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Are “economic bads” of infectious diseases and “economic goods” of foreign direct investment antagonistic to each other? This is the salient question that this research inquiry unravels for 34 African economies from 2000 to 2017. The empirical evidence revealed the following through a generalized method of moments (SGMM) inter alia: First, the mitigating roles of infectious diseases, such as malaria, HIV prevalence rate and AIDS, on global FDI inflows are unconditionally certified from a statistical and economic sense. Second, the diminishing influences of other confounders, such as low per capita GDP, shallow financial development, excruciating inflationary trend, and natural resource rents curse, are empirically endorsed, on the one hand, while the persistent nature of FDI and trade openness as boosting mechanisms for FDI are unambiguously applauded, on the other hand. Finally, a reduction in the numerical strength of the estimates after accounting for the outliers’ effect from the models and the inclusion of additional controls do not diminish the robustness of already established findings, except for the HIV prevalence rate. On the policy front, if the foreign direct investment is truly pro-development outcomes, any policy interventions that eliminate infectious diseases will be Pareto-improving.

Global warming remains the most devastating environmental issue embattling the global economies, with significant contributions emanating from CO2 emissions. The continued rise in the level of greenhouse gas (GHG) emissions serves as a compelling force which constitutes the core discuss at the recent COP26 prompting nations to commit to the net zero emissions target. The current research advances the first empirical investigation on the roles of structural change, demographic mobility, and energy transition in G7 pathways to environmental sustainability captured by CO2 emissions per capita (PCCO2) in G7 economies from the empirical perspective. The study considers the additional impacts of resource abundance and technology. The empirical backings are subjected to pre-estimation tests consist of cross-sectional dependence, second-generation stationarity, and panel cointegration tests. The model estimation is based on Cross-Sectional Augmented Autoregressive Distributed Lag, Dynamic Common Correlated Effects Mean Group, and Augmented Mean Group for the main analysis and robustness checks. The findings reveal the existence of EKC based on the direct and indirect effects of the components of economic growth. The indicators of demographic mobility differ in the direction of influence on PCCO2. For instance, while rural population growth negatively influences PCCO2 in the short-run alone, urban population growth increases PCCO2 in the short-run and long-run periods. Nonrenewable energy, information computer technology (ICT) imports, and mobile cellular subscriptions serve as positive predictors of PCCO2, while ICT exports and renewable energy moderate the surge in PCCO2. Policy implications that enhance environmental sustainability are suggested following the empirical verifications.

This study probes the environmental consequences of income inequality (INQ) in G7 economies from 1971 to 2015. INQ is captured by four indicators comprising GINI coefficients, Palma ratio, Theil index, and Atkinson index on per capita carbon emission as a proxy for environmental degradation using both fully modified OLS (FM-OLS) and dynamic OLS (D-OLS). The empirical data are subjected to pre-test using cross-sectional dependence (CSD) test and panel unit root and panel cointegration tests. The following results are established. First, the absence of CSD and presence of cointegration is confirmed. Second, positive effects of INQ indices are reported for the panel analyses. Third, the results of country-specific analyses are divergent and mixed among the G7 economies. For instance, positive impacts are reported for Canada, Japan, and the USA and negative for France and Germany; and insignificant impacts are evident in the case of Italy and the UK. Fourth, the effects of other covariates emerge from two directions entailing both positive and negative. While per capita GDP (LGDPPC) and trade openness (OPN) are aligned with the former a prior, per energy use (PEU) and inflation (INF) satisfied the latter. Consequently, embarking on pro-poor programs such as social welfare funds, private initiative support fund, and state intervention aimed at checkmating the excesses of the capitalists is seen as sacrosanct to solving the INQ-pco2 nexus disharmony.

This article investigates whether trade facilitation acts as a stimulus or deterrent for foreign direct investment (FDI) inflow to Africa by employing six key components relating to cross-border tr...

