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Urbanization and economic growth in sub-Saharan Africa have undergone dramatic changes in recent decades with countries in sub-Saharan Africa seeking to industrialize their economies to boost economic growth. This study, with panel data from 37 sub-Saharan countries between the time period of 1995 and 2017, employs panel cointegration tests and pooled mean group ARDL (PMG-ARDL) techniques and the Dumitrescu-Hurlin causality test to empirically examine the impact of urbanization, economic growth, energy consumption, and industrialization on carbon emissions. Results from the PMG estimator confirm no significant impact of urbanization on carbon emissions in both the long run and short run. One percent surge in energy consumption was found to have significantly caused 1.03% and 0.15% rise in carbon emissions in both long run and short run respectively, thereby reducing the environmental quality. Further findings revealed a significantly negative relationship between economic growth and carbon emissions as well as industrialization and carbon emissions. Additionally, our causality test shows a unidirectional relationship running from energy consumption to carbon emissions. Policymakers are advised to develop rural areas and plan urban centers, pay attention to sustainable energy sources and waste recycling, and educate the populace to improve environmental quality.

Sub-Saharan Africa, though not a 'big emitter,' is disproportionately affected by the enormous impact of climate change. With urbanization and economic growth in sub-Saharan Africa having undergone dramatic changes in recent decades, this study, with panel data from 37 sub-Saharan countries between the time period of 1995 to 2017, employs panel cointegration tests and pooled mean group ARDL (PMG-ARDL) techniques to empirically examine the impact of urbanization, economic growth, energy consumption, and industrialization on carbon emissions. Results confirm that (1) There is no significant impact of urbanization on carbon emissions in both the long-run and short-run. (2) energy consumption was found to have significantly impacted carbon emissions, thereby reducing environmental quality in the long-run and short-run. (3) Further findings revealed a significantly negative relationship between economic growth and carbon emissions as well as industrialization and carbon emissions with 1% growth in GDP per capita and industrialization reducing carbon emissions by 0.11% and 0.06% respectively in the long-run. (4) Additionally, our causality test shows a feedback relationship between urbanization and carbon emissions. Policymakers are advised to develop rural areas and plan urban centres, pay attention to sustainable energy sources and waste recycling, and educate the populace in order to improve environmental quality.

This study investigates the asymmetric cointegration and causal relationships between economic growth, carbon emissions, and energy consumption in the next eleven (11) countries over the period 1972&ndash, 2013. The nonlinear autoregressive distributed lag (NARDL) bounds testing approach and nonpragmatic Granger causality tests are employed. This research&rsquo, s empirical results have entrenched vital relationships that have significant policy implications. We affirm nonlinear cointegration among the variables in Bangladesh, Iran, Turkey, and Vietnam. The long-run asymmetric effect outcomes indicate a definite boom in economic growth, significantly increases carbon emission in Turkey, and a decline in Vietnam. Additionally, a positive shock to energy consumption significantly increases the carbon emission in Bangladesh, Iran, and Turkey, but a decrease in emissions in Vietnam. Findings from the Wald test reveal a long-run asymmetric effect between carbon emission and economic growth in Bangladesh, Iran, and Vietnam, and for Iran, an asymmetric short-run impact. Long-run and short-run asymmetric effects between carbon emission and energy consumption in Bangladesh and Iran. In terms of asymmetric causality results, bidirectional causality between carbon emission and economic growth was noted in Bangladesh and Turkey, and a unidirectional causality from economic growth to carbon emission in Egypt and South Korea. Energy consumption causes carbon emission in Bangladesh, Egypt, Pakistan, South Korea, and not vice versa. We determined a bidirectional asymmetric causality relationship between carbon emission and energy consumption in Vietnam and a unidirectional causality link from carbon emissions to Turkey&rsquo, s energy consumption.

This article examines the asymmetric relationship between electric consumption, economic growth, and carbon dioxide emission in 15 countries over the period 1971–2014. We employed a nonlinear auto-regressive distribution Lag (NARDL) model approach to investigate the asymmetric cointegration between variables. Additionally, we applied the asymmetric causality approach to determine the causal relationship between variables. Results confirm nonlinear cointegration between variables in Cameroon, Congo Republic, Zambia, Canada, and the UK. The Wald test results confirm a long-run asymmetric link between electricity consumption, economic growth, and carbon emission in Canada and Cameroon, while a short-run asymmetric effect in the Congo Republic and the UK. Findings from the granger causality test are volatile across variables. The result provides strong support for the symmetric relationship between electric consumption, economic growth, and carbon emission in the short and long run. This study provides new evidence for policymakers to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth.

This paper investigates the impact of total natural resource rent on economic growth by applying the Nonlinear Autoregressive Distributed Lag (NARDL) developed by Shin et al. (2014) and nonlinear Granger causality proposed by Diks and Panchenko (2006) in the case of top ten mineral-rich countries in the world for the period 1981-2017. Empirically, after testing the stationarity properties of the variables, we applied the Johansen Cointegration approach to examine the cointegration relationship between total natural resource rent, trade openness, and economic growth. The causal relationship between the variables investigated by applying the conventional Granger Causality Test and the nonlinear Granger causality test. We employ the BDS Tests to examine the possibility of nonlinear dependence between the variables. Further, we tested the robustness of the asymmetric short- and long-run nonlinearities through positive and negative partial sum decompositions of the predetermined explanatory variables using NARDL, which exhibits robustness to small sample sizes. The empirical results confirm nonlinear cointegration between the variables in Australia, Brazil, Canada, The Democratic Republic of Congo (DRC), India, and Saudi Arabia. Long-run asymmetric effect results show that total natural resource rent has an adverse effect on economic growth in Australia, DRC, and India, therefore, confirming the "resource curse" phenomenon in these countries. However, we found that natural resource rent has a positive effect on economic growth in Brazil and Canada, which implies that natural resources contribute positively to economic growth and therefore is a blessing in these countries. Our Wald test results reveal a long-run asymmetric effect between total natural resource rent and economic growth in Australia, Canada, the DRC, India, and Saudi Arabia and a short run asymmetric effect in India and Saudi Arabia. The results also indicate a positive shock to trade openness has a positive impact on economic growth in most of the countries. The causality analysis in the nonlinear framework suggests that natural resource rent does not cause economic growth in the majority of the countries assessed. We recommend the implementation of more trade liberalization policies to maximize the benefits from trade openness, especially in the countries where the "natural resource curse phenomenon reported. Important policy implications can be learned from the empirical results.