Modelling energy trilemma and economic growth on renewables in N11 economies: Do economic complexity matter?

Utilizing renewable energy is a necessity for accomplishing global agendas, including combating climate change and promoting sustainable development programs. Although much literature has investigated the nexus between energy sources and their affected regressors during the last few years, no appreciable emphasis is available in the previous studies respecting the influence of the energy trilemma index and economic expansion on the influence of the energy trilemma index and economic the renewables in N11 economies. Therefore, the current study analyzes the crucial influencing factors, including the energy trilemma, economic growth, economic complexity, financial development, and urban population, as drivers of renewable energy in N11 economics from 1990 to 2021 by utilizing a panel quantile regression approach. The empirical outcomes certify that renewable energy is positively connected with the energy trilemma, economic growth, financial development, and urban population, but not with economic complexity, which has the inverse result. As a result, legislators responsible for monitoring the deployment of renewables should stimulate their attempts to consider the energy trilemma dimensions into account when determining energy structural policies, increase the use of greener energy subsidies, pose high-carbon taxes, promote green financial innovation, and improve energy efficiency.

Assessing the role of green economy on sustainable development in developing countries.

Purpose: Over the last few years, the green economy (GE) notion has been realized as a key tool for achieving sustainable development (SD) in both developing and developed nations. Therefore, the current study tries to investigate the role of GE in achieving SD in developing countries. Through empirically examining the relationship between the GE and three different dependent variables which are GDP per capita, total unemployment rate, and poverty level, using cross-sectional data for 60 developing countries in 2018. Design/methodology/approach: Applying generalized least square (GLS) approach. The four dimensions of the Global Green Economy Index (GGEI) are the key independent variables that measure the accomplishment of nations in aspects of the global green economy. Findings: The empirical results showed the existence of a positive statistically significant relationship between the GE and GDP per capita and the level of total unemployment, while there is a negative statistically significant relationship between the GE and the poverty rate in developing countries. Implication policy: This study recommends that both the private and public sectors continue to endorse and adopt GE in the future for SD, job creation, and poverty alleviation.The original value of the study: It is the first research for developing countries that explores the relationship between GE and SD using three indicators of SD using a GLS approach according to our information. Also, this study categorized the dataset of the developing countries based on their income level for addressing the heteroskedasticity problem.

Modelling natural gas, renewables-sourced electricity, and ICT trade on economic growth and environment: evidence from top natural gas producers in Africa.

Addressing extensive global goals including growing energy-sourced electricity and advancing sustainable development plans strongly depends on natural gas as a transition fuel to renewable forms of energy. Therefore, by using pooled, random, and fixed-effects models, the current study investigates the effects of electricity sourced from natural gas (ENG), renewable energy (RE), and trade in information and communication technologies (ICTs) on economic growth and carbon dioxide (CO2) emissions in Africa's top three natural gas producers, Algeria, Egypt, and Nigeria, from 1990 to 2020. The findings indicate that CO2, ENG, ICT trade, and urbanization (UP) are all strongly and positively correlated to economic progress, with the exception of RE, which has an insignificant influence. For the environment, data indicate that RE and GDP degrade the environment while ENG and ICT trade boost it. The causality results that ENG and RE cause both economic growth and CO2 emissions. Based on these empirical results, it is recommended that policymakers should step up their efforts to usage natural gas as a transition fuel to renewable energy sources and acknowledge the advantages of the significant contribution that green ICT trade can make to economic advancement and a clean environment.

Assessing environmental concern and its association with carbon trade balances in N11 Do financial development and urban growth matter?

Expanding of complex global supply chains enhances the role of global trade in the deterioration of the environment by production redeployment across nations, which is tightly connected to emission transmission or the carbon trade balance. Although much earlier studies have assessed the link between emissions of carbon dioxide (CO2) and their influenced variables in the past few years, no substantial attention is available in the literature review concerning the influence of carbon trade balance on the environment in N11 economies. Therefore, via economic progress, renewable/fossil energies consumption, financial development, and urbanization growth as control variables, the influence of the carbon trade balance on emissions of CO2 in N11 countries is explored from 1990 to 2020. The Co-integration and causality relationships using Panel PMG ARDL and Granger causality techniques are investigated to reach our goal. All of the variables investigated degrade the environment in the long run, whereas renewables alleviate CO2. As a result, carbon emission countries' regulators should step up their efforts to support green energy subsidies and carbon taxes, as well as, when supply chains outsource emission-intensive production units to partner nations, they should encourage positive externalities of innovative green technologies.