Portioning Using Ordinal Preferences: Fairness and Efficiency

Stéphane Airiau (), Haris Aziz, Ioannis Caragiannis, Justin Kruger, Jérôme Lang () and Dominik Peters ()
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Stéphane Airiau: LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique
Haris Aziz: UNSW - University of New South Wales [Sydney], CSIRO - Data61 [Canberra] - ANU - Australian National University - CSIRO - Commonwealth Scientific and Industrial Research Organisation [Australia]
Ioannis Caragiannis: Aarhus University [Aarhus]
Justin Kruger: LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique
Jérôme Lang: CNRS - Centre National de la Recherche Scientifique, LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique
Dominik Peters: LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique

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Abstract: A divisible public resource is to be divided among projects. We study rules that decide on a distribution of the budget when voters have ordinal preference rankings over projects. Examples of such portioning problems are participatory budgeting, time shares, and parliament elections. We introduce a family of rules for portioning, inspired by positional scoring rules. Rules in this family are given by a scoring vector (such as plurality or Borda) associating a positive value with each rank in a vote, and an aggregation function such as leximin or the Nash product. Our family contains wellstudied rules, but most are new. We discuss computational and normative properties of our rules. We focus on fairness, and introduce the SD-core, a group fairness notion. Our Nash rules are in the SD-core, and the leximin rules satisfy individual fairness properties. Both are Pareto-efficient.

Keywords: Computational social choice; Voting; Portioning; Public goods; Scoring rules (search for similar items in EconPapers)
Date: 2023-01
New Economics Papers: this item is included in nep-gth
Note: View the original document on HAL open archive server: https://hal.science/hal-03843084v1
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Citations: View citations in EconPapers (1)

Published in Artificial Intelligence, 2023, 314, pp.103809. ⟨10.1016/j.artint.2022.103809⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03843084

DOI: 10.1016/j.artint.2022.103809

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