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A model of energy poverty and access: Estimating household electricity demand and appliance ownership

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  • Poblete-Cazenave, Miguel
  • Pachauri, Shonali

Abstract

In countries that have a large share of population in energy poverty, appliance and electricity demand can be expected to rise. Approaches to estimate latent demand of energy poor populations often assume a constant income elasticity of demand. Here, we develop a novel simulation-based structural estimation approach to estimate responsiveness of electricity demand to income accounting for non-linearities, and considering other important drivers. We apply the model using micro-data for four developing nations to assess the implications of policy scenarios for achieving the Sustainable Development Goal SDG 7 under different socio-economic futures. We find that under scenarios that include policies to achieve universal access to electricity, total electricity demand is higher but the average per capita is lower than in no access policy futures. We also find that the level of adoption of electrical appliances varies significantly by country, appliance type, climate and income, with a high and stable share of electricity used for entertainment in all four countries and socio-economic futures. However, the share of electricity used for food preservation and preparation and clothes maintenance rises significantly with income as people are able to afford appliances that provide greater convenience. Our results confirm that as energy poor populations gain access to electricity services their demand will rise, but neglecting heterogeneity can result in biased estimates.

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  • Poblete-Cazenave, Miguel & Pachauri, Shonali, 2021. "A model of energy poverty and access: Estimating household electricity demand and appliance ownership," Energy Economics, Elsevier, vol. 98(C).
  • Handle: RePEc:eee:eneeco:v:98:y:2021:i:c:s0140988321001717
    DOI: 10.1016/j.eneco.2021.105266
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    6. Pelz, Setu & Pachauri, Shonali & Falchetta, Giacomo, 2023. "Short-run effects of grid electricity access on rural non-farm entrepreneurship and employment in Ethiopia and Nigeria," World Development Perspectives, Elsevier, vol. 29(C).
    7. Dalia Streimikiene & Grigorios L. Kyriakopoulos, 2023. "Energy Poverty and Low Carbon Energy Transition," Energies, MDPI, vol. 16(2), pages 1-15, January.
    8. Najeeb, A. & Sridharan, S. & Rao, A.B. & Agnihotri, S.B. & Mishra, V., 2024. "Determinants of residential electricity consumption in South, East and South East Asia: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 198(C).
    9. Xuefeng Li & Han Yang & Jin Jia, 2022. "Impact of energy poverty on cognitive and mental health among middle-aged and older adults in China," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-13, December.
    10. Nepal, Rabindra & Best, Rohan & Taylor, Madeline, 2023. "Strategies for reducing ethnic inequality in energy outcomes: A Nepalese example," Energy Economics, Elsevier, vol. 126(C).
    11. Chunli Zhou & Xiqiao Lin & Renhao Wang & Bowei Song, 2023. "Real-Time Carbon Emissions Monitoring of High-Energy-Consumption Enterprises in Guangxi Based on Electricity Big Data," Energies, MDPI, vol. 16(13), pages 1-19, July.

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