This study examines the disaggregated impacts of non-renewable energy (NRE) indicators comprising coal, gas, and fuel, and trade openness (TO) entailing imports and exports on environmental quality proxied by (carbon emission per capita, co2pc) in selected G-20 countries with the conditioning role of technological innovation (ecoi) from 1990 to 2018. The empirical analyses are evaluated using a battery of estimation techniques comprising augmented mean group (AMG), common correlated effect mean group (CCEMG), and mean group (MG), respectively. The following major results are evident from the analyses. First, coal, gas, fuel, and imports increase co2pc while exports reduce it. Second, the unconditional and conditional effects of technological innovation (ECOI) significantly reduce co2pc. These results are consistent with the robustness checks based on CCEMG and MG estimators. On the policy front, promoting technological innovation remains a veritable option to curtailing the devastating impacts of co2pc.

The growing trend of economic integration and globalization has made the need to harmonize cross-border trade and their associated procedures among trading countries, inevitable. Nonetheless, there is an emerging debate about the environmental consequences of engaging in trade interactions among the policymakers, trade pundits and researchers alike. To this end, this study examines whether Africa’s inefficient trade facilitation procedures hold plausible explanations for her coincidental low incidence of carbon emissions. The empirical evidence is based on both Pooled Ordinary Least Squares (POLS) and Two-Step System Generalized Method of Moments (Sys-GMM) on six components of trade facilitation (costs, documents and time required to import and export) vis-a-vis the environmental measures including carbon emissions (CO2), and nitrous oxides (N2O) on a panel of 48 African countries over the period spanning, 2005–2014. While the choice of the former estimator is chiefly influenced by the need to have a baseline model on the one hand, the choice of the latter is motivated by the need to account for econometric concerns including endogeneity, reverse causality and simultaneity bias, respectively, on the other hand. The main finding from the study reveals a significant negative relationship between trade facilitation and environmental pollution captured. On the policy perspective, determining the threshold levels of trade procedural measures is necessary for achieving effective regulation of inflow of carbon–embodied goods and services into an already environmentally lax continent.

The present study empirically investigates the tripartite impacts of renewable energy (RE), nonrenewable energy (NRE), and trade openness (TO) with the conditioning role of technology on environmental quality (CO2 emission) for the G-7 countries (Canada, France, Germany, Japan, Italy, USA, and United Kingdom) for the period straddling 1990–2019. The empirical analyses are anchored on a set of estimation procedures including; cross-sectional dependence test, second generation panel unit root test, Westerlund cointegration test, Hausman test, and pooled mean group (PMG). The following results emanate from the findings. First, the presence of cross-sectional dependence and long-run relationships are confirmed for the countries. Second, RE significantly lessens the prevalence of carbon emissions across the estimated models. This further underscores the mitigating effects of RE on CO2 emissions for the G-7 countries. Third, the impacts of NRE and TO are found to contribute to surge in CO2 emissions. Fourth, the effects of technological progress captured by research and development (RD) and eco-innovation significantly reduce the stock of CO2 emissions using both unconditional (single effect) and conditional (interactive effect) methods. Fifth, the existence of Environmental Kuznets Curve (EKC) receives empirical support for the G-7 countries. Other covariates such as foreign direct investment (FDI), Gross Fixed Capital Formation (GCFC), and service value-added (SVA) exert diverging impacts on CO2 emissions. Sixth, the country-level analyses show the heterogeneous nature of the G-7 countries as evident from each country’s findings.

This study examines the impacts of non-renewable energy (NRE) on quality of life (QOL) through the conditioning role of technology on a panel of 43 Sub-Saharan African (SSA) countries over the period spanning 1990–2019. For easy traceability of the channel through which NRE affects QOL, the aggregate measure of Human Development Index (HDI) was decomposed into three namely life expectancy, education, and per capita GDP (GDPPC). Four indicators such as coal, natural gas, petroleum oil (disaggregated), and fossil fuel (aggregated) capture NRE while ICT service exports are used to proxy technology. The empirical analyses are deployed on a two-step system generalized method of moments (SYS-GMM) with forward orthogonal and the Panel Fixed Effects. Similarly, the empirical analyses also consider four regions (viz: South, West, East, and Central) in SSA. The following findings are established. First, the indicators of non-renewable energy (NRE) are statistically significant and negatively signed when HDI, life expectancy, and GDPPC are the outcome variables but positive for education. Second, the role of technology is examined from two angles: unconditional (single) and conditional (interaction with NRE variables). Across all models, technology proves to be QOL enhancing. Third, while the test of nonlinearity in the NRE-QOL nexus is confirmed, the findings are also consistent with the sub-regional analyses.

