Economic inequalities and rural-urban disparities in clean cooking fuel use in Ghana

Tabiri, Kwasi Gyabaa; Adusah‐Poku, Frank; Novignon, Jacob

doi:10.1016/j.esd.2022.05.001

Cited by 15 publications

(2 citation statements)

References 27 publications

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“…Although various WASH services projects have been conducted in Uzbekistan [25], the recent focus on clean energy may be a potential factor [42,43]. A study on economic inequalities in clean fuels for cooking reported inequalities favoring high-income households in the use of clean cooking fuels in Ghana [44]. Another study on household energy choices in Ghana found that price and household income were factors influencing household choices of fuels, with higher income households more likely to purchase modern fuels than traditional ones [45].…”

Section: Discussionmentioning

confidence: 99%

Regional Disparities in Safe and Clean Environments in Uzbekistan: Analysis of 2021–2022 Uzbekistan Multiple Indicator Cluster Survey Data

Moon,

Choi,

Kim

2024

Sustainability

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Background: Water, sanitation, and hygiene (WASH) services and clean fuels are representative factors of a clean and safe residential environment. Uzbekistan faces environmental issues and ranks low among countries on the Environmental Performance Index. This study aimed to identify regional disparities and wealth inequalities in WASH services and clean fuels in Uzbekistan. Methods: We employed raw data from the 2021–2022 Uzbekistan Multiple Indicator Cluster Survey (MICS) and the WASH and clean fuels coverage were analyzed. For each of the variables with the lowest coverage within WASH services and clean fuels variables, we evaluated the disparities between urban and rural areas and calculated the concentration index (CI). Results: Among WASH services and clean fuels, basic handwashing and clean fuels for space heating demonstrated the lowest coverage. In most regions, urban areas had higher coverage of basic handwashing and clean fuels for space heating compared to rural areas. The CI of clean fuels for space heating was 0.2141 or higher in five areas. The CI was notably high in areas with low coverage of WASH services and clean fuel for space heating. Conclusions: Basic handwashing and clean fuels for space heating showed varied regional coverage patterns and wealth-related inequalities. The results of this study can provide evidence for policy formulation, particularly in addressing disparities.

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Section: Discussionmentioning

confidence: 99%

Regional Disparities in Safe and Clean Environments in Uzbekistan: Analysis of 2021–2022 Uzbekistan Multiple Indicator Cluster Survey Data

Moon,

Choi,

Kim

2024

Sustainability

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“…Ghana generates enough electricity to power its economy nonetheless it is coming from mainly from fossil fuel sources. Even though Ghana has adequate energy access now and generates enough electricity, household of electricity for cooking is yet very low at about 20% access to modern cooking solutions (Tabiri, et al 2022). According to ( M.A.…”

Section: Literature Reviewmentioning

confidence: 99%

Modelling the electricity generation dynamics of Ghana. A Structural VAR Approach

Atuahene

Alemzero

2022

Preprint

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This study estimates endogenous parameters to ascertain the dynamics in the electricity generation sector in Ghana. An unrestricted VAR model is utilized to examine the empirical ramifications of the Ghanaian electricity energy sector and power consumption. The data period ranges between 2002 02021. Precisely, the results detected structural long run and short run headwinds to the unrestricted models. The findings depict that the reactions of GDP growth rate and electricity from fossil fuels react directly to headwinds based on their correlation. Also, there is feedback relationship between GDP growth rate rand electricity from fossil fuel sources since they are significant, from the granger causality analysis. Furthermore, the impulse function depicts GDP growth rate reacts to exogenous headwinds and the impacts are enduring to an extended period. Furthermore, the Variance decomposition results backed this analysis via having renewable energy without hydropower explaining less than 1% variance due to shocks and total global greenhouse emissions further explains about 85% variance due to headwinds in the time period. Electricity from fossil fuels sources explains more than 100% of the variance owing to headwinds hitting the system. Implying the nation’s overreliance on conventional energy source. Installed renewable energy will grow to over 2500MW by 2036, growing at 57.8% %.Ultimately, this calls for a rapid transformation of energy landscape in the country to a sustainable pathway. This will inform policy discourses regarding diversifying Ghana’s energy mix.

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Impacts of crop and income diversification on poverty and inequality among rural farm households in Ghana

Horlu

2024

Environ Dev Sustain

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Economic inequalities and rural-urban disparities in clean cooking fuel use in Ghana

Cited by 15 publications

References 27 publications

Regional Disparities in Safe and Clean Environments in Uzbekistan: Analysis of 2021–2022 Uzbekistan Multiple Indicator Cluster Survey Data

Regional Disparities in Safe and Clean Environments in Uzbekistan: Analysis of 2021–2022 Uzbekistan Multiple Indicator Cluster Survey Data

Modelling the electricity generation dynamics of Ghana. A Structural VAR Approach

Impacts of crop and income diversification on poverty and inequality among rural farm households in Ghana

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