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Drivers of Electricity Poverty in Spanish Dwellings: A Quantile Regression Approach

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  • Rafael de Arce

    (Department of Applied Economics (Econometrics), Universidad Autónoma de Madrid (UAM), 28049 Madrid, Spain)

  • Ramón Mahía

    (Department of Applied Economics (Econometrics), Universidad Autónoma de Madrid (UAM), 28049 Madrid, Spain)

Abstract

The main objective of this article is to explore the causes of household electricity poverty in Spain from an innovative perspective. Based on evidence of energy inequality across households with different income levels, a quantile regression approach was used to better capture the heterogeneity of determinants of energy poverty across different levels of electricity expenditure. The results illustrate some interesting and counter-intuitive findings about the relationship between household income and electricity poverty, and the technical efficiency of quantile regression compared to the imprecise results of a standard single coefficient/OLS approach.

Suggested Citation

  • Rafael de Arce & Ramón Mahía, 2019. "Drivers of Electricity Poverty in Spanish Dwellings: A Quantile Regression Approach," Energies, MDPI, vol. 12(11), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:11:p:2089-:d:236154
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    Cited by:

    1. Blanka Tundys & Agnieszka Bretyn & Maciej Urbaniak, 2021. "Energy Poverty and Sustainable Economic Development: An Exploration of Correlations and Interdependencies in European Countries," Energies, MDPI, vol. 14(22), pages 1-25, November.
    2. Chen, Haitao & Zhang, Bin & Wang, Zhaohua, 2022. "Hidden inequality in household electricity consumption: Measurement and determinants based on large-scale smart meter data," China Economic Review, Elsevier, vol. 71(C).

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    Keywords

    electricity poverty; quantile regression;

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