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The Distortion of Public-Spirited Participatory Budgeting

AAAI 2025 · Learning theory and algorithms › Submodular and game algorithms · approach: Committee voting rules · 1 citations (OpenAlex)

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Theoretical study of distortion in public-spirited participatory budgeting, showing linear barriers for standard ballots and proposing a rank-of-predefined-bundles ballot with sublinear, logarithmic, and constant distortion protocols.

Problem

Participatory budgeting aggregates voter ballots into a budget-feasible project set; with unrestricted utilities, standard ballot formats and deterministic rules incur unbounded or large welfare distortion. The paper asks whether public-spirited voters allow low distortion in PB.

Approach

Extends the public-spirited voting model of Flanigan et al. to PB with additive values, proves linear distortion lower bounds for deterministic rules on existing ballots, and introduces a ranking-of-predefined-bundles ballot whose multi-round protocols achieve sublinear, logarithmic, and constant distortion.

Key results

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace individual-project rankings with high-low bundle rankingsCopeland in deterministic PB · PBdistortion: O(m/γ²_min) -> O(√m/γ²_min)Helped
Use two-round tiered-cost bundle rankings after project rankingsCopeland in deterministic PB · PBdistortion: O(log(m)/γ⁴_min)Helped
Use two-round exhaustive bundle rankings after project rankingsCopeland in deterministic PB · PBdistortion: O(1/γ⁴_min)Helped
Use project rankings with a deterministic PB aggregation ruleDeterministic PB rules · PBdistortion: Ω(m/γmin)Hurt
Use project rankings with a randomized PB aggregation ruleRandomized PB rules · PBdistortion: Ω(log(m))Hurt
Use rankings by value for moneyDeterministic PB rules · PBdistortion: ∞Hurt
Use k-approval ballots with k > 1Deterministic PB rules · PBdistortion: ∞Hurt
Use 1-approval ballotsDeterministic PB rules · PBdistortion: Ω(m²/γmin)Hurt
Use knapsack ballotsDeterministic PB rules · PBdistortion: Ω(m/γmin)Hurt
Use threshold approval ballotsDeterministic PB rules · PBdistortion: Ω(m)Hurt

Surprising findings

Limitations

Experimental setup

Datasets: 1244 real PB elections from pabulib.org

Metrics: distortion number of bundles ranked per alternative

Baselines: rankings by value-for-money k-approval knapsack ballots threshold approval plurality

Builds on: Flanigan, Procaccia, and Wang (2023) public-spirited voting Benadè et al. (2021) PB distortion under unit-sum utilities Copeland rule Maximal Lottery

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