Ashagidigbi, Waheed MobolajiBabatunde. Bashirat AdenikeOgunniyi, Adebayo IsaiahOlagunju, Kehinde OluseyiOmotayo, Abiodun Olusola2024-03-262024-03-262020-09-07Ashagidigbi, W.M., Babatunde, B.A., Ogunniyi, A.I., Olagunju, K.O. and Omotayo, A.O. (2020) ‘Estimation and Determinants of Multidimensional Energy Poverty among Households in Nigeria’, Sustainability. MDPI AG. Available at: https://doi.org/10.3390/su12187332.2071-1050 (electronic)https://doi.org/10.3390/su12187332Publication history: Accepted - 24 August 2020; Published - 7 September 2020.The sustainable use of clean and safe sources of energy is indeed a global challenge. Traditional and unsafe forms of energy use is predominant among households in sub-Saharan Africa. This is not only a threat to the environment, but also constitutes health risk to the population. In the Nigeria context, this study provides the first attempt to estimate household energy poverty status and also investigate the driving factors of household energy poverty status using the National Demographic Health Survey (NDHS) dataset. The analytical techniques adopted in this study are based on Multidimensional Energy Poverty Index (MEPI) and Tobit regression model. Our results show that national average MEPI was 0.38, suggesting that majority of the households are energy poor. Energy poverty is however found to be higher in rural areas than in urban areas. We also found that male-headed households, age, rural sector and northeast residents are found to be the energy poverty enhancing factors, while household income and credit access are energy poverty inhibiting factors. The study concludes that income smoothening among other energy poverty reduction interventions should be prioritized, especially among rural households in order to help them exit energy poverty trap.en© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license http://creativecommons.org/licenses/by/4.0/).energy sourcesenergy povertyTobit regressionMultidimensional approachNigeriaArticle