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Measuring fuel poverty in tropical territories: A latent class model

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  • Charlier, Dorothée
  • Legendre, Bérangère
  • Ricci, Olivia

Abstract

There are well established strategies for measuring fuel poverty in developed countries based on heating factors correlated with household income (expenditure, heating restriction or cold houses), but they do not translate well to tropical regions where climatic conditions and socioeconomic contexts entail different energy use. Fuel poverty in tropical regions has never been defined. We propose a new framework for the identification of fuel-poor households based on Sen's capability approach. We employ latent class model (LCM) methodology to accurately assess fuel poverty in tropical areas using observable objective characteristics of decent, safe and healthy dwellings. This approach enables us to categorize households as fuel-poor or fuel-sufficient. It is also possible to extend the model further by considering the multi-dimensional phenomenon of fuel poverty. We find that the most deprived represent approximately 12% of the population, while 32% of the population is expected to belong to the fuel-sufficient class. An intermediate class encompassing 56% of the population represents vulnerable households that could easily be affected by an exogenous shock. Energy deprivation is much more complex and multidimensional than a binary phenomenon, implying that fuel poverty can be measured with different degrees of exposure. With this research, we enable policy makers to identify a target group of households that should be a top priority in fighting fuel poverty in tropical regions.

Suggested Citation

  • Charlier, Dorothée & Legendre, Bérangère & Ricci, Olivia, 2021. "Measuring fuel poverty in tropical territories: A latent class model," World Development, Elsevier, vol. 140(C).
    • Handle: RePEc:eee:wdevel:v:140:y:2021:i:c:s0305750x20304058
    DOI: 10.1016/j.worlddev.2020.105278
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    Cited by:

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    3. Hoyos-Gómez, Laura S. & Ruiz-Muñoz, Jose F. & Ruiz-Mendoza, Belizza J., 2022. "Short-term forecasting of global solar irradiance in tropical environments with incomplete data," Applied Energy, Elsevier, vol. 307(C).
    4. Charlier, Dorothée, 2021. "Explaining the energy performance gap in buildings with a latent profile analysis," Energy Policy, Elsevier, vol. 156(C).
    5. Chaudhuri, Kausik & Huaccha, Gissell, 2023. "Who bears the energy cost? Local income deprivation and the household energy efficiency gap," Energy Economics, Elsevier, vol. 127(PA).
    6. Bardazzi, Rossella & Charlier, Dorothée & Legendre, Berangère & Pazienza, Maria Grazia, 2023. "Energy vulnerability in Mediterranean countries: A latent class analysis approach," Energy Economics, Elsevier, vol. 126(C).
    7. Mahumane, Gilberto & Mulder, Peter, 2022. "Urbanization of energy poverty? The case of Mozambique," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    8. Dorothée Charlier, 2021. "Explaining the energy performance gap in buildings with a latent profile analysis," Post-Print hal-03894155, HAL.

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    More about this item

    Keywords

    Fuel poverty; Tropical islands; Latent class model; Capabilities approach;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • R - Urban, Rural, Regional, Real Estate, and Transportation Economics

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