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on Collective Decision-Making |
| By: | Steven Kivinen (University of Graz, Austria); Norovsambuu Tumennasan (Dalhousie University, Canada) |
| Abstract: | Generalized median voter (GMV) rules on the single-peaked preference domain are group strategy-proof. We show that if incomplete information coexists with the ability to commit to coalitional agreements, then GMV rules can be susceptible to insincere voting by groups with heterogeneous beliefs. We identify strategic compromise as a novel source of insincere voting in this environment. Our two main results characterize the set of fair, efficient, and robust voting rules: those that ensure sincere voting under asymmetric information and coalition formation. Each result uses a different notion of robustness, and both give (at most) two alternatives special treatment, with the remaining alternatives chosen according to a type of consensus. |
| Keywords: | robust group strategy-proofness, voting, median voter |
| JEL: | C71 C78 D70 D80 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:grz:wpaper:2025-15 |
| By: | Matteo Gamalerio, Massimo Morelli, Margherita Negri |
| Abstract: | We show that policies using plurality rule to elect their policymakers are more likely to adopt more restrictive immigration policies than those using dual-ballot systems. Plurality rule provides stronger incentives for right-wing, anti-immigrant parties to run alone, as opposed to joining a coalition with other right-wing parties that offer a less restrictive immigration policy. We prove the result theoretically and empirically. Our theoretical results hold with sincere and strategic voters, with and without endogenous turnout, and can be extended to the comparison between plurality rule and proportional representation without majority bonuses in parliamentary elections. Empirically, we combine municipal-level data on migration-related expenditures and mayoral elections and establish causality using a regression discontinuity design. |
| Keywords: | Electoral Rules, Immigration, Salience |
| JEL: | D72 J24 J61 R23 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:baf:cbafwp:cbafwp25260 |
| By: | Berliant, Marcus; Gouveia, Miguel |
| Abstract: | The political economy setting of voting over general nonlinear income taxes with labor disincentives and information asymmetry in consumer/worker/voter types is considered. The economy is the realization of a finite draw from a continuous distribution. The revenue required from a draw is determined by Pareto optimal provision of a public good for that draw. Assuming that the government must meet the revenue requirement for any possible draw, in other words the tax is robust, a majority rule equilibrium is shown to exist at the median voter's preferred tax function out of this robust set. |
| Keywords: | Voting; Income taxation; Public good; Robustness |
| JEL: | D72 D82 H21 H41 |
| Date: | 2025–10–29 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:126649 |
| By: | Levin Hornischer (LMU - Ludwig Maximilian University [Munich] = Ludwig Maximilians Universität München); Zoi Terzopoulou (GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - UL2 - Université Lumière - Lyon 2 - UJM - Université Jean Monnet - Saint-Étienne - EM - EMLyon Business School - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | Can neural networks be applied in voting theory, while satisfying the need for transparency in collective decisions? We propose axiomatic deep voting: a framework to build and evaluate neural networks that aggregate preferences, using the wellestablished axiomatic method of voting theory. Our findings are: (1) Neural networks, despite being highly accurate, often fail to align with the core axioms of voting rules, revealing a disconnect between mimicking outcomes and reasoning. ( 2) Training with axiom-specific data does not enhance alignment with those axioms. (3) By solely optimizing axiom satisfaction, neural networks can synthesize new voting rules that often surpass and substantially differ from existing ones. This offers insights for both fields: For AI, important concepts like bias and value-alignment are studied in a mathematically rigorous way; for voting theory, new areas of the space of voting rules are explored. |
| Keywords: | Voting theory, Neural networks |
| Date: | 2025–08–05 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05395413 |