Work

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

Year: 2013
Type: preprint
Abstract: 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.
Language: English
Subfield: Safety Research
Open Access status: green
OpenAlex ID: W10624164
Cites: 91
Cited by: 17
Related to: 10