Lower Bounds and the Linearity Assumption in Parametric Estimations of Inequality of Opportunity

Abstract

The consistent underestimation of inequality of opportunity has led some scholars to call into question the usefulness of such estimates. In this paper we argue that neglecting heterogeneity in the influence of circumstances across types as well as neglecting heterogeneity in type-specific effort distributions are two important sources of the downward bias in inequality of opportunity measures. Compared to the standard parametric approach of ex ante measurement of inequality of opportunity, we calculate a 50% upwards correction when accounting for both sources of heterogeneity. Therefore, taking heterogeneity across types seriously is an important step towards strengthening the policy relevance of this concept.