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Persistent and Transient Energy Poverty: A Multi-Level Analysis in Spain

Author

Listed:
  • Pourkhanali, Armin

    (Economics Finance & Marketing, Royal Melbourne Institute of Technology)

  • Kholghi, Donya

    (Department of Mathematics, Institute for Advanced Studies in Basic Sciences)

  • Llorca, Manuel

    (Department of Economics, Copenhagen Business School)

  • Jamasb, Tooraj

    (Department of Economics, Copenhagen Business School)

Abstract
This empirical analysis investigates the determinants and dynamics of energy poverty in Spain using a combination of traditional regression models and machine learning techniques. The study identifies significant determinants of energy poverty, including income, housing type, education level, and health conditions. Findings demonstrate that lower income, specific housing types, and lower education levels increase the likelihood of energy poverty. This study also investigates the dynamics of energy poverty, and the results show the coexistence of both transient and persistent aspects of energy poverty. 35% of Spanish households struggled to maintain adequate warmth in their homes during at least one period from 2016 to 2021. While a small portion (5%) experienced chronic energy poverty, indicating their inability to maintain their home adequate warmth throughout the 70% sample period. Finally, the study offers valuable insights into the dynamics and drivers of energy poverty. It underscores both its temporary and persistent characteristics, in addition to the impact of socioeconomic factors.

Suggested Citation

  • Pourkhanali, Armin & Kholghi, Donya & Llorca, Manuel & Jamasb, Tooraj, 2023. "Persistent and Transient Energy Poverty: A Multi-Level Analysis in Spain," Working Papers 9-2023, Copenhagen Business School, Department of Economics.
    • Handle: RePEc:hhs:cbsnow:2023_009
    as

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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Transient and persistent energy poverty; Self-assessed health; Dynamic random effects probit; Machine learning;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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