The growing concerns on the need to moderate the unceasing surge in global greenhouse gas (GHG) emissions believed to be detrimental to the environment and wellbeing of the human race have generated concerted efforts from governments and policymakers worldwide. Among many other factors, fossil fuels which remain the most consumed energy resource have been identified as the primary culprit to demeaning life expectancy. To this end, this study probes how income mediates between fossil fuels and carbon emissions to promote life expectancy in selected oil-abundant African economies from 1980 to 2019. The roles of human capital through investment in education are considered in the current inquiry. The empirical evidence is anchored on second-generation tests comprising cross-sectional dependence, slope homogeneity, and Westerlund cointegration tests. The empirical model is estimated based on advanced panel techniques comprising cross-sectional dependence autoregressive distributed lag model, common correlated effects mean group, augmented mean group, and quantile regression. Findings from the study reveal that fossil fuels and carbon emissions reduce life expectancy. Besides, income level promotes healthy life expectancy while equally subduing the negative impacts of fossil fuels on it. Additionally, the life-improving roles of human capital are empirically confirmed. Based on the findings, withdrawing the subsidies on fossil fuels and making aggregate income inclusive are among the key policies formulated.

This study examines the impact of trade facilitation and institutions on sustainable environment on a panel of 41 Sub-Saharan African countries over the period 2005–2014. Six composite indicators o...

Although available statistics reveal Africa as an insignificant contributor to the devastating global climate condition, the succeeding impacts seem to hit the region harder than others. Efforts to address the environmental issues have seen the transition from carbon-intensive to carbon-abating sectors. Hence, this study makes the first empirical attempt to probe the ecological effects of structural transition and demographic mobility amidst the presence of technological innovation, foreign direct investment, and renewable energy. The empirical evidence focuses on the five highest emitters in Africa from 1990 to 2019 using advanced estimators, including cross-sectional autoregressive distributed lag (CS-ARDL), augmented mean group (AMG), common correlated effect mean group (CCEMG), and method of moment quantile regression (MMQR). For easy tracking of emanating effects, structural transition is captured by agriculture, manufacturing, and service sectors’ value added, whereas demographic mobility vectors rural and urban population. The results reveal agriculture sector, manufacturing sector, rural population, and urban population as amplifiers of CO2 emissions. Conversely, the moderating roles of technological innovation amidst service sector, foreign direct investment, and renewable energy are confirmed. Besides, Granger causality uncovers unidirectional and bidirectional causality in the model. Promoting developments in research and development and adopting carbon tax policies are among the emanating policies on the findings.

This study examines the impactful role played by trade facilitation (TF) in promoting or hindering food security in a panel of 34 sub-Saharan countries for the period 2005–2019. The empirical evidence is based on the Two-Step Dynamic System Generalized Method of Moments estimator, employed to account for econometric concerns bothering on unobserved heterogeneity and potential endogeneity inherent in the variables used. The empirical findings show that the nature of TF procedures, which are inefficient, negatively impact food security in SSA. These effects are evident on the availability and accessibility dimensions of food security as well as their composite index. While it is noted that this result runs counter to the established a priori of positive signs on the one hand, it however portrays the reality of the economic phenomenon in SSA on the other/hand. In balance, the present TF regime can best be described as anti-food security as suggested by the prevailing burdensome procedures involved in exporting and importing staple food items. The functional roles of population growth and institutional quality are empirically enhanced divergently. Going forward, we recommend that for food sufficiency and Sustainable Development Goals to be achieved quickly, governments within the region would need to finetune the underlying modalities of the present TF regime

