Strategy-Proof Budgeting via a VCG-Like Mechanism

Jonathan Wagner, Reshef Meir

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present a strategy-proof public goods budgeting mechanism where agents determine both the total volume of expenses and specific allocation. It is constructed as a modification of VCG to a non-typical environment, where we do not assume quasi-linear utilities or direct revelation. We further show that under plausible assumptions it satisfies strategyproofness in strictly dominant strategies, and consequently implements the social optimum as a Coalition-Proof Nash Equilibrium. A primary (albeit not an exclusive) motivation of our model is Participatory Budgeting, where members of a community collectively decide the spending policy of public tax dollars. In that scenario, charging individual payments from voters as the VCG method instructs would be undesirable, thus our second main result provides that, under further specifications relevant in that context, these payments will vanish in large populations, and can further be constructed as non-positive in some cases.

Original languageEnglish
Title of host publicationAlgorithmic Game Theory - 16th International Symposium, SAGT 2023, Proceedings
EditorsArgyrios Deligkas, Aris Filos-Ratsikas
PublisherSpringer Science and Business Media Deutschland GmbH
Pages401-418
Number of pages18
ISBN (Print)9783031432538
DOIs
StatePublished - 2023
EventProceedings of the 16th International Symposium on Algorithmic Game Theory, SAGT 2023 - Egham, United Kingdom
Duration: 4 Sep 20237 Sep 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14238 LNCS

Conference

ConferenceProceedings of the 16th International Symposium on Algorithmic Game Theory, SAGT 2023
Country/TerritoryUnited Kingdom
CityEgham
Period4/09/237/09/23

Keywords

  • Participatory Budgeting
  • VCG

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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