Measuring overeducation with earnings frontiers and multiply imputed censored income data

In this paper, we remove one serious drawback of the IAB employment sample impeding its applicability to the estimation of earnings frontiers: the censoring of the income data, by multiple imputation. Then, we estimate individual potential income with stochastic earnings frontiers, and we measure overeducation as the ratio between actual income and potential income. It is shown that the measurement of overeducation by this income ratio is a valuable addition to the overeducation literature because the well-established objective or subjective overeducation measures focus on some ordinal matching aspects and ignore the metric income and efficiency aspects of overeducation.