The interrelationships among financial development, economic growth and environmental sustainability: evidence from Ghana

The complexity of financial development and economic growth nexus in Syria: A nonlinear modelling approach with artificial neural networks and NARDL model

This study investigates the complex interaction between financial development (FD) and economic growth (EG) in Syria from 1980 to 2018 using advanced nonlinear modeling techniques including artificial neural network VAR models, nonlinear causality tests, and nonlinear autoregressive distributed lag (NARDL) models. The results indicate that linear models are inadequate to capture the data patterns, necessitating nonlinear approaches. The artificial neural network VAR model reveals a nonlinear connection between FD and EG. The nonlinear causality test confirms that FD causes EG in a nonlinear manner. The NARDL (1, 1, 0, 1, 1) model is selected based on Akaike information criterion and diagnostics. The findings show a long-run equilibrium and short-run dynamics between FD and EG in Syria. Moreover, positive changes in FD have stronger, more persistent effects on EG compared to negative changes, implying asymmetry. Additionally, the impact of FD on EG is nonlinear, varying with FD levels. These results support recent studies suggesting a nonlinear nexus between FD and EG. They also lend support to the finance-led growth theory while opposing the "too much finance harms growth" hypothesis. The study offers policy implications for Syria to create conditions conducive to positive FD shocks and adopt a long-term perspective regarding FD-EG policies.

Reducing agricultural nitrous oxide emissions in China: the role of food production, forest cover, income, trade openness, and rural population

In the light of China's carbon-neutral goal, this study examines how food production, forest cover, trade openness, and rural population contribute to the quest of addressing China's agricultural nitrous oxide emissions. Time series data ranging from 1971 to 2018 was used for analysis in this study. The autoregressive distributed lag (ARDL) technique was employed to evaluate potential cointegration as well as to ascertain the long and short-run effects of food production, forest cover, income, trade openness, and rural population on agricultural nitrous oxide emission. The Toda-Yamomoto causality analysis was also used to identify the causal relations between covariates (food production, forest cover, income, trade openness, and rural population) and the outcome variable (agricultural nitrous oxide emission). The long-run evidence is that rural population in itself tends to increase agricultural nitrous oxide emissions likewise food production. There is also validation of the existence of environmental Kuznets curve for agricultural nitrous oxide emissions. Moreover, income interacts with rural population to reduce agricultural nitrous oxide emissions in the long-run. Causality analysis indicated rural population affects the level of forest cover; forest cover is found to cause agricultural nitrous oxide emissions but the converse is not established, and income as well as the interaction between income and rural population determines agricultural nitrous oxide emissions. The short-run dynamics results establish an oscillatory equilibrium convergence for agricultural nitrous oxide emissions in event of structural disturbances. From the findings, the EKC hypothesis is relevant by offering avenue to reduce emission. Thus, income growth remains helpful in addressing nitrous oxide emission from the agricultural sector. However, research is needed to unravel why nitrous oxide tends to increase in many forest areas. Since food production cannot be halted, policy makers need to enhance the uptake of efficient food production technologies including developing and using more renewable energy for food production. It is important for authorities to attend to rural development in order to mitigate agricultural nitrous oxide emissions in China.

Climate change mitigation role of renewable energy consumption: Does institutional quality matter in the case of reducing Africa's carbon dioxide emissions?

Renewable energy and institutions have emerged among other variables touted to address climate change problems. However, empirical results have been conflicting. With a relatively poorer state of institutional quality and a lower level of renewable energy development amidst rising carbon dioxide (CO₂) emissions in Africa, the study assesses: a) the direct effect of renewable energy and institutional quality on CO₂ emissions in Africa; and b) the moderation role of institutional quality on the effect of renewable energy on CO₂ emissions in Africa. The study relies on panel data covering 2002-2021 for 32 African countries. The Fully-Modified OLS regression method is employed to analyze the data based on the environmental Kuznets curve (EKC) hypothesis and Stochastic Impacts by Regression on Population, Affluence, & Technology (STIRPAT) model. The results show that urbanization and trade openness increase CO₂ emissions. Although income has a positive effect on carbon emissions, the square term has a negative confirming the EKC hypothesis. Renewable energy also reduces CO₂ emissions. Institutional quality variables of control of corruption, rule of law, regulatory quality, political stability and absence of violence, voice and accountability, government effectiveness and institutional index created from the above indicators reduce CO₂ emissions. In addition, except government effectiveness, the remaining indicators of institutional quality negatively moderate the effect of renewable energy on CO₂ emissions. The results among other things imply that intensifying the development and usage of renewable energy would help address the rising carbon dioxide emissions trend in Africa. Also, strengthening institutions promises to reduce CO₂ emissions.

