2024/07/01 by Brian Hedden, Jacob M. Nebel · 1 citation
Economics, Econometrics and Finance · Social Sciences · #Aggregate (composite) #Arrow's impossibility theorem #Data aggregator #Economic Theory and Institutions #Game Theory and Voting Systems #Impossibility #Income, Poverty, and Inequality #Salient #Scale (ratio) #Social choice theory #Variety (cybernetics)
paper · doi:10.1215/00318108-11249629
published in The Philosophical Review 133(3), 265-308 (Duke University Press)
openalex publication_date 2024/07/01 · openalex created_date 2026/03/14 · openalex updated_date 2026/06/16
Multidimensional concepts are everywhere, and they are important. Examples include moral value, welfare, scientific confirmation, democracy, and biodiversity. How, if at all, can we aggregate the underlying dimensions of a multidimensional concept F to yield verdicts about which things are Fer than which overall? Social choice theory can be used to model and investigate this aggregation problem. This article focuses on a particularly thorny problem made salient by this social choice-theoretic framework: the underlying dimensions of a given concept might be measurable on different types of scales—for example, some ordinal and some cardinal. An underappreciated impossibility theorem due to Anna Khmelnitskaya shows that seemingly plausible constraints on aggregation across scale types are inconsistent. This impossibility threatens to render the notion of overall Fness incoherent. This article attempts to defuse this threat, arguing that the impossibility depends on an overly restrictive conception of measurement and of how measurement constrains aggregation. Adopting a more flexible—and, the authors think, more perspicuous—conception of measurement opens an array of possibilities for aggregation across disparate scale types.