Education economists and others have examined the concept and implications of repayment burdens (RBs) for more than a quarter of a century. Defined simply, a RB is the proportion of a person’s income per period that needs to be allocated to repay a debt.
There are several approaches available for calculations of RBs which capture the fundamental role of graduate income distributions. We will use the parametric approach because it is a standard tool for exercises of this nature.
We employ the unconditional quantile regression (UQR) technique to estimate earnings functions. This provides a disaggregation of income distributions: we are able to learn the effects for the poorest graduates. This approach allows insight into the critical policy question for MLs: are RBs at the bottom of the graduate income distributions such as to suggest that this form of loan has the capacity to severely and negatively impact on the most disadvantaged of debtors.
Our RB technique can be applied to several countries with ICL, such as England and Australia, by addressing the hypothetical question of what the circumstances would be for their graduate debtors if current ICL systems were to be replaced with ML financing approaches. We will extend the range of these RB studies to include several interesting additional countries, which include Ireland and China.