The current study examined the impact of different levels of education on environmental quality and renewable energy. Panel data was drawn from the World Bank and OECD databases for 20 OECD countries for the period 1997–2019. Rigorous analytic procedures were employed to better address the methodological issues of existing literature for the analysis of panel data. In this regard, cross-section dependency and heterogeneous structure of the panel data were considered. Accordingly, Gengenbach, Urbain, and Westerlund's panel cointegration test was employed to examine whether there was a long-term relationship between the variables. Fully Modified Ordinary Least Square and Mean Group Dynamic Least Squares were employed to test the robust impact of independent variables on the dependent variable in the long run. Lastly, Dumitrescu & Hurlin's Granger non-causality test was conducted to determine the direction of the relationship between variables. Findings showed that while lower-level education and per capita GDP significantly increased CO2 emissions, higher education significantly decreased it. The CO2 emissions and per capita GDP posed significant negative influences on renewable energy. On the contrary, while both levels of education had positive influences, higher education appeared to be the most influential variable on renewable energy. The causality analyses yielded bidirectional causality relationships between CO2 emissions and renewable energy, low-level education, and higher education; conversely, unidirectional causality relationships between CO2 emissions and per capita GDP. Collectively, the study highlighted the significance of a highly educated workforce for promoting and creating a sustained environment by reducing CO2 emissions and increasing renewable energy utilization.
- And granger non-causality test
- Environmental quality
- Mean group dynamic least squares
- Panel cointegration
- Renewable energy
ASJC Scopus subject areas
- Environmental Science(all)