Returns to Higher Education and Dropouts: A Double Machine Learning Approach

ZEW Discussion Paper Nr. 20-084 // 2020
ZEW Discussion Paper Nr. 20-084 // 2020

Returns to Higher Education and Dropouts: A Double Machine Learning Approach

This paper provides estimates of the short-term individual returns to Higher Education (HE) in the United Kingdom, focusing on the effects of attending HE on the labour market outcomes for dropouts. Results show differential labour market outcomes for dropouts vs. individuals who have never attended HE, where outcomes are employment, wages and occupational status. I find that female dropouts, on average, have a higher occupational status than those who have never participated in HE, but do not experience a wage premium. Conversely, male dropouts experience a wage premium relative those who have never participated in HE, but the effect on occupational status is comparatively small. The evidence is mixed, however, as both male and female dropouts are more likely to be unemployed, though the effect is larger for males.

McNamara, Sarah (2020), Returns to Higher Education and Dropouts: A Double Machine Learning Approach, ZEW Discussion Paper Nr. 20-084, Mannheim.

Autoren/-innen Sarah McNamara