Journal
ENERGY ECONOMICS
Volume 98, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.eneco.2021.105266
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In countries with a large share of population in energy poverty, appliance and electricity demand are expected to increase as income rises. The level of adoption of electrical appliances varies significantly by country, appliance type, climate, and income, with a stable share of electricity used for entertainment in all four countries and socio-economic futures. Achieving universal access to electricity can increase total electricity demand but decrease average per capita consumption.
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. (C) 2021 Published by Elsevier B.V.
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