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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?

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          Abstract

          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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          Most cited references53

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          A simple panel unit root test in the presence of cross-section dependence

          M. Pesaran (2007)
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            Testing for unit roots in heterogeneous panels

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              Testing for Granger non-causality in heterogeneous panels

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                Author and article information

                Contributors
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                Journal
                Energy & Environment
                Energy & Environment
                SAGE Publications
                0958-305X
                2048-4070
                September 15 2022
                : 0958305X2211242
                Affiliations
                [1 ]School of Foreign Studies, Nanjing University, Nanjing, China
                [2 ]Institute of African Studies, Nanjing, China
                [3 ]University of Lagos, Akoka, Lagos State, Nigeria
                [4 ]Department of Accounting and Financial Management, Faculty of Business and Law, University of Portsmouth, Portsmouth, The UK
                [5 ]Consultant in Economics and Finance, Riyadh, Saudi Arabia
                Article
                10.1177/0958305X221124221
                036b67cb-fe2b-449b-a1d8-27023af8e98f
                © 2022

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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