The effects of economic growth on carbon dioxide emissions in selected Sub-Saharan African (SSA) countries

Deciphering the complex interplay: Heterogeneous, threshold, and mediation effects of trade openness on CO2 emissions in Africa

Despite having barely anything to do with the issue of CO2 emissions, Africa has been experiencing more severe climate change and its adverse effects than most other regions of the globe. However, the issue of CO2 emissions and its adverse effects has received relatively little attention in the African research arena. To this end, the present research assesses the effect of trade openness on the CO2 emissions utilizing panel data from 46 African countries spanning 2000 through 2022. To account for the possible heterogeneity and nonlinearity, the panel quantile regression and threshold methods were employed. Moreover, this study investigates the key mediating effects of the channel. The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. Besides the result from the double threshold model reveals a complex, nonlinear relationship between trade openness and CO2 emissions in Africa. Moreover, the findings divulge that openness to trade indirectly reduces CO2 emissions through the substitution and technology channels whereas it indirectly increases carbon dioxide production via the economic track. Therefore, it is vital to promote the use of renewable energy, effectively leverage the knowledge spillover effects of trade to decrease energy intensity and formulate pertinent policies aimed at curbing carbon emissions and addressing the imminent threat of climate change in Africa. Besides, the nonlinear and heterogeneous effects of trade openness on CO2 emissions suggest that policies and interventions related to the impact of trade openness on CO2 emissions should consider the current level of carbon dioxide emissions.

Navigating the impact of remittances on environmental quality in Africa: The crucial role of institutional quality

The Sub-Saharan African (SSA) region remains the world's largest recipient of remittances. Due to growing concerns over climate change issues, recent studies have examined how these financial flows have affected environmental quality. Sundry variables were controlled in such studies concerning the remittances-environment nexus, including institutional quality. Notwithstanding that remittance and institutional quality are imperative, their combined effect on environmental quality has been overlooked. The present study has inspected how remittances and institutional quality have jointly influenced environmental quality in 44 economies in the SSA region between 2000 and 2022. Using PMG-ARDL analysis, the findings revealed that remittances had a negative long-term impact on environmental quality. Conversely, the study found that institutional quality positively affected the per capita ecological footprints, as measured by the six indicators' average. Furthermore, the results indicated that improvements in institutional quality over time mitigated the adverse impact of remittances on the environment in the sampled SSA countries. Additionally, a threshold level of institutional quality effectively moderates remittances' detrimental effects on environmental quality were identified. Therefore, most regional countries must enhance their institutional quality to mitigate the negative environmental impact of remittances.

Achieving zero emission targets: The influence of green bonds on clean energy investment and environmental quality

The effectiveness of green finance in driving clean energy and environmental sustainability in the current era is receiving attention. Therefore, this study proposes an empirical framework highlighting the effects of green bonds (GB) on clean energy investment (CEI), clean energy investment efficiency (CEE) and environmental sustainability of 29 green bond issuing countries between 2014 and 2022. Using system and difference GMM approaches, this study finds that (i) green bond issuance drives clean energy investment. (ii) Green bonds sufficiently enhance the selected countries' environmental quality. These results supplement the promotion of green bonds in increasing the transfer of funds towards renewable energy projects by reducing reliance on fossil fuels. (iii) Using Driscoll & Kraay, Fully Modified-OLS, and changing the dependent variable, this study further supported the idea that green bonds effectively promote the CEE and environmental sustainability of the chosen countries. (iv) Similarly, this study conducted income heterogeneity, showing that green bonds improve high- and middle-income countries' CEI and environmental quality. (v) Finally, the results indicate that resource consumption escalates CO2 emissions by declining the CEI. Technological innovations increase CEI, whereas they do not mitigate CO2 emissions directly, hinting at the requirement for a comprehensive approach. Therefore, inclusive policies on green bond frameworks, robust incentives, and rigorous environmental criteria should be implemented to attract investment in clean energy development and ensure the environmental sustainability of the selected countries.

