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The study investigated two aspects, namely, (1) the impact of renewable energy consumption on economic growth in Brazil, Russia, India, China, South Africa (BRICS) and (2) whether education is a channel through which renewable energy consumption affects economic growth in BRICS. Panel data analysis such as fully modified ordinary least squares, pooled ordinary least squares and fixed effects methods were used with data ranging from 1994 to 2015. Both models across all the three estimation techniques show that renewable energy consumption had a significant negative effect on economic growth in support of the findings by Silva et al. (2012) and Lee and Jung (2018). What is also clear across all the three panel data analysis methods used is that education reduced the size of the negative effect of renewable energy consumption on economic growth in BRICS. In other words, education is a channel through which renewable energy consumption's influence on economic growth is enhanced, in support of views by Dunn and Mutti (2004), Ozcicek andAgpak (2017) and Lawrence et al. (1991). The implication of the study is that BRICS countries are therefore urged to invest more in education as that is more likely to enhance the impact of renewable energy consumption on economic growth.

The study explored the impact of remittances on poverty in selected emerging markets. On the theoretical front, the optimistic view argued that remittances inflow into the labour exporting country reduces poverty whereas the pessimistic view proponents said that remittances dependence syndrome retards both economic growth and income per capita. Separately, using two measures of poverty [the poverty headcount ratio at US $1.90 and US $3.10 a day (% of population)] as dependent variables, the fixed effects approach produced results which supported the remittances led poverty reduction (optimistic) hypothesis whereas the pooled ordinary least squares (OLS) framework found that remittances inflow into the selected emerging markets led to an increase in poverty levels. The implication of the findings is that emerging markets should put in place policies that attract migrant remittances in order to reduce poverty levels. They should avoid over‑reliance on remittances as that might retard economic growth and income per capita.

This study explored the influence of information and communication technology (ICT) on carbon emissions in emerging markets using panel data analysis methods (fixed effects, random effects, pooled OLS, FMOLS) with annual secondary data spanning from 1994 to 2014. Additionally, the study investigated whether financial development and economic growth are channels through ICT has an influence on carbon emissions. Without interaction terms, ICT was found to have had a significant positive influence on carbon emissions across all the four panel data analysis methods. After introducing interaction terms, financial development was found to be a channel through which ICT increased carbon emissions under the fixed effects, random effects and the FMOLS. Under the pooled OLS, financial development was found to be a channel through ICT enabled the reduction in carbon emissions. Economic growth was found to be a channel through ICT lowered down carbon emissions in emerging markets across all the four panel data analysis methods.

This study investigated the impact of infrastructure and human capital development on economic growth in transitional economies. It also explored whether the interaction between infrastructural and human capital development enhanced economic growth in the transitional economies. Although the literature is awash with studies which investigated the separate impact of infrastructure and human capital development on economic growth, no study that the author is aware of has so far explored whether the interaction between infrastructure and human capital development enhances economic growth. The study mainly used a dynamic panel generalised methods of moments (GMM) approach by Arellano and Bond (1995), a framework that takes into account the dynamic nature of economic growth data and addresses the endogeneity issues normally associated with economic growth regression functions. Panel data analysis approaches such as pooled ordinary least squares (OLS), and fixed and random effects were used for comparison purposes and robustness tests. According to the dynamic GMM framework, the interaction between infrastructure and human capital development improved economic growth in transitional economies, in line with theoretical and empirical predictions. Random effects and pooled OLS show that the interaction between infrastructural and human capital development had a deleterious effect on economic growth, whilst according to the fixed effects approach, the interaction between these two variables had an insignificant positive influence on economic growth in transitional economies. Considering that the results from a dy34 Kunofiwa Tsaurai, Adam Ndou namic panel GMM are considered to be more accurate due to the approach’s ability to address the endogeneity problem and the dynamic nature of economic growth data, the current study recommends that transitional economies should implement policies that improve human capital development in order to enhance infrastructural development’s ability to influence economic growth. Future studies should investigate not just one (human capital development), but all the conditional factors which must be in place before economic growth advantages triggered by infrastructure development are realised.

The study's main objective was to investigate the macroeconomic determinants of carbon emissions in transitional economies using panel methods with data ranging from 1996 to 2014. The main data analysis was done using econometric estimation methods such as fixed effects, random effects, pooled ordinary least squares (OLS) and the dynamic generalized methods of moments (GMM) approach whilst robustness tests were done under the umbrella term, the lagged independent variable approach. To a larger extent, infrastructural development, economic growth, trade openness, financial development and natural resources were found to have had a significant positive effect on carbon emissions, in line with major theoretical predictions. On the other hand, renewable energy consumption, foreign direct investment, information and communication technology and human capital development were mainly found to have reduced carbon emissions in transitional economies. The results are firmly supported by literature. Transitional economies are therefore urged to increase their use of renewable energy and information and communication technology (ICT) infrastructure, attract more foreign direct investment (FDI) and implement policies aimed at enhancing human capital development to reduce carbon emissions. Given data availability, future studies must investigate whether other macroeconomic variables mentioned in the empirical literature that they determine carbon emissions are relevant in transitional economies.

This study investigated the impact of energy consumption on poverty in BRICS using panel data analysis methods (fixed effects, pooled OLS, random effects, FMOLS) with annual data ranging from 1995 to 2018. Whether economic growth is a channel through which energy consumption influences poverty in BRICS was also a subject of investigation in this study? Although there is acknowledgment that energy consumption reduces poverty through economic growth by authors such as Okwanya et al ( 2015), Hussein and Filho (2012) and Okwanya and Abah (2018), there is no dedicated empirical study on the subject matter which exclusively focused on BRICS. Nothing is known about the energy consumption-growth-poverty nexus in BRICS, according to the author's best knowledge. Also, majority of the energy consumption-poverty nexus empirical research wrongly assumed that the two variables (energy consumption and poverty) are linearly linked. Using both mean mortality rate and mean life expectancy as measures of poverty, the study noted that energy consumption reduced poverty in a significant way across all the four panel methods employed in BRICS. Economic growth was also generally found to have reduced poverty in BRICS countries. The complementarity between the two variables (energy consumption and economic growth) had a significant poverty reduction effect in BRICS, in support of the existing literature. BRICS nations are therefore urged to develop and implement policies that ensure more energy consumption and increased economic growth activities if they intend to reduce poverty.

The study explored whether the complementarity between foreign direct investment(FDI) and natural resources availability led to poverty reduction in Southern and WesternAfrican nations using panel data analysis (fixed effects, random effects, pooled ordinaryleast squares (OLS) and dynamic generalised methods of moments (GMM) with dataspanning from 2002 to 2012. The objective emanates from the theoretical view that if thecountries that are receiving FDI have abundance of natural resources, a large number ofthe unemployed people are likely to get jobs, earn income and get out of poverty zone.Three measures of poverty were used in the current study, namely life expectancy atbirth, total (years), household consumption expenditure as a ratio of gross nationalproduct and mortality rate and infant (per 1 000 live births). Generally, all the four paneldata analysis methods produced similar finding: the interaction between FDI and naturalresources reduced poverty levels in African countries studied. Southern and WesternAfrican nations are therefore urged to implement FDI enhancement policies which attractforeign investors into the natural resources extraction sector if they want to sustainablyreduce poverty. Future studies should investigate other macroeconomic factors that mustbe available in the host country before FDI reduce poverty in all its forms.