Realizing the 2050 Paris climate agreement in West Africa: the role of financial inclusion and green investments

International organizations have emphasized the importance of global economies supporting efforts to combat climate change. The Paris Agreement or Agenda 2050 urges nations to ensure that the increase in global temperature is limited to 1.5 °C. Studies have analyzed the factors that contribute to harmful emissions, particularly carbon dioxide emissions, in order to limit temperature rise. However, since there are other equally harmful pollutants, this study evaluates the impact of financial inclusion and green investment on reducing greenhouse gas emissions. The study uses data from West Africa, where environmental pollution has significantly increased. The study employed regression analysis while controlling for economic growth, foreign direct investment (FDI), and energy consumption. The study's key findings reveal that financial inclusion and green investment have a monotonic effect on reducing greenhouse gas emissions. Additionally, the study confirms the environmental Kuznets curve hypothesis and the pollution haven effect for the region. Technological innovation reduces pollution, but green investment and financial inclusion reinforce this effect. Therefore, the study recommends that governments in the sub-region commit to supporting green investment and environmentally friendly technological innovations. It is also crucial to strictly enforce laws regulating the operations of multinational corporations in the region.

The effects of urbanization, ICT, fertilizer usage, and foreign direct investment on carbon dioxide emissions in Ghana

Rising levels of carbon dioxide emissions in emerging countries has become a concern to all and there are calls for urgent action to curtail this. Ghana's government has in recent times sought to achieve higher economic growth at a lower carbon emission rate. With the current development of the country, this study analyzed the effect of urbanization, fertilizer usage, foreign direct investment (FDI), and ICT development on carbon dioxide emissions in Ghana. Time series data for 1971-2018 period was analyzed using autoregressive distributed lag regression approach within the environmental Kuznets curve (EKC) framework. From regression analysis, while the EKC hypothesis was not validated for aggregate carbon emissions, it was found that urbanization has a negative and significant impact on aggregate carbon emissions, whereas FDI and ICT infrastructure have positive impacts on the same in the both long run and short run. Fertilizer usage is seen to interact with urbanization to reduce carbon emissions at the aggregate and sectoral levels. It was found that although ICT helps reduce emissions at some sectoral levels, it was not enough to lower emissions at the aggregate level. Among other things, it is important for Ghana to take a critical assessment of its FDI sources and engagements to ensure that it does not become a sink for high toxic-emitting industries. Intensive education on efficient usage of fertilizer is also needed. It is important for policymakers to critically assess ways and means by which ICT development can be deployed to reduce overall carbon dioxide emissions in the country.

The effect of transport services and ICTs on carbon dioxide emissions in South Africa

The rising trend in carbon dioxide emissions has implications on economic livelihoods through global warming and climate change. Attaining lower carbon dioxide emissions is therefore crucial for the realization of the sustainable development goals. South Africa happens to be one of the leading countries in ICT and transport infrastructure in the sub-Saharan African region. Oppossing arguments on how ICT and tranport services affect carbon dioxide emissions exist. However, their effects on the rising trend in carbon emissions in the country has not received much empirical attention. The study analyses the role ICTs and the transportation sector play in the carbon dioxide emissions of South Africa. Regression analysis of data for the 1989-2018 period shows mobile adoption, internet usage, and telephone usage increases carbon dioxide emissions while transportation services in the country helps reduce carbon dioxide emissions. Income positively affects carbon dioxide emissions while urbanization has negative effects. Implications from the findings include the urgent need to have electricity that power ICT devices and equipment be generated from renewable and sustainable sources rather than from heavy polluting sources.

Are environmental damage and export concentration the major threats for the long-run economic growth in Bangladesh?

Using World Bank and IMF data over the period 1990-2018, this research explores the determinants of economic growth in Bangladesh with particular attention to environmental degradation and export concentration variables. An ARDL (Autoregressive Distributed Lag) bound testing approach is employed as an estimation strategy with FMOLS (Fully Modified Ordinary Least Squares) and CCR (Canonical Cointegrating Regression) for cross-checking the results. The obtained results confirm that CO2 emissions, consumption expenditure, export concentration, remittances, and inflation are the main driving forces for the long-run economic growth in Bangladesh where the effects of the first two variables and the last three variables are positive and negative, respectively. The study also reveals the dynamic short-run relationships among the chosen variables. Environmental pollution and export concentration are found to be the barriers to economic growth; therefore, the country should take necessary steps to mitigate this problem for ensuring long-run sustainable economic development.

The effect of industrialization, militarization, and government expenditure on carbon dioxide emissions in Ghana

The need to attain lower carbon dioxide emissions has become a topical issue in recent times. The effect of a number of economic variables on carbon dioxide emissions has been empirically assessed. Rising government expenditure, industrialization, and militarization have characterized many developing countries including Ghana. While it is undeniable that such situation has socio-economic importance to offer developing countries, their environmental effects have become a matter of debate among researchers. This study assesses the carbon dioxide emissions effect of industrialization, government expenditure, and militarization in Ghana. Based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework, the study models Ghana's carbon emission as a function of income, population, industrialization, government expenditure, and military expenditure. Time series data over the 1971-2018 period was used for investigation. The techniques employed to analyze the data were unit root test, cointegration test, and regression analysis. The autoregressive distributed lag (ARDL) regression approach reveals there is an inverted U-shaped relationship between income and carbon emission confirming the environmental Kuznets curve hypothesis. Also in the long run, carbon emissions are positively influenced by population, industrialization, and militarization but reduced by government expenditure. Similar outcome was obtained in the short run. The paper concludes that the level of income, industrialization, militarization, and population matters to deal with carbon dioxide emissions in Ghana. Policy implications of the findings include the urgent need for authorities to promote the use of eco-friendly production methods for military and industrial activities to sustain the economic growth without harming the environment.