Tertiary Education and the Path to Lower Emissions: Educational EKC Insights from Asian Panel Data
Mahmudul Hasan
What the paper says
This study examines the educational Environmental Kuznets Curve (EKC) hypothesis, exploring the impact of tertiary education on environmental degradation, particularly the relationship between the gross enrolment ratio in tertiary education and CO 2 emissions per capita within the income–environment relationship framework across 13 Asian countries from 1990 to 2016. Using panel data analysis with fixed effects and random effects models, the findings support the standard EKC hypothesis, confirming an inverted-U-shaped relationship between GDP per capita and CO 2 emissions per capita with a turning point of $69,629.48. The study also finds a concave relationship between tertiary education and CO 2 emissions, with a turning point of 69.50, indicating that tertiary education can ultimately reduce CO 2 emissions, after reaching a certain threshold, by raising environmental awareness at both the individual and national levels and fostering the adoption of environmentally friendly technologies. Furthermore, cluster analysis reveals similar inverted-U-shaped relationships in countries with higher levels of tertiary education. Smaller turning point of both the standard and educational EKC are observed for this group, indicating that this threshold can be reached earlier in countries with higher levels of tertiary education. The study finds that a 1% increase in government spending on education (% of GDP) reduces CO 2 emissions per capita by 0.06%, with no significant link to trade openness. The effect of government expenditure on education is also found to be stronger in the high tertiary education cluster, particularly at 0.202%, highlighting greater policy effectiveness in countries with higher levels of tertiary education.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.