The global environment faces the issue of sustainability arising from the persistent growth rates in general production levels. Hence, there is the need to resolve the growth environment conflicts in order to enhance the sustainability of the current and future generations. This study presents the first empirical analysis on the dynamic impacts of non-renewable and renewable energy, total resource rents, population growth, human capital, and financial inclusion on environmental quality in Sub-Saharan Africa (SSA) with the conditioning roles of technological progress and income level. The empirical evidence is based on a two-step system generalized method of moments (SYS-GMM) with forward orthogonal deviations for 42 countries in the SSA region from 2004 to 2018. The following results are established from the empirical analyses. First, renewable energy emerges as a promoter of environmental quality through its reducing impacts on carbon emissions per capita (co2pc). Second, other regressors turn out to impede environmental quality by contributing to the surge in co2pc. Third, the robustness checks analyses, which consider different variants of carbon emissions as outcome variables, revealing that the main results are robust and empirically supported to explain the variations in the level of pollutants in the region. Fourth, the impacts of technological progress from both direct (unconditional) and interactive (conditional) angles mitigate co2pc while income promotes it. On the policy front, promoting investment in renewable energy and structuring human capital development plans to promote green growth are seen as sacrosanct towards achieving a sustainable environment in the region.

The present millennium records the most devastating effects of global warming than what was evident in the pre-industrial era. The pervasive effects of global warming have raised concerns about the sustainability of the present and future generations. Hence, researchers are working assiduously towards proffering the most effective method of halting the surging emissions from global, regional, and national angles. This study contributes to the extant literature by providing the first empirical verification of how renewable energy, technological innovations, trade openness, and transport services impact carbon emissions in Germany. The empirical evidence is anchored on annual time series data from 1990 to 2020 estimated using the novel nonlinear ARDL to explore the positive and negative shocks associated with the short and long-run nexus. The wavelet coherence estimator is equally for ascertaining the multiple time scales in the time series and extends the knowledge frontier to the literature. The following findings are eminent from the overall analyses. First, long-run cointegration is supported among the variables of interest Second, only the adverse effects of renewable energy and technology are substantial enough to mitigate carbon emissions. The trade-induced emissions are established with the positive impacts of trade openness on carbon emissions. Transport services contribute significantly to carbon emissions in the long-run and short-run periods. However, mitigating effects of small magnitude are apparent in the long-run due to the perceived transition to green transportation. Policy implications supporting the transition to 100% renewable energy and green transportation are significant steps towards achieving Germany's carbon neutrality target.

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 PM2.5 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.

Nuclear energy has sparked international attention as one of the most important strategies for reducing emissions thanks to its ability to provide low-carbon power. Based on this interesting fact, the current research explores the effect of nuclear energy on CO2 emissions in the leading countries by nuclear power consumption using a quarterly dataset from 1990 to 2019. The study employs the quantile-on-quantile (QQ) estimator, which accounts for both non-parametric and conventional analyses and enhances the provision of unbiased and consistent estimates. In addition, the Granger causality in quantiles approach is adopted to assess the causality in quantiles between the variables of investigation. The outcomes from the QQ estimator reveals that in the majority of the quantiles, nuclear energy contributes to decreased degradation of the environment in the USA, France, Russia, South Korea, Canada, Ukraine, Germany, and Sweden. Contrawise, the feedbacks from Spain and China expose that Nuclear Energy Consumption (NUC) contributes to the deterioration of the environment. Moreover, the outcomes of the causality test disclose that nuclear energy and CO2 emissions can predict each other in the majority of the quantiles. The findings above provide profound ramifications for policymakers planning nuclear energy and CO2-emission policies towards achieving sustainable environment in the sample countries and beyond..

Investment in capitals is sacrosanct to launch a country to a greater path of sustainable development. Notwithstanding, its deleterious impacts on environment are equally incontestable. In light of this stark reality, this paper examines the threshold effects of capital investments on carbon emissions in G20 economies over the period, 1992–2014, for which data are available. The study uses both exogenously determined and endogenously determined thresholds to uncover the relationship. While the former relies on median approach to determining the threshold on the one hand, the latter uses both the fixed effects panel threshold model proposed by (Hansen J Econ 93:345–368, 1999) and the bootstrap method by (Hansen Econometrica 68:575–603, 2000) to assess the statistical relevance of the threshold effects on the other hand. The results of the exogenously determined thresholds show higher statistical significant environmental impacts of capital investments at a median threshold of above 3.068 than when it is lesser. The findings of the latter approach indicate the relationship between capital investments and carbon emissions to be non-linear for the G20 countries. More specifically, this study establishes a single-threshold level of capital investment on carbon emissions for the group of countries. The threshold estimator of 3.434 is established at the 95% confidence interval. Beyond this point, the environmental impacts of capital investments are imaginable. On the policy front, keeping to the limit set by threshold effects would go a long way to stemming environmental pollution and mitigating climatic change impacts.

