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Tracking environmental sustainability pathways in Africa: Do natural resource dependence, renewable energy, and technological innovations amplify or reduce the pollution noises?

Jiahao ShenInstitute of African Studies, Nanjing, ChinaRidwan Lanre IbrahimUniversity of Lagos, Akoka, Lagos State, NigeriaKazeem Bello AjideUniversity of Lagos, Akoka, Lagos State, NigeriaMamdouh Abdulaziz Saleh Al‐FaryanConsultant in Economics and Finance, Riyadh, Saudi Arabia
2022en
ABI

Аннотация

The global economy is experiencing the most challenging era of climate change beyond what is evident in the pre-industrial age. Although Africa's share of global greenhouse gas (GHG) is minimal, the ensuing effects hit hard on the continent. Hence, the present study provides the first comprehensive empirical assessment of environmental sustainability in Africa within the novel STIRPAT framework. This study critically examines the impacts of natural resource dependence, renewable energy, urbanization, technological innovations, and structural transition on environmental pollution proxied by carbon emissions, ecological footprint, and PM 2.5 air pollution from 1990 to 2019 in five top carbon-emitting African countries. The empirical evidence is based on advanced panel estimators comprising CS-ARDL, CCEMG, and AMG robust to cross-sectional dependence (CSD). The quantile regression efficient for exploring the conditional distribution effects is equally employed alongside Dumitrescu-Hurlin panel granger causality test. The preliminary tests reveal the presence of CSD and heterogeneity of the series, which led to the conduct of second-generation unit root and cointegration tests. The main empirical results show that renewable energy, technological innovations, and structural transition reduce environmental pollutants from surging based on the observable negative signs. By implication, these indicators support Africa's path to environmental sustainability. On the flip side, resource dependence and urbanization amplify the surge. The feedbacks from quantile regression provide sturdy support for the main estimators. The granger causality feedbacks support the existence of bidirectional and unidirectional causality among the variables. Based on the findings, policies that promote sustainable environment are formulated.

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