The Price of Proportional Representation in Temporal Voting

arXiv:2605.1115781.5
AI Analysis

For researchers in computational social choice, this work provides the first formal analysis of the efficiency cost of proportionality in temporal voting, revealing a trade-off between fairness and welfare.

The paper quantifies the welfare loss from enforcing proportional representation in temporal voting, showing it grows sublinearly with voters or rounds. For JR, welfare loss vanishes asymptotically, but stronger axioms cause persistent conflict.

We study proportional representation in the temporal voting model, where collective decisions are made repeatedly over time over a fixed horizon. Prior work has extensively investigated how proportional representation axioms from multiwinner voting (e.g., justified representation (JR) and its variants) can be adapted, satisfied, and verified in this setting. However, much less is understood about their interaction with social welfare. In this work, we quantify the efficiency cost of enforcing proportionality. We formalize the welfare-proportionality tension via the worst-case ratio between the maximum achievable utilitarian welfare and the maximum welfare attainable subject to a proportionality axiom. We show that imposing proportional representation in the temporal setting can incur a growing, yet sublinear, welfare loss as the number of voters or rounds increases. We further identify a clean separation among axioms: for JR, the welfare loss diminishes as the time horizon grows and vanishes asymptotically, whereas for stronger axioms this conflict persists even with many rounds. Moreover, we prove that welfare maximization under each axiom is NP-complete and APX-hard, even under static preferences and bounded-degree approvals, and provide fixed-parameter algorithms under several natural structural parameters.

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