Estimation and Determinants of Multidimensional Energy Poverty among Households in Nigeria

Ashagidigbi, Waheed Mobolaji; Babatunde, Bashirat Adenike; Ogunniyi, Adebayo; Olagunju, Kehinde Oluseyi; Omotayo, Abiodun Olusola

doi:10.3390/su12187332

Cited by 39 publications

(32 citation statements)

References 28 publications

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“…Likewise, being income poor (OR ¼ 2.03, CI ¼ 1.86-2.22 under Model 1; (OR ¼ 0.34, CI ¼ 0.30-0.40) under Model 2; (OR ¼ 2.35, CI ¼ 2.14-2.59) under Model 3; (OR ¼ 1.25, CI ¼ 1.12-1.39) under Model 4; (OR ¼ 1.48, CI ¼ 1.19-1.84) increased the odds of energy poverty incidences. This result resonates well with that of Ashagidigbi et al (2020), who, in a Nigerian study, found that low-income households depended much on biomass fuels, partly because, sometimes, it is accessed free of charge. A previous study by Anker and Anker (2017) poverty.…”

Section: Determining Factors Associated With Energy Poverty Under An Expenditure-based Approachsupporting

confidence: 87%

“…In addition, some of the determining factors were household size, education level, gender and age of household head, general poverty, region of residence and proportion of working members in the household. Nevertheless, in Nigeria, a recent study by Ashagidigbi et al (2020) showed an average MEPI of 0.38 but still had a high energy poverty incidence. Additionally, male-headed households, age and rural location were found to be enhancing factors for energy poverty.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The inclusion of some of the independent variables was based on the existing literature (Table 4) regarding determinants of energy poverty (Castano- Rosa and Okushima, 2021;Ashagidigbi et al, 2020;Phoumin and Kimura, 2019a,b;Bouzarovski, 2018;Ogwumike and Ozughalu, 2016;Bouzarovski and Petrova, 2015). These variables comprised household demographics such as age, gender, household size, income poverty status, presence of elderly members, presence of children, rural-urban residence and the region in which the household lives.…”

Section: Selection Of the Independent Variables For Assessing Determinants Of Energy Povertymentioning

confidence: 99%

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Examining the state of energy poverty in Rwanda: An inter-indicator analysis

Khundi-Mkomba

Saha

Wali

2021

Heliyon

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This paper adopted an inter-indicator analytical approach to investigate the state of energy poverty in Rwanda. It used a nationally representative sample of 14458 households from Rwanda's Integrated Living Standard Survey conducted between October 2016 and October 2017. The first indicator entailed a multidimensional analysis of energy poverty using eleven pointers of energy deprivation. Each pointer was assigned a weight using principal component analysis to form a household energy poverty index. The paper also employed a ‘modified’ expenditure-based approach that emphasizes affordability and accessibility. This is the approach on which the second indicator of energy poverty was based. This constituted an examination of different levels of household income and energy expenditure patterns as well as the use of biomass for cooking. The results from the multidimensional analysis revealed that the most energy-poor households were concentrated in the southern (30.15%), western (27.69%) and northern (24.86%) provinces of Rwanda. In contrast, ‘the least energy-poor are mostly found in urban areas of the country. A cross-comparison with the second approach showed different magnitudes of energy poverty incidences. Nonetheless, similar trends were observed in terms of areas of concentration of energy poverty. Last, the results from multilevel binary logistic regressions showed that household size, income poverty, education level of the head of the family, rural location and Kigali residentship were determinants of energy poverty.

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Section: Determining Factors Associated With Energy Poverty Under An Expenditure-based Approachsupporting

confidence: 87%

Section: Literature Reviewmentioning

confidence: 99%

Section: Selection Of the Independent Variables For Assessing Determinants Of Energy Povertymentioning

confidence: 99%

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Examining the state of energy poverty in Rwanda: An inter-indicator analysis

Khundi-Mkomba

Saha

Wali

2021

Heliyon

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“…Apart from these two factors, the authors stressed that household income level and fertility also determine the incidence of energy poverty within the rural households of Senegal and Togo. On the other hand, Ashagidigbi et al [31] used the ratio of energy-poor households in the total number of households to measure energy poverty in Nigeria and found that energy poverty is determined by the location of the household as rural households were evidenced to be relatively more energy-poor compared to the urban households. Besides, male-headed households and an older household head were identified as the key drivers of energy poverty in Nigeria.…”

