The impact of renewable energy on carbon emissions and economic growth in 15 major renewable energy-consuming countries - Saidi, Kais; Omri, Anis (Environmental research, 2020)
Closing the gap between carbon emissions and economic development is one of the solutions for reaching the sustainable development goals (SDGs). The role of renewable energy in rebalancing environmental and economic conditions is becoming a significant subject of some debates in the current discussion circles. Hence, the main purpose of this article is to use both growth and environmental functions to demonstrate the effectiveness of renewable energy in promoting economic growth and mitigating carbon emissions in the case of 15 major renewable energy-consuming countries using both fully modified ordinary least square (FMOLS) and vector error correction model (VECM) estimation techniques. The results of the FMOLS method show the efficiency of renewable energy in increasing economic growth and reducing carbon emissions. We also find, from the VECM Granger causality test, that there is (i) a bidirectional causality between economic growth and renewable energy inshort- and long-run for both estimated functions, validating the feedback hypothesis; (ii) no causal relationship between CO2 emissions and renewable energy in the long-run, but a bidirectional causality between the two variables is found in the short-run; (iii) a bidirectional relationship between economic growth and CO2 emissions is found in both short and long-run. Policy and practical implications and future research directions are also discussed. •Using the fully modified ordinary least square (FMOLS) and the vector error correction model (VECM) techniques.•A bidirectional causality between economic growth and renewable energy inshort and long-run for both models, validating the feedback hypothesis.•A bidirectional relationship between economic growth and CO2 emissions in both short and long run.•No causal relationship between CO2 emissions and renewable energy in the long run, but a bidirectional causality between the two variables is found in the short run.