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Determinants of electricity demand for newly electrified low-income African households


  • Louw, Kate
  • Conradie, Beatrice
  • Howells, Mark
  • Dekenah, Marcus


Access to clean, affordable and appropriate energy is an important enabler of development. Energy allows households to meet their most basic subsistence needs; it is a central feature of all the millennium development goals (MDGs) and, while a lack of access to energy may not be a cause of poverty, addressing the energy needs of the impoverished lets them access services which in turn address the causes of poverty. While much is known about the factors affecting the decisions made when choosing between fuel types within a household, few quantitative studies have been carried out in South Africa to determine the extent to which these factors affect energy choice decisions. It is assumed that the factors traditionally included in economic demand such as price and income of the household affect choice; tastes and preferences as well as external factors such as distance to fuel suppliers are expected to influence preferences. This study follows two typical low-income rural sites in South Africa, Antioch and Garagapola, where the Electricity Basic Services Support Tariff (EBSST) was piloted in 2002. The EBSST is set at 50 kWh/month per household for low domestic consumers; this is worth approximately R201 (±US$3). This subsidy is a lifeline tariff, where households receive the set amount of units per month, free of charge irrespective of whether more units are purchased. These data (collected in 2001 and 2002), recently collated with detailed electricity consumption data, allow us to determine the drivers of electricity consumption within these households. The sample analysed is taken from the initial phase of the study, when no FBE had been introduced to the households. This enabled the study presented here to make use of the well-populated datasets to assess what affects the electricity use decision in these households. This paper attempts to assess which factors affected the decision-making process for electricity consumption within these households. A brief history of the electricity industry and the electrification is provided and the theoretical background for the electricity consumption model is provided. It was found that income, woodfuel usage, iron ownership and credit obtained were significant in determining consumption levels within these households. Price and cross-price elasticities were difficult to assess due to lack of data within the sample. The results have many possible implications for policy, including the effect that easily obtained credit has for low-income households.

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  • Louw, Kate & Conradie, Beatrice & Howells, Mark & Dekenah, Marcus, 2008. "Determinants of electricity demand for newly electrified low-income African households," Energy Policy, Elsevier, vol. 36(8), pages 2814-2820, August.
  • Handle: RePEc:eee:enepol:v:36:y:2008:i:8:p:2814-2820

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    References listed on IDEAS

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    Cited by:

    1. Taale, Francis & Kyeremeh, Christian, 2015. "Households' willingness to pay for reliable electricity services in Ghana," MPRA Paper 65780, University Library of Munich, Germany.
    2. Ahlborg, Helene & Boräng, Frida & Jagers, Sverker C. & Söderholm, Patrik, 2015. "Provision of electricity to African households: The importance of democracy and institutional quality," Energy Policy, Elsevier, vol. 87(C), pages 125-135.
    3. Carter, Adrian & Craigwell, Roland & Moore, Winston, 2012. "Price reform and household demand for electricity," Journal of Policy Modeling, Elsevier, vol. 34(2), pages 242-252.
    4. Levin, Todd & Thomas, Valerie M., 2012. "Least-cost network evaluation of centralized and decentralized contributions to global electrification," Energy Policy, Elsevier, vol. 41(C), pages 286-302.
    5. Taale, Francis & Kyeremeh, Christian, 2016. "Households׳ willingness to pay for reliable electricity services in Ghana," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 280-288.
    6. Jones, Rory V. & Fuertes, Alba & Lomas, Kevin J., 2015. "The socio-economic, dwelling and appliance related factors affecting electricity consumption in domestic buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 901-917.
    7. Johanna CHOUMERT & Pascale COMBES MOTEL & Pierre Leonard LE ROUX, 2017. "Stacking up the ladder: A panel data analysis of Tanzanian household energy choices," Working Papers 201724, CERDI.
    8. Naeem Ur Rehman, Khattak & Tariq, Muhammad & Khan, Jangraiz, 2010. "Determinants of Household’s Demand for Electricity in District Peshawar," MPRA Paper 56007, University Library of Munich, Germany, revised 2010.
    9. Arthur, Maria de Fátima S.R. & Bond, Craig A. & Willson, Bryan, 2012. "Estimation of elasticities for domestic energy demand in Mozambique," Energy Economics, Elsevier, vol. 34(2), pages 398-409.
    10. Heshmati, Almas, 2012. "Survey of Models on Demand, Customer Base-Line and Demand Response and Their Relationships in the Power Market," IZA Discussion Papers 6637, Institute for the Study of Labor (IZA).
    11. Chineke, Theo Chidiezie & Ezike, Fabian M., 2010. "Political will and collaboration for electric power reform through renewable energy in Africa," Energy Policy, Elsevier, vol. 38(1), pages 678-684, January.
    12. Johanna Choumert & Pascale Combes Motel & Leonard Le Roux, 2017. "Stacking up the Ladder: A Panel Data Analysis of Tanzanian Household Energy Choices," Working Papers 2017.28, FAERE - French Association of Environmental and Resource Economists.
    13. Amusa, Hammed & Amusa, Kafayat & Mabugu, Ramos, 2009. "Aggregate demand for electricity in South Africa: An analysis using the bounds testing approach to cointegration," Energy Policy, Elsevier, vol. 37(10), pages 4167-4175, October.
    14. Sokona, Youba & Mulugetta, Yacob & Gujba, Haruna, 2012. "Widening energy access in Africa: Towards energy transition," Energy Policy, Elsevier, vol. 47(S1), pages 3-10.
    15. 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.
    16. Büscher, Bram, 2009. "Connecting political economies of energy in South Africa," Energy Policy, Elsevier, vol. 37(10), pages 3951-3958, October.

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