The impact of urbanization and economic growth on carbon dioxide emission in sub-Saharan African countries: a perspective from the spatial-temporal approach

Sub-Saharan Africa (SSA) is seeing exceptional urbanization and economic expansion rates. Therefore, the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) parameters and the spatial econometric framework are used in this work to examine the influence of economic growth and urbanization on SSA's CO2 emissions. Likewise, to determine the spatial effect and understand how factors influence the spatial dependence of carbon emissions, the study builds a spatial Durbin model (SDM). In line with the findings, the spatial correlation test revealed the spatial correlations across various countries. This indicates that the changes in sub-Saharan African country's CO2 emissions impacted nearby countries and the countries themselves. Additionally, the findings reveal that, in the SSA's countries, urbanization, economic growth, industrial structure, trade, and population, excluding energy intensity, which failed the significant test, all positively influence CO2 outflows, in line with the spatial econometric model's findings. Thus, energy intensity shares an adverse impact on carbon emissions. As an outcome, energy intensity reduces carbon dioxide emissions in nearby nations and the entire region. Thus, the study recommends that policymakers account for the effects of spatial spillover when establishing low-carbon policies, encouraging a low-carbon lifestyle, promoting environmentally friendly technologies, and improving regional collaboration.

Dynamics of urban expansion and form changes impacting carbon emissions in the Guangdong-Hong Kong-Macao Greater Bay Area counties

Cities are the main carriers of social and economic development, and they are also important sources of carbon emissions. Therefore, it is essential to explore the impact of urban expansion and form changes on carbon emissions. Here, we attempted to analyzes the relationship between urban expansion and carbon emissions at the county level in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 1997 to 2017. It further decomposes the driving effects of carbon emissions from multiple factors, and considers the spatial heterogeneity between different urban form changes and driving effects. The results show that: The relationship between urban expansion and carbon emissions in the GBA has gone through three stages from 1997 to 2017, with 2012 as a turning point. Optimization of economic development models and strict protection of the ecological environment can effectively control carbon emissions. After 2012, the economic development effect (GE) and population scale effect (PE) are the driving factors of carbon emissions, while the carbon emission intensity effect (CE) and urban land intensity effect (UE) are the inhibitory factors of carbon emissions. The contribution rate of UE to carbon emission reduction can reach 86 %. The impact of urban form changes on carbon emissions has spatial heterogeneity. The changes in urban form have a significant impact on the carbon emissions of counties in Dongguan and Shenzhen. The increase in fragmentation indirectly promotes carbon emissions. In 2007-2012, the increase in centrality significantly weakened the economic development effect, which is conducive to emission reduction. After 2007, the increase in compactness in counties in the eastern part of the GBA, including Zhongshan and Zhuhai, is not conducive to emission reduction.

The impact of green FDI on environmental quality in less developed countries: A case study of load capacity factor based on PCSE and FGLS techniques

This paper examines the effect of green foreign direct investment (GFDI) on environmental quality (EQ) in 34 less-developed countries (LDCs) from 2003 to 2021. We analyze balanced panel data using Feasible Generalized Least Squares (FGLS) and Panel-Corrected Standard Errors (PCSE). Our findings reveal several vital insights: (1) GFDI helps improve EQ. (2) Environmental costs associated with economic growth are negative. (3) Trade openness positively influences EQ. (4) EQ is enhanced by institutional quality, energy use, and population expansion in the chosen countries. (5) The existence of a U-shaped curve was established. This is valuable to the relatively scanty literature on GFDI, especially in LDCs. To the best of our awareness, this study simultaneously employs the Load Capacity Factor (LCF) and Total Value of Announced Greenfield projects as proxies for environmental sustainability and GFDI for the first time. Secondly, incorporating PCSE and FGLS models in this context is an innovative methodological strategy. The present research work provides to the existing theoretical and empirical discussions on GFDI and EQ and has practical implications that inform policy-making.