The recent decades have witnessed an unprecedented surge in global warming occasioned by human anthropogenic activities. The ensuing effects have brought devastating threats to human existence and the ecosystem, with the sustainability of the future generations highly uncertain. Resolving this pervasive issue requires evidence-based policy implications. To this end, this study contributes to the ongoing sustainable development advocacy by investigating the impacts of renewable energy and transport services on economic growth in Germany. The additional roles of digital technology, FDI, and carbon emissions are equally evaluated using data periods covering 1990 to 2020 within the autoregressive distributed lag (ARDL) framework. The results show the existence of cointegration among the variables. Additionally, renewable energy and transport services positively drive economic growth. Furthermore, economic growth is equally stimulated by other explanatory variables, such as digital technology and carbon emissions. These outcomes are robust for both the long-run and short-run periods. More so, departures in the long run are noted to heed to corrections at an average of 60% speed of adjustment. The estimated models are confirmed to be valid based on the outcomes of the postestimation tests. Policy implications that support the path to sustainability are highlighted based on the findings.

This study investigates the dynamic impacts of disaggregated nonrenewable energy, trade openness, total natural resource rents, financial development and regulatory quality on environment quality of the BRICS economies from 1996 to 2018. To track the channel through which nonrenewable energy impacts the environment, the study explores the data on both production and consumption for coal, gas and fuel while import and export of goods and services are separately used to proxy trade openness. The empirical analyses are based on preliminary tests, comprising of descriptive statistics, normality tests, cross-sectional dependence test and slope heterogeneity test. Panel unit root tests based on first and second generations are equally employed before conducting panel cointegration test. Estimation of empirical models is based on second-generation techniques comprising Augmented Mean Group (AMG) and Common Correlated Effect Mean Group (CCEMG). The following findings are evident. First, coal and fuel from both angles of production and consumption and gas production are found to be carbon emission per capita (co2pc) inducing while gas consumption turns out to be co2pc-abating. Second, the trade led environmental impacts are not supported. Third, total natural resource rents, financial development and regulatory quality are found to positively contribute to surge in co2pc. Fourth, the results of causality test based on Dumitrescu and Hurlin reveal the case of bi-directional and uni-directional among the variables. The emanating policy implications suggest gas promotion and discouragement of coal and fuel adoption as strategies to improving environmental quality in BRICS.

This study investigates the effects of non-renewable energy (NRE) on quality of life (QOL) in 43 Sub-Saharan African (SSA) economies for the period straddling 1990–2017. Four indicators of NRE comprising coal, natural gas, and petroleum oil (disaggregated) and fossil fuel (aggregated) are examined on three indicators of QOL (life expectancy, mortality rate, and human development index) by employing two-step system generalized method of moment (SYS-GMM) with forward orthogonal, fixed effects OLS, and fully modified OLS. The findings reveal significant negative impacts of NRE indicators on life expectancy and HDI but positive effects on mortality rate (infant). Besides, these results are consistent with the robustness checks. Based on the findings, implementing policies that will help discontinue the surge in non-renewable energy consumption, and raise the income level of the populace are sacrosanct to improving QOL in the region.

The study examines the extent to which lockdown measures impact on COVID-19 confirmed cases in Nigeria. Six indicators of lockdown entailing retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residential, are considered. The empirical evidence is anchored on the negative binomial regression estimator, due to the count nature of the dataset on the daily cases of the virus. The study established the key following findings: First, retail and recreation, grocery and pharmacy, parks, transit stations, and workplaces are statistically significant and negatively signed as relevant predictors of the virus. Second, the impact of residential is positive and statistically significant at the conventional level. Lastly, the results are robust to an alternative estimator of Poisson Regression. The emanated policy message centres on the need to direct efforts toward ensuring total compliance to the lockdown rules as it holds the key to keeping the virus under check., Highlights • This study examines the extent to which lockdown measure impacts on COVID-19 confirmed cases in Nigeria. • Lockdown variables such as, retail and recreation, grocery & pharmacy, parks, transit stations, and workplaces are significant and negative. • The impact of residential is positive and significant. • The results for the both estimators correspond thus highlighting the efficacy of the estimates.