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Household structure and electricity consumption in Ghana

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  • Amoako, Samuel
  • Andoh, Francis Kwaw
  • Asmah, Emmanuel Ekow

Abstract

Ghana has a rising residential electricity consumption of 47% of total generation while at the same time experiencing a worsening household age-dependency ratio considered to be above the global average. Using the most recent Ghana Living Standards Survey (2016/17 i.e., the seventh round), and employing logistic regression analyses, this paper examines how and the extent to which household age-dependency (0–14 and 64+) and other sociodemographic characteristics of Ghanaian households influences residential electricity consumption. In the face of worsening climate change partly attributable to high energy consumption, understanding the role household structure in residential electricity consumption across gender and location is critical in designing appropriate demand-side management policies. The results show that dependency ratio increases electricity consumption by approximately 12.4%. Furthermore, female-headed households with dependents tend to use less; or have reduced electricity usage compared to a male-headed household with dependents. The study recommends among others, the use of local government to spearhead education on energy efficiency especially at the household level and the establishment of green financing scheme for importers, manufacturers, and households.

Suggested Citation

  • Amoako, Samuel & Andoh, Francis Kwaw & Asmah, Emmanuel Ekow, 2023. "Household structure and electricity consumption in Ghana," Energy Policy, Elsevier, vol. 182(C).
  • Handle: RePEc:eee:enepol:v:182:y:2023:i:c:s030142152300352x
    DOI: 10.1016/j.enpol.2023.113767
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    as
    1. Zheng, Xinye & Wei, Chu & Qin, Ping & Guo, Jin & Yu, Yihua & Song, Feng & Chen, Zhanming, 2014. "Characteristics of residential energy consumption in China: Findings from a household survey," Energy Policy, Elsevier, vol. 75(C), pages 126-135.
    2. He, Xiaoping & Reiner, David, 2016. "Electricity demand and basic needs: Empirical evidence from China's households," Energy Policy, Elsevier, vol. 90(C), pages 212-221.
    3. Nidhi Tewathia, 2014. "Determinants of the Household Electricity Consumption: A Case Study of Delhi," International Journal of Energy Economics and Policy, Econjournals, vol. 4(3), pages 337-348.
    4. Paul Nduhuura & Matthias Garschagen & Abdellatif Zerga, 2021. "Impacts of Electricity Outages in Urban Households in Developing Countries: A Case of Accra, Ghana," Energies, MDPI, vol. 14(12), pages 1-26, June.
    5. Baldini, Mattia & Trivella, Alessio & Wente, Jordan William, 2018. "The impact of socioeconomic and behavioural factors for purchasing energy efficient household appliances: A case study for Denmark," Energy Policy, Elsevier, vol. 120(C), pages 503-513.
    6. Wright, Andrew & Firth, Steven, 2007. "The nature of domestic electricity-loads and effects of time averaging on statistics and on-site generation calculations," Applied Energy, Elsevier, vol. 84(4), pages 389-403, April.
    7. Kavousian, Amir & Rajagopal, Ram & Fischer, Martin, 2013. "Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior," Energy, Elsevier, vol. 55(C), pages 184-194.
    8. Kniesner Thomas J & Viscusi W. Kip & Ziliak James P, 2006. "Life-Cycle Consumption and the Age-Adjusted Value of Life," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 5(1), pages 1-36.
    9. Stephanie Paige Williams & Gladman Thondhlana & Harn Wei Kua, 2020. "Electricity Use Behaviour in a High-Income Neighbourhood in Johannesburg, South Africa," Sustainability, MDPI, vol. 12(11), pages 1-19, June.
    10. Jaehyeok Kim & Minwoo Jang & Donghyun Shin, 2019. "Examining the Role of Population Age Structure upon Residential Electricity Demand: A Case from Korea," Sustainability, MDPI, vol. 11(14), pages 1-19, July.
    11. Robin Burgess & Michael Greenstone & Nicholas Ryan & Anant Sudarshan, 2020. "The Consequences of Treating Electricity as a Right," Journal of Economic Perspectives, American Economic Association, vol. 34(1), pages 145-169, Winter.
    12. Broadstock, David C. & Li, Jiajia & Zhang, Dayong, 2016. "Efficiency snakes and energy ladders: A (meta-)frontier demand analysis of electricity consumption efficiency in Chinese households," Energy Policy, Elsevier, vol. 91(C), pages 383-396.
    13. Zhou, Shaojie & Teng, Fei, 2013. "Estimation of urban residential electricity demand in China using household survey data," Energy Policy, Elsevier, vol. 61(C), pages 394-402.
    14. Salari, Mahmoud & Javid, Roxana J., 2017. "Modeling household energy expenditure in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 822-832.
    15. Filippini, Massimo & Pachauri, Shonali, 2004. "Elasticities of electricity demand in urban Indian households," Energy Policy, Elsevier, vol. 32(3), pages 429-436, February.
    16. Brantley Liddle, 2011. "Consumption-Driven Environmental Impact and Age Structure Change in OECD Countries," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 24(30), pages 749-770.
    17. Adom, Philip Kofi & Bekoe, William & Akoena, Sesi Kutri Komla, 2012. "Modelling aggregate domestic electricity demand in Ghana: An autoregressive distributed lag bounds cointegration approach," Energy Policy, Elsevier, vol. 42(C), pages 530-537.
    18. Twerefou, Daniel Kwabena & Abeney, Jacob Opantu, 2020. "Efficiency of household electricity consumption in Ghana," Energy Policy, Elsevier, vol. 144(C).
    19. Yu, Yihua & Guo, Jin, 2016. "Identifying electricity-saving potential in rural China: Empirical evidence from a household survey," Energy Policy, Elsevier, vol. 94(C), pages 1-9.
    20. Brounen, Dirk & Kok, Nils & Quigley, John M., 2012. "Residential energy use and conservation: Economics and demographics," European Economic Review, Elsevier, vol. 56(5), pages 931-945.
    21. Solveig Erlandsen & Ragnar Nymoen, 2008. "Consumption and population age structure," Journal of Population Economics, Springer;European Society for Population Economics, vol. 21(3), pages 505-520, July.
    22. Adom, Philip Kofi, 2016. "Electricity Supply and System losses in Ghana. What is the red line? Have we crossed over?," MPRA Paper 74559, University Library of Munich, Germany, revised 11 Nov 2016.
    23. McLoughlin, Fintan & Duffy, Aidan & Conlon, Michael, 2013. "Evaluation of time series techniques to characterise domestic electricity demand," Energy, Elsevier, vol. 50(C), pages 120-130.
    24. Dimitra Kotsila & Persefoni Polychronidou, 2021. "Determinants of household electricity consumption in Greece: a statistical analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-20, December.
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    More about this item

    Keywords

    Electricity; Age dependency; Regional; District; Cluster; Ghana;
    All these keywords.

    JEL classification:

    • D10 - Microeconomics - - Household Behavior - - - General
    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis
    • D13 - Microeconomics - - Household Behavior - - - Household Production and Intrahouse Allocation
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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