Ballot Design and Electoral Outcomes: The Role of Candidate Order and Party Affiliation

TL;DR

This study uses causal inference to show that ballot design, especially candidate order and party designations, significantly influences voter behavior and election outcomes, highlighting the importance of ballot layout in electoral fairness.

Contribution

It provides the first causal analysis of how mixed ballot designs with and without party designations affect voter accuracy and election results using natural experiments and advanced machine learning methods.

Findings

11.8% of Democratic voters cast incorrect votes due to ballot design

15.4% of Republican voters cast incorrect votes due to ballot design

Ballots with mixed contest types mislead voters, impacting election outcomes

Abstract

We use causal inference to study how designing ballots with and without party designations impacts electoral outcomes when partisan voters rely on party-order cues to infer candidate affiliation in races without designations. If the party orders of candidates in races with and without party designations differ, these voters might cast their votes incorrectly. We identify a quasi-randomized natural experiment with contest-level treatment assignment pertaining to North Carolina judicial elections and use double machine learning to accurately capture the magnitude of such incorrectly cast votes. Using precinct-level election and demographic data, we estimate that 11.8% (95% confidence interval: [4.0%, 19.6%]) of democratic partisan voters and 15.4% (95% confidence interval: [7.8%, 23.1%]) of republican partisan voters cast their votes incorrectly due to the difference in party orders. Our results indicate that ballots mixing contests with and without party designations mislead many voters, leading to outcomes that do not reflect true voter preferences. To accurately capture voter intent, such ballot designs should be avoided.