Section: Literature Reviewmentioning

confidence: 99%

The Non-Linear Effects of Energy Efficiency Gains on the Incidence of Energy Poverty

et al. 2021

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Energy poverty is defined as insufficient access to modern energy resources which are relatively cleaner than the traditionally utilized ones. In this regard, the incidence of energy poverty is particularly higher in the cases of the developing countries across the globe. Accordingly, the chronic energy poverty issues in the developing countries within Sub-Saharan Africa have become a major socioeconomic and environmental concern for the associated governments. Hence, this study aims to evaluate the effects of energy efficiency gains and shocks to other key macroeconomic factors on energy poverty in the context of selected Sub-Saharan African nations. In this study, we measure energy poverty in terms of the lack of access to clean cooking fuels and technologies for the population of the selected Sub-Saharan African countries. The overall findings from the common correlated effects panel regression analysis reveal that energy efficiency gains initially aggravate the energy poverty situation but improve it later on; consequently, a U-shaped relationship between energy efficiency and access to clean cooking fuels and technologies is evidenced. Besides, the predicted threshold levels of energy efficiency are observed to be higher than the average energy efficiency level of the Sub-Saharan African nations. Moreover, the results also portray that economic growth, carbon dioxide emissions, foreign direct investment inflows, and international trade are effective in reducing energy poverty. Conversely, financial development is witnessed to be ineffective in influencing the incidence of energy poverty in this region.

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“…Thus, the growth of the Metropolitan Mamminasata economy is predominantly influenced by the strategic economic activity sector, i.e., industry, trade, agriculture, transportation, and educational services. To achieve sustainable development, effective tools are needed to facilitate the sustainability management process and enable the implementation of various strategies and programs that promote the development of strategic economic sectors [91,92]. In the Mamminasata Metropolitan Area, energy resources are very important to support the development of residential areas related to the supply of household energy, which tends to increase due to population growth over time.…”

Section: Economic Growth and Energy Security As Determinants Of City mentioning

confidence: 99%

Economic Evaluation, Use of Renewable Energy, and Sustainable Urban Development Mamminasata Metropolitan, Indonesia

et al. 2021

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The acceleration of the development of the Metropolitan Mamminasata area has an impact on the socio-economic dynamics of the community and the use of excess energy resources. The purpose of this study was to analyze (1) economic growth and energy security work as determinants of urban development for Metropolitan Mamminasata, (2) the effect of economic growth, energy consumption, availability of transportation infrastructure, and renewable energy on the quality of the environment and the sustainability of the Metropolitan Mamminasata system, and (3) renewable energy management strategies and sustainable urban development for Metropolitan Mamminasata. An explanatory sequential approach was used. Data were obtained through observation, surveys, and documentation. The results showed that renewable energy which has the potential to used, in the Mamminasata Metropolitan urban area to support economic growth and increase urban productivity, namely water energy, wind energy, and biomass energy. Furthermore, it takes the effectiveness and efficiency of energy users toward improving environmental quality. Economic growth, energy consumption savings, the availability of transportation infrastructure, and renewable energy have a significant effect on environmental quality, with a determination coefficient of 82.3%, and the sustainability of the Metropolitan Mamminasata system, with a determination coefficient of 75.7%. Use of renewable energy in the management of urban development will require support from government policies, as well as community and business participation. This study recommends a renewable energy management strategy as an important part of supporting the sustainability of urban development in Metropolitan Mamminasata, Indonesia.

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Estimation and Determinants of Multidimensional Energy Poverty among Households in Nigeria

Cited by 39 publications

References 28 publications

Examining the state of energy poverty in Rwanda: An inter-indicator analysis

Examining the state of energy poverty in Rwanda: An inter-indicator analysis

The Non-Linear Effects of Energy Efficiency Gains on the Incidence of Energy Poverty

Economic Evaluation, Use of Renewable Energy, and Sustainable Urban Development Mamminasata Metropolitan, Indonesia

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