The geometry of distributional preferences and a non-parametric identification approach

This paper proposes a geometric delineation of distributional preference types and a non-parametric approach for their identification in a two-person context. It starts with a small set of assumptions on preferences and shows that this set (i) naturally results in a taxonomy of distributional archetypes that nests all empirically relevant types considered in previous work in economics and social psychology; and (ii) gives rise to a clean experimental test design that discriminates between archetypes according to core features of preferences rather than properties of specific modelling variants. As a by-product the test yields a two-dimensional index of preference intensity.