Does foreign direct investment influence carbon emission-related environmental problems? Contextual evidence from developing countries across Sub-Saharan Africa

Sub-Saharan African nations face multifaceted environmental problems, especially those associated with carbon discharges. Hence, this study calculates a composite carbon index in the context of 39 developing nations from this region and uses it as a proxy for the carbon emission-related environmental problems they have faced during the 2000-2020 period. This index is estimated by utilizing data regarding annual carbon dioxide discharges, output-based carbon productivity rates, and energy consumption-based carbon intensity levels in the concerned countries. Hence, policy takeaways from this study have critical relevance for the selected sub-Saharan African nations to help them achieve the objectives related to the Sustainable Development Goals agenda and the Paris Accord. Overall, the findings from the econometric analyses verify that more receipt of foreign direct investment initially raises but later on reduces environmental problems. Thus, the nexus concerning these variables depicts an inverse U-shape. Besides, the results endorse that greening the energy consumption structures of the sampled sub-Saharan African countries helps to abate their environmental problems in the long run while financial development aggravates the extent of environmental adversities that take place. Lastly, improving the quality of regulatory agencies enables the Sub-Saharan African nations to further mitigate their environmental problems. Moreover, these aforementioned findings are observed to be heterogeneous across low- and middle-income categories of the selected Sub-Saharan African countries. Furthermore, the heterogeneity of the findings is also confirmed by the outcomes derived from the country-specific analyses. Nevertheless, these nations should attract clean energy-embodying foreign direct investment, make their energy consumption structures greener by amplifying renewable energy adoption rates, introduce green funds to develop their financial sectors, and make their environmental regulatory agencies more transparent with their activities.

An environmental perspective of energy consumption, overpopulation, and human capital barriers in South Asia

Prior literature is substantive in highlighting the nexus between pollutant and socio-economic predictors; however, the role of human interaction has not been sufficiently explored. Thus, the present study examines the validity of the environmental Kuznets Curve (EKC) hypothesis in the presence of energy consumption, overpopulation, and human capital index in five South Asian countries. It employs fixed effects, random effects, and dynamic panel causality techniques with a set of panel data from 1972 to 2021. The baseline results validate the existence of the EKC hypothesis in the recipient panel. Nevertheless, the findings reveal that energy consumption and population density have positive effects, while human capital has negative impacts on CO2 emissions. Furthermore, the study observes that energy consumption and per capita GDP have a significant causal link with CO2 emissions, whereas CO2 emissions are evident to have causality with population density and human capital index. The results are robust and suggest that the consolidation of an effective regulatory framework and technological improvements are substantial measures to improve environmental quality in South Asia. Moreover, allocating sufficient resources to uplift contemporary educational and health status would be imperative to improving environmental quality as aspired to by the Paris Agreement.

What factors cause ocean CO2? A panel data analysis

Over the past three decades, industrial innovations and technological advancements have changed business dynamics, adversely devastating the overall environment. As a result, our oceans have been severely affected due to climate change and global warming. To address this issue, this study investigates the factors that cause ocean CO2 using a sample of 44 countries over 2012-2021 and explores a dynamic and causal relationship between economic growth, ocean carbon dioxide emissions, energy consumption, and control variables relating to the ocean industry. This study finds that increasing economic activity tends to increase ocean carbon emissions. The results support the evidence of the environmental Kuznets curve (EKC) hypothesis suggesting an inverted U-shaped association between ocean emissions and real income for the sample countries. Moreover, this study reports that ocean health index, maritime container transport, trade of fishery and ocean species, aquaculture production and marine species, and employment rate in the fishery processing sector are the significant factors of ocean CO2. Region-wise analyses suggest that real income positively influences ocean emissions and confirm the evidence of the EKC hypothesis in European sample countries but these relationships have an insignificant effect in Asia and the Pacific and the American regions. Furthermore, a short-run unidirectional panel causality flows from the production of aquaculture and other species to RD&D, from OHI and GDP to trade of fishery and other species, and from OHI to employment rate in the fishery sector. Likewise, bidirectional causality runs from energy consumption and maritime transport to ocean CO2 in the long term. Regarding the long-run causal association, the results determine that all of the estimated coefficients of the lagged error correction terms are statistically significant which explains that they are crucial in the adjustment process as they deviate from the long-run equilibrium.

Development and performance comparison of optimized machine learning-based regression models for predicting energy-related carbon dioxide emissions

Accurate prediction of CO2 emissions for the countries has become a crucial task in decision-making processes for planning energy conversion and usage, supporting the design of effective emissions reduction strategies, and helping to achieve the goal of a sustainable and low-carbon future. Therefore, this study aims to develop a general model that can predict the national CO2 emissions of each country using data from 68 countries with high prediction accuracy based on machine learning regression models. Nine prediction models were developed using Support Vector Regression, Ensemble of Trees, and Gaussian Process Regression algorithms as machine learning methods, and their prediction performances were compared. Additionally, the hyperparameters of these three machine-learning methods were tuned by Bayesian optimization to improve their prediction performance. The test results of the optimized Gaussian Process Regression model (MSE = 106.68, RMSE = 10.328, MAE = 4.904, MAPE = 3.38%, R2 = 0.9998) showed that it was the best prediction model among the all developed models. Additionally, the optimized Gaussian Process Regression model gave very robust results in predicting CO2 emissions in many countries, indicating that it can be used reliably and with high accuracy as a promising prediction model.

Does higher energy efficiency growth homogeneously affect carbon emission growth rate across developing Sub-Saharan African nations? The importance of utilizing clean energy

Establishing a sustainable environment and acquiring a carbon-neutral status require Sub-Saharan African nations to reduce their year-on-year growth rates of carbon emission levels. Thus, this study considers a sample of 38 countries from this region and selects the time period from 2000 to 2020 for analyzing the annual carbon emission growth rate influencing impacts of energy efficiency, clean energy, institutional quality, international trade, and net receipts of foreign direct investment. Overall, for the full sample of Sub-Saharan African nations, the results verify that the enhancing the growth rate of energy efficiency improvement reduces both total and per capita annual carbon emission growth rates. Besides, the results endorse that enhancing renewable energy shares of the final energy consumption profiles and promoting good governance-led betterment of institutional quality also plunge emission growth rates in the long run. More importantly, energy efficiency improvement, renewable energy consumption, and better quality institutions are observed to jointly exert carbon emission growth rate-impeding effects, as well. By contrast, more openness to international trade is not seen to influence the carbon emission growth rates of the Sub-Saharan African nations of concern. Lastly, a greater share of net foreign direct investment receipts in the national output level is evidenced to boost annual carbon emission growth rates across this region; consequently, the pollution haven hypothesis is verified. Furthermore, these above-mentioned findings are found to be heterogeneous across groups of low-income and middle-income Sub-Saharan African nations. Accordingly, in line with the findings, a couple of policies are recommended to the governments of the Sub-Saharan African countries in order to guide them in designing effective environmental sustainability policies that are relevant for tackling climate change-related atrocities in the future.

Exploring the dynamic effect of economic growth on carbon dioxide emissions in Africa: evidence from panel PMG estimator

The relationship between economic growth and environmental pollution continues to attract significant research interest for researchers, practitioners, and policymakers all over the globe. Theoretically, the environmental benefit of economic growth should be greater than its negative externality with higher level of development. However, from the African perspective, countries with higher economic performances often face several environmental challenges, which raises the doubt whether economic growth helps or constrains environmental quality improvement. Under the environmental Kuznets curve (EKC) hypothesis, this study re-examined the effect of economic growth on CO2 emissions conditional on the dynamics of urbanization, renewable energy, and good governance across 47 African countries using panel data from 1996 to 2019. We employ panel cointegration tests to establish whether there is a long-run equilibrium relationship among our variables. We also apply pooled mean group ARDL (PMG-ARDL) techniques and the Dumitrescu-Hurlin causality test to determine the long- and short-run effects of economic growth, urbanization, renewable energy consumption, and good governance on CO2 emissions. The results from the PMG estimator validate the EKC hypothesis since a 1% surge in GDP per capita increases emissions by 0.61% in the long run, while a 1% increase in its square decreases emissions by 0.03%. In the short-run, economic growth does not exercise any significant effect on emissions. Furthermore, results indicate a significantly negative and positive long-run effect of renewable energy and governance, respectively. Finally, our causality test shows bidirectional relationship between CO2 emissions and all the explanatory variables. Henceforth, we provided policy implications based on the study's results.

Relationship between financial inclusion and carbon emissions: International evidence

The nexus between financial inclusion and carbon emissions is becoming an increasingly important topic, given the augmented awareness of the negative impacts of climate change and carbon emissions on the environment and human health. In this study, we examine the impact of financial inclusion on carbon emissions using the STIRPAT framework for 102 countries from 2004 to 2020. We measure financial inclusion as a composite index, using principal component analysis (PCA) from five financial inclusion proxies. Our robust panel regression estimations suggest an N-Shaped relationship between financial inclusion and carbon emissions. The N-shaped Environmental Kuznets Curve (EKC) implies that the impact of financial inclusion on carbon emission is nonlinear and changes from an inverted U-shaped to a U-shaped. This finding is strong in developing countries and weak in advanced countries. It is also robust across our two normalized measures of financial inclusion as well as across different estimation techniques. These findings suggest adapting a universal environmental strategy that enhances financial inclusion through strong and accessible financial systems, particularly for low-income countries. Our results further suggest that government authorities and policymakers need to develop well-directed and inclusive financial policies that consider the varying levels of governance, regulations, and income across countries.

An autoregressive distributed lag approach for estimating the nexus between CO2 emissions and economic determinants in Pakistan

Carbon dioxide (CO2) emissions have become a critical aspect of the economic and sustainable development indicators of every country. In Pakistan, where there is a substantial increase in the population, industrialization, and demand for electricity production from different resources, the fear of an increase in CO2 emissions cannot be ignored. This study explores the link that betwixt CO2 emissions with different significant economic indicators in Pakistan from 1960 to 2018 using the autoregressive distributed lag (ARDL) modelling technique. We implemented the covariance proportion, coefficient of determination, the Durbin Watson D statistics, analysis of variance (ANOVA), variance inflating factor (VIF), the Breusch-Pagan test, the Theil's inequality, the root mean quare error (RMSE), the mean absolute percentage error (MAPE), and the mean absolute error (MAE) for the diagnostics, efficiency, and validity of our model. Our results showed a significant association between increased CO2 emissions and increased electricity production from oil, gas, and other sources. An increase in electricity production from coal resources was seen to have resulted in a decrease in CO2 emissions. We observed that an increase in the gross domestic product (GDP) and population growth significantly contributed to the increased CO2 emissions. The increment in CO2 emissions resulting from industrial growth was not significant. The increment in CO2 emissions in the contemporary year is significantly associated with the preceding year's increase. The rate of increase was very alarming, a sign that no serious efforts have been channelled in this regard to reduce this phenomenon. We call for policy dialogue to devise energy-saving and CO2 emission reduction strategies to minimize the impact of climate change on industrialization, population growth, and GDP growth without deterring economic and human growth. Electricity production from different sources with no or minimal CO2 emissions should be adopted. We also recommend rigorous tree planting nationwide to help reduce the concentration of CO2 in the atmosphere as well as environmental pollution.