ‘typical profile’ and show that the composition of the population depends on the choice of the indicator.Second, we applied an intra-indicator analysis using two objective expenditure-based indicators with thresholds. In particular, we conducted a sensitivity analysis based on a logit model including variables describing household and dwelling characteristics. We show that the profiles of fuel-poor households as well as the drivers of fuel poverty vary considerably with the chosen threshold level.Given these findings, we stress the need to review how we currently rely on conventional fuel poverty indicators to identify target groups and give some recommendations.

Suggested Citation

  • Florian Fizaine & Sondès Kahouli, 2019. "On the power of indicators: how the choice of fuel poverty indicator affects the identification of the target population," Applied Economics, Taylor & Francis Journals, vol. 51(11), pages 1081-1110, March.
  • Handle: RePEc:taf:applec:v:51:y:2019:i:11:p:1081-1110
    DOI: 10.1080/00036846.2018.1524975

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    Cited by:

    1. Rodriguez-Alvarez, Ana & Orea, Luis & Jamasb, Tooraj, 2019. "Fuel poverty and Well-Being:A consumer theory and stochastic frontier approach," Energy Policy, Elsevier, vol. 131(C), pages 22-32.
    2. Agbim, Chinelo & Araya, Felipe & Faust, Kasey M. & Harmon, Dana, 2020. "Subjective versus objective energy burden: A look at drivers of different metrics and regional variation of energy poor populations," Energy Policy, Elsevier, vol. 144(C).
    3. Charlier, Dorothée & Legendre, Bérangère & Ricci, Olivia, 2021. "Measuring fuel poverty in tropical territories: A latent class model," World Development, Elsevier, vol. 140(C).
    4. Kelly, J. Andrew & Clinch, J. Peter & Kelleher, L. & Shahab, S., 2020. "Enabling a just transition: A composite indicator for assessing home-heating energy-poverty risk and the impact of environmental policy measures," Energy Policy, Elsevier, vol. 146(C).

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