Estimating heterogeneous returns to college by cognitive and non-cognitive ability

Recent work has highlighted the significant variation in returns to higher education across individuals. I develop a novel methodology --- exploiting recent advances in the identification of mixture models --- which groups individuals according to their prior ability and estimates the wage returns to a university degree by group, and show that the model is non-parametrically identified. Applying the method to data from a UK cohort study, the findings reflect recent evidence that skills and ability are multidimensional. The flexible model allows the returns to university to vary across the (multi-dimensional) ability distribution, a flexibility missing from commonly used additive models, but which I show is empirically important. Returns are generally increasing in ability for both men and women, but vary non-monotonically across the ability distribution.