Party Competition with Costly Voting

Thomas Mustillo ()
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Thomas Mustillo: https://keough.nd.edu/about/faculty-staff-directory/tom-mustillo

Journal of Artificial Societies and Social Simulation, 2026, vol. 29, issue 3, 4

Abstract: This study investigates political party competition within a two-dimensional policy space. It departs from existing computational models that typically assume full turnout. Specifically, it extends Laver and Sergenti’s (2012) ``baseline'' (chapter 5) framework by examining the impact of voting costs on six party system outcomes: voter turnout & citizen representation, mean party & winner eccentricity (i.e., polarization), and voter & abstainer profiles. Using agent-based simulations that vary the number of parties, voting costs, and party strategies (all-hunter, all-aggregator, and all-sticker party systems), the study finds that costly voting increases party eccentricity in small all-hunter systems, while reducing it in large all-hunter systems. It also finds that the ability of all-aggregator party systems to maximize citizen representation erodes with increases in voting costs. Across all types of party systems, it finds that abstainers arise at the extremes of the policy space, and grow more moderate as costs rise. Theoretically and methodologically, the research uses experiments in a computational setting, and applies fractional polynomial regression to analyze the effect sizes of the inputs on the outcomes. The models, which integrate classic spatial models of party competition with the ``calculus of voting model,'' yield results which reveal complex interdependence between voting behavior, party behavior, and system-level properties.

Keywords: Spatial Model of Party Competitio; Voter Turnout; Costly Voting; Agent-Based Model; Political Polarization; Centroidal Voronoi Tessellation; Lloyd's Algorithm (search for similar items in EconPapers)
Date: 2026-06-30
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Persistent link: https://EconPapers.repec.org/RePEc:jas:jasssj:2024-179-3

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