Carbon Emissions and Economic Growth in Africa: Are They Related?

Olubusoye, Olusanya E.; Musa, Donald

doi:10.1080/23322039.2020.1850400

Cited by 71 publications

(51 citation statements)

References 89 publications

(99 reference statements)

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“…Our specificity resides in the fact that we analyse whether African countries behave homogeneously in relation to how economic development affects the environmental pollution. Second, available evidence on the continent (including Abid, 2016;Adzawla et al, 2019;Demissew Beyene & Kotosz, 2020;Olubusoye & Musa, 2020;Omotor, 2016;Yusuf et al, 2020) provide inconclusive results on the pollution-effect of growth. More importantly, we find that no study has considered spatial dependence in the assessment of the EKC in Africa, while recent evidence shows that Co2 emissions and economic development tend to cluster across geographical space (Rio & Gianmoena, 2018).…”

Section: Introductionmentioning

confidence: 99%

Co2 emissions and economic development in Africa: Evidence from a dynamic spatial panel model

Espoir

Sunge

2021

Journal of Environmental Management

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Section: Introductionmentioning

confidence: 99%

Co2 emissions and economic development in Africa: Evidence from a dynamic spatial panel model

Espoir

Sunge

2021

Journal of Environmental Management

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“…Energy consumption based on fossil fuel, agriculture production, and other determinants contribute to CO 2 emissions in North Africa and some selected countries in East and South Africa (Siti, 2014;Umar et al, 2021). In addition, Olubusoye and Musa (2020) in their study showed that an increase in economic growth as well induces more of CO 2 emissions in most African countries. Using the Kaya identity, Ayompe et al (2020) studied energy-related CO 2 emissions data of 27 African countries from 1990-2017.…”

Section: Introductionmentioning

confidence: 96%

Bayesian Spatio-temporal Analysis of Greenhouse Gas Emissions in Africa

Akeresola¹,

Gayawan

2021

Preprint

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Global warming is a driver of climate change and is attributed to the increasing concentration of greenhouse gases in the atmosphere due to human activities. Although Africa contributes the least to global greenhouse gas emissions, its emissions are still on the increase. This study analyzes the spatial effect, temporal effect, and the interaction of these effects on these emissions in Africa. A 27-year greenhouse gas emissions data of some selected African countries was studied using Bayesian Spatio-temporal analysis within a Bayesian framework. Inference was based on integrated nested Laplace approximation implemented using the R-INLA package in R. Various subsets of Spatio-temporal models were fitted, including those that accounted for boundary shared among countries. Results show that models with the Spatio-temporal interaction effect outperform models that did not take this effect into account, confirming findings from existing literature. Findings from this study also revealed that the boundary shared among countries impacts greenhouse gas emissions. Countries that are less likely to have high greenhouse gas emissions but shared boundaries with those likely to have high estimates eventually had a high estimate of emissions over a long period. Controlling and reducing greenhouse gas emissions in Africa should be a collective effort, particularly among countries sharing boundaries.

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“…In the STD region, growth in Co2 per capita is negative (-1.29%), yet its growth in GDP per capita (3.55%) is higher than that of WTM (3.17%). Despite the existence of different climate regimes in Africa, existing studies on the nexus between climate change and economic growth (Abid, 2016;Chekouri et al, 2021;Olubusoye & Musa, 2020;Omotor, 2016;Yusuf et al, 2020) have ignored the heterogeneous effects of climate regimes and indeed temperature variations. Attempts to account for specific conditions are restricted to the country's levels of development (Olubusoye & Musa, 2020), oil-producing countries (Yusuf et al, 2020), and geographical regions (Demissew Beyene & Kotosz, 2020;Omotor, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…To capture the heterogeneous effects based on climate regime criterium, we utilise the wavelet methods. Contrary to several empirical studies in Africa (see, for example, Abid, 2016;Chekouri et al, 2021;Olubusoye & Musa, 2020;Omotor, 2016;Yusuf et al, 2020), in this study, we adopt the wavelet coherence transform, multiple wavelets and the partial wavelet analysis for decomposing the time in different time scales. The wavelet method has a consistent set of advantages compared to classical time domains.…”

Section: Introductionmentioning

confidence: 99%

CO2 emissions and economic growth: Assessing the heterogeneous effects across climate regimes in Africa

Espoir

Mudiangombe

Bannor

et al. 2022

Science of The Total Environment

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Carbon Emissions and Economic Growth in Africa: Are They Related?

Cited by 71 publications

References 89 publications

Co2 emissions and economic development in Africa: Evidence from a dynamic spatial panel model

Co2 emissions and economic development in Africa: Evidence from a dynamic spatial panel model

Bayesian Spatio-temporal Analysis of Greenhouse Gas Emissions in Africa

CO2 emissions and economic growth: Assessing the heterogeneous effects across climate regimes in Africa

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