Participation Incentives in Randomized Social Choice

TL;DR

This paper investigates how randomized social choice functions can balance Pareto efficiency and participation incentives, especially under DL and SD preferences, highlighting the maximal recursive rule's strong participation properties.

Contribution

It establishes formal relations between participation notions under SD and DL and demonstrates the maximal recursive rule's strong participation guarantees.

Findings

Maximal recursive rule satisfies strong participation under SD and DL.

Formal relations between SD and DL participation notions are established.

Results contribute to understanding incentive-compatible randomized voting rules.

Abstract

When aggregating preferences of agents via voting, two desirable goals are to identify outcomes that are Pareto optimal and to incentivize agents to participate in the voting process. We consider participation notions as formalized by Brandl, Brandt, and Hofbauer (2015) and study how far efficiency and participation are achievable by randomized social choice functions in particular when agents' preferences are downward lexicographic (DL) or satisfy stochastic dominance (SD). Our results include the followings ones: we prove formal relations between the participation notions with respect to SD and DL and we show that the maximal recursive rule satisfies very strong participation with respect to both SD and DL.