2020
DOI: 10.1108/ijesm-04-2020-0004
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Growth threshold-effect on renewable energy consumption in major oil-producing countries in sub-Saharan Africa: a dynamic panel threshold regression estimation

Abstract: Purpose This study aims to explore the relationship between the growth threshold effect on renewable energy consumption (REC) in the major oil-producing countries in sub-Saharan Africa (SSA) over the period 1990–2018. Design/methodology/approach This article used a dynamic panel threshold regression model introduced by Hansen (1996, 1999 and 2000) threshold (TR) models. The procedure is achieved using 5,000 bootstrapping replications and the grid search to obtain the asymptotic distribution and p-values. For… Show more

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Cited by 25 publications
(13 citation statements)
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“…First, it is now apparent that SSA is host to some of the worst systems of energy grid in the world, with the obvious lack of political will and financial resources to address corresponding policy syndromes related to environmental pollution and adoption of cleaner sources of energy (Jarrett, 2017). In fact, there is a bulk of contemporary literature supporting the position that concerns of poor economic performance and environmental degradation and energy crisis in Africa are substantially traceable to issues of governance, inter alia (Nathaniel & Iheonu, 2019;Asongu, Iheonu & Odo, 2019;Joshua & Alola, 2020;Nathaniel & Bekun, 2020;Joshua & Bekun & Sakordie, 2020;Abdulqadir, 2020). However, despite the scholarly and policy concerns surrounding the importance of governance in driving environmental reforms for energy sustainability, SSA has not yet received the scholarly attention it deserves.…”
Section: Introductionmentioning
confidence: 99%
“…First, it is now apparent that SSA is host to some of the worst systems of energy grid in the world, with the obvious lack of political will and financial resources to address corresponding policy syndromes related to environmental pollution and adoption of cleaner sources of energy (Jarrett, 2017). In fact, there is a bulk of contemporary literature supporting the position that concerns of poor economic performance and environmental degradation and energy crisis in Africa are substantially traceable to issues of governance, inter alia (Nathaniel & Iheonu, 2019;Asongu, Iheonu & Odo, 2019;Joshua & Alola, 2020;Nathaniel & Bekun, 2020;Joshua & Bekun & Sakordie, 2020;Abdulqadir, 2020). However, despite the scholarly and policy concerns surrounding the importance of governance in driving environmental reforms for energy sustainability, SSA has not yet received the scholarly attention it deserves.…”
Section: Introductionmentioning
confidence: 99%
“…First, it is now apparent that SSA is host to some of the worst systems of energy grid in the world, with the obvious lack of political will and financial resources to address corresponding policy syndromes related to environmental pollution and adoption of cleaner sources of energy (Jarrett, 2017). In fact, there is a bulk of contemporary literature supporting the position that concerns of poor economic performance and environmental degradation and energy crisis in Africa are substantially traceable to issues of governance, inter alia (Nathaniel & Iheonu, 2019;Asongu, Iheonu & Odo, 2019;Joshua & Alola, 2020;Nathaniel & Bekun, 2020;Joshua & Bekun & Sakordie, 2020;Abdulqadir, 2020). However, despite the scholarly and policy concerns surrounding the importance of governance in driving environmental reforms for energy sustainability, SSA has not yet received the scholarly attention it deserves.…”
Section: Introductionmentioning
confidence: 99%
“…The model is a nonlinear threshold regression approach by Hansen (1999Hansen ( ,2000 but augmented with policy variables closest to a study by Abdulqadir (2020). The model as in Eq.…”
Section: Threshold Regression (Tr)mentioning
confidence: 99%
“…The marginal effect of the coe cient is calculated by taking the partial derivate in Eq. ( 7) with respect to the regressors, thus nding the coe cient (Abdulqadir, 2020(Abdulqadir, , 2022.…”
Section: Quantile Regression (Qr)mentioning
confidence: 99%