Effect of Electoral Seat Bias on Political Polarization: A Computational Perspective

TL;DR

This paper investigates how electoral systems with a bias towards large parties can increase political polarization, using agent-based simulations to analyze voter behavior over multiple election cycles.

Contribution

It introduces a computational simulation approach to study the impact of electoral seat bias on polarization, incorporating complex voter behavior patterns.

Findings

Electoral systems with larger-party bias lead to higher polarization.

Simulation results confirm the hypothesis linking seat bias to polarization.

The Mehlhaff index effectively measures polarization changes.

Abstract

Research on the causes of political polarization points towards multiple drivers of the problem, from social and psychological to economic and technological. However, political institutions stand out, because -- while capable of exacerbating or alleviating polarization -- they can be re-engineered more readily than others. Accordingly, we analyze one class of such institutions -- electoral systems -- investigating whether the large-party seat bias found in many common systems (particularly plurality and Jefferson-D'Hondt) exacerbates polarization. Cross-national empirical data being relatively sparse and heavily confounded, we use computational methods: an agent-based Monte Carlo simulation. We model voter behavior over multiple electoral cycles, building upon the classic spatial model, but incorporating other known voter behavior patterns, such as the bandwagon effect, strategic voting, preference updating, retrospective voting, and the thermostatic effect. We confirm our hypothesis that electoral systems with a stronger large-party bias exhibit significantly higher polarization, as measured by the Mehlhaff index.