This study examines the nexus between energy access, institutional quality, and environmental quality in sub-Saharan Africa (SSA). To get insight into the relationship among the variables of interest, the study unbundles a set of institutional and environmental quality variables using the Bayesian vector auto-regression technique. The findings reveal that among institutions, technology adoption contributes most significantly to renewable energy development in SSA. The study recommends institutional development and strategic technological development to influence sustainable renewable energy utilization in the ongoing renewable energy revolution.
Get full access to this article
View all access options for this article.
References
1.
AkinyemiO., EfobiU., AsonguS., & OsabuohienE. (2019a). Renewable energy, trade performance and the conditional role of finance and institutional capacity in sub-Sahara African countries. Energy Policy 132, 490–498.
2.
AkinyemiO, EfobiU., OsabuohienE., & AlegeP. (2019b). Regional integration and energy sustainability in Africa: Exploring the challenges and prospects for ECOWAS. African Development Review, 31(4), 517–528.
3.
BhattacharyaM., Awaworyi ChurchillS., & Reddy ParamatiS. (2017). The dynamic impact of renewable energy and institutions on economic output and CO2 emissions across regions. Renewable Energy, 111, 157–167.
4.
ColeM. A. (2007). Corruption, income and the environment: An empirical analysis. Ecological Economics, 62, 637–647.
5.
CanovaF., & CiccarelliM. (2013). Panel vector autoregressive models: A survey. (European Central Bank Working Paper 1501). apps.eui.eu/Personal/Canova/working papers/panel_var_final_3.pdf
6.
EjemeyovwiJ. O., OsabuohienE. S., & OsabohienR. (2018a). Investment in technology and human capital development in ECOWAS. International Journal Economics and Business Research, 15(4), 463–474.
7.
EjemeyovwiJ. O., ObindahG., & DoyahT. (2018b). Carbon dioxide emissions and crop production: Finding a sustainable balance. International Journal of Energy Economics and Policy, 8(4), 303–309.
8.
EjemeyovwiJ. O., OsabuohienE. S., JohnsonO. D., & BowaleK. E. (2019a). Internet usage and inclusive growth in West Africa. Journal of Economic Structures, 8(1), 15.
9.
EjemeyovwiJ. O., AdiatQ., & EkongE. (2019b). Energy usage, internet usage and human development in selected Western Afrıcan countrıes. International Journal of Energy Economics and Policy, 9(5), 1–6. doi:https://doi.org/10.32479/ijeep.7611
10.
EjemeyovwiJ. O., & OsabuohienE. S. (2020). Investigating mobile technology adoption and inclusive growth in West Africa. Contemporary Social Science, 15(1), 48–61.
11.
GielenD., BoshellF., SayginD., BazilianM. D., WagnerN., et al. (2019). The role of renewable energy in the global energy transformation. Energy Strategy Reviews, 24, 38–50.
12.
HerrmannR., JumbeC., BruentrupM., & OsabuohienE. (2018). Competition between biofuel feedstock and food production: Empirical evidence from sugarcane outgrower settings in Malawi. Biomass and Bioenergy, 114(July), 100–111.
13.
HichamJ., Marszal-PomianowskaA., EllingsgaardJ. R., & LiuM. (2019). Building energy flexibility: A sensitivity analysis and key performance indicator comparison. Journal of Physics. (Conference Series, vol. 1343). CISBAT 2019, Climate Resilient Cities – Energy Efficiency & Renewables in the Digital Era, 4–6 September 2019, EPFL Lausanne, Switzerland.
14.
HunjraA. I., TayachiT., MuhammadI. C., VerhoevenP., & MehmoodA. (2020). The moderating effect of institutional quality on the financial development and environmental quality nexus. Sustainability, 12,1–13.
IhayereO., AlegeP. O., GershonO., EjemeyovwiJ. O., & DaramolaP. (2021). Information communication technology access and use towards energy consumption in selected Sub-Saharan Africa. International Journal of Energy Economics and Policy, 11(1), 471–477.
17.
KarakaraA., & OsabuohienE. (2020). Clean versus dirty energy: Empirical evidence from fuel adoption and usage by households in Ghana. African Journal of Science, Technology, Innovation and Development. https://doi.org/10.1080/20421338.2020.1816266
18.
LittermanR. B. (1980). Techniques of forecasting using vector autoregressions. (Working Paper 115, 1–135). Federal Reserve Bank of Minneapolis.
19.
OwusuP. A., & SarkodieS. A. (2016). A review of renewable energy sources, sustainability issues and climate change mitigation. Cogent Engineering, 3, 1. DOI: 10.1080/23311916.2016.1167990
20.
ShahS. Z., ChughtaiS., & SimonettiB. (2020). Renewable energy, institutional stability, environment and economic growth nexus of D-8 countries. Energy Strategy Reviews, 29, 100484.
21.
ToddR. M. (1984). Improving economic forecasting with Bayesian vector autoregression. Federal Reserve Bank of Minneapolis Quarterly Review, 18–29.
22.
WangQ., & WangL. (2020). Renewable energy consumption and economic growth in OECD countries: A nonlinear panel data analysis. Energy, 207, 118200. DOI: 10.1016/j.energy.2020.118200
Zambrano-MonserrateM. A., RuanoM. A., & Sanchez-AlcaldeL. (2020). Indirect effect of COVID-19 on the environment. Science of Total Environment, 728, 138813. https://doi.org/10.1016/j.scitotenv.2020.138813
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
