Energy poverty in Uganda: Evidence from a multidimensional approach

• Published in: Energy economics 2021-09, Vol.101, p.105445, Article 105445
• Main Authors: Ssennono, Vincent Fred, Ntayi, Joseph M., Buyinza, Faisal, Wasswa, Francis, Aarakit, Sylvia Manjeri, Mukiza, Chris Ndatira
• Format: Article
• Language: English
• Subjects: Affirmative action; Deprivation; Electrification; Energy; Energy economics; Energy poverty; Incidence; Indexes; Indicators; Inequality; Intensity; Measurement; Multidimensional approach; Multidimensional energy poverty; Poverty; Rural areas; Rural communities; Subgroups; Uganda; Uniform distribution
• ISSN: 0140-9883; 1873-6181
• DOI: 10.1016/j.eneco.2021.105445

Energy poverty measurement has taken various approaches with the most preferred being Multidimensional in nature. This paper augments the multidimensional energy poverty measurement to estimate a national multidimensional energy poverty index for Uganda. It applies the M-Gamma method on data from the 2018 National Electrification Survey (NES) which captures various aspects of energy poverty. Results show that, 66% of Ugandans are multidimensionally energy poor, 33% are severely energy poor and the average deprivation score is 51%. The multidimensional energy poverty index for Uganda (MEPI-U) is estimated at 0.33. Implying that, the proportion of the population that is multidimensionally energy poor is deprived in five or more indicators at the same time. This paper's computed MEPI-U suggests that, exclusion of context specific indicators over estimates multidimensional energy poverty. Further, results show that energy poverty does not follow a uniform distribution, the M-Gamma approach reveals high inequality distribution by residence, gender and regional location. Policies that seek to alleviate the energy deficit in Uganda should be multidimensional, comprehensive and should take into account energy poverty differences across subgroups. Affirmative action interventions targeting the rural areas should continue to be prioritised. •The existing Multidimensional energy poverty approach is augmented to capture inequality among the energy poor using the M-gamma method.•Exclusion of context specific indicators over estimates multidimensional energy poverty and thus underscores the superiority of multidimensional poverty estimates.•The distribution of the energy poor does not follow a uniform distribution. There are more deprivations in rural areas and among the female headed households.