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Extreme Energy Poverty Incidence and Determinants in Nigeria: A Multidimensional Approach

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  • Uche M. Ozughalu

    (University of Nigeria)

  • Fidelis O. Ogwumike

    (University of Ibadan)

Abstract

Energy poverty has emerged in recent times as a crucial aspect of poverty, afflicting the developing world in general and Nigeria in particular. Drawing from some of the recent literature on energy poverty measurement, this study measures and discusses the incidence and determinants of extreme energy poverty in Nigeria based on a robust multidimensional energy poverty index that covers five major dimensions and six indicators of deprivation in basic energy services. The study uses the 2010 Harmonised Nigeria Living Standard Survey—obtained from the National Bureau of Statistics, Abuja, Nigeria—for its analysis. The results of the study show, among other things, that over a fifth of the Nigerian population are afflicted by extreme energy poverty and the phenomenon is more pronounced in the rural areas than in the urban areas as well as in Northern Nigeria than in Southern Nigeria. The results also indicate that the determinants of extreme energy poverty include region of residence, household composition as well as age, gender and educational level of household head. The Nigerian government should take urgent and adequate steps to eradicate extreme energy poverty in the country in order to pave the way for rapid and sustainable development in the country.

Suggested Citation

  • Uche M. Ozughalu & Fidelis O. Ogwumike, 2019. "Extreme Energy Poverty Incidence and Determinants in Nigeria: A Multidimensional Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(3), pages 997-1014, April.
    • Handle: RePEc:spr:soinre:v:142:y:2019:i:3:d:10.1007_s11205-018-1954-8
    DOI: 10.1007/s11205-018-1954-8
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    9. Gafa, Dede W. & Egbendewe, Aklesso Y.G., 2021. "Energy poverty in rural West Africa and its determinants: Evidence from Senegal and Togo," Energy Policy, Elsevier, vol. 156(C).
    10. Yuxiang Xie & E. Xie, 2023. "Measuring and Analyzing the Welfare Effects of Energy Poverty in Rural China Based on a Multi-Dimensional Energy Poverty Index," Sustainability, MDPI, vol. 15(18), pages 1-21, September.
    11. Wang, Hanjie & Maruejols, Lucie & Yu, Xiaohua, 2021. "Predicting energy poverty with combinations of remote-sensing and socioeconomic survey data in India: Evidence from machine learning," Energy Economics, Elsevier, vol. 102(C).
    12. Chengchao Wang & Yuan Wang & Haiyan Fang & Bidan Gao & Zudeng Weng & Ying Tian, 2020. "Determinants of Rural Poverty in Remote Mountains of Southeast China from the Household Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 150(3), pages 793-810, August.
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    15. Ngarava, Saul & Zhou, Leocadia & Ningi, Thulani & Chari, Martin M. & Mdiya, Lwandiso, 2022. "Gender and ethnic disparities in energy poverty: The case of South Africa," Energy Policy, Elsevier, vol. 161(C).
    16. Murshed, Muntasir & Ozturk, Ilhan, 2023. "Rethinking energy poverty reduction through improving electricity accessibility: A regional analysis on selected African nations," Energy, Elsevier, vol. 267(C).
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    18. Pedro Macedo & Mara Madaleno & Victor Moutinho, 2022. "A New Composite Indicator for Assessing Energy Poverty Using Normalized Entropy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(3), pages 1139-1163, October.
    19. Enrique Cabello-Vargas & Azucena Escobedo-Izquierdo & Arturo Morales-Acevedo, 2021. "Review on Rural Energy Access Policies," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 157-171.
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    21. Drago, Carlo & Gatto, Andrea, 2023. "Gauging energy poverty in developing countries with a composite metric of electricity access," Utilities Policy, Elsevier, vol. 81(C).

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    More about this item

    Keywords

    Multidimensional; Extreme energy poverty; Incidence; Determinants; Logistic regression; Nigeria;
    All these keywords.

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • R20 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - General

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