Previous estimates of inequality of opportunity (IOp) are lower bounds because of the unobservability of the full set of endowed characteristics beyond the sphere of individual responsibility. Knowing the true size of unfair IOp, however, is important for the acceptance of (some) inequality and...

This paper suggests multidimensional affluence measures for the top of the distribution. In contrast to commonly used top income shares, they allow the analysis of the extent, intensity and breadth of affluence in several dimensions within a common framework. We illustrate this by analyzing the...

Previous estimates of unfair inequality of opportunity (IOp) are only lower bounds because of the unobservability of the full set of endowed circumstances beyond the sphere of individual responsibility. In this paper, we suggest a new estimator based on a fixed effects panel model which...

Previous estimates of unfair inequality of opportunity (IOp) are only lower bounds because of the unobservability of the full set of endowed circumstances beyond the sphere of individual responsibility. In this paper, we suggest a new estimator based on a fixed effects panel model which...

Previous estimates of unfair inequality of opportunity (IOp) are only lower bounds because of the unobservability of the full set of endowed circumstances beyond the sphere of individual responsibility. In this paper, we suggest a new estimator based on a fixed effects panel model which...

Previous estimates of unfair inequality of opportunity (IOp) are only lower bounds because of the unobservability of the full set of endowed circumstances beyond the sphere of individual responsibility. In this paper, we suggest a new estimator based on a fixed